Line data Source code
1 : /*************************************************************************
2 : ALGLIB 3.17.0 (source code generated 2020-12-27)
3 : Copyright (c) Sergey Bochkanov (ALGLIB project).
4 :
5 : >>> SOURCE LICENSE >>>
6 : This program is free software; you can redistribute it and/or modify
7 : it under the terms of the GNU General Public License as published by
8 : the Free Software Foundation (www.fsf.org); either version 2 of the
9 : License, or (at your option) any later version.
10 :
11 : This program is distributed in the hope that it will be useful,
12 : but WITHOUT ANY WARRANTY; without even the implied warranty of
13 : MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
14 : GNU General Public License for more details.
15 :
16 : A copy of the GNU General Public License is available at
17 : http://www.fsf.org/licensing/licenses
18 : >>> END OF LICENSE >>>
19 : *************************************************************************/
20 : #ifdef _MSC_VER
21 : #define _CRT_SECURE_NO_WARNINGS
22 : #endif
23 : #include "stdafx.h"
24 : #include "statistics.h"
25 :
26 : // disable some irrelevant warnings
27 : #if (AE_COMPILER==AE_MSVC) && !defined(AE_ALL_WARNINGS)
28 : #pragma warning(disable:4100)
29 : #pragma warning(disable:4127)
30 : #pragma warning(disable:4611)
31 : #pragma warning(disable:4702)
32 : #pragma warning(disable:4996)
33 : #endif
34 :
35 : /////////////////////////////////////////////////////////////////////////
36 : //
37 : // THIS SECTION CONTAINS IMPLEMENTATION OF C++ INTERFACE
38 : //
39 : /////////////////////////////////////////////////////////////////////////
40 : namespace alglib
41 : {
42 :
43 : #if defined(AE_COMPILE_BASESTAT) || !defined(AE_PARTIAL_BUILD)
44 :
45 : #endif
46 :
47 : #if defined(AE_COMPILE_WSR) || !defined(AE_PARTIAL_BUILD)
48 :
49 : #endif
50 :
51 : #if defined(AE_COMPILE_STEST) || !defined(AE_PARTIAL_BUILD)
52 :
53 : #endif
54 :
55 : #if defined(AE_COMPILE_CORRELATIONTESTS) || !defined(AE_PARTIAL_BUILD)
56 :
57 : #endif
58 :
59 : #if defined(AE_COMPILE_STUDENTTTESTS) || !defined(AE_PARTIAL_BUILD)
60 :
61 : #endif
62 :
63 : #if defined(AE_COMPILE_MANNWHITNEYU) || !defined(AE_PARTIAL_BUILD)
64 :
65 : #endif
66 :
67 : #if defined(AE_COMPILE_JARQUEBERA) || !defined(AE_PARTIAL_BUILD)
68 :
69 : #endif
70 :
71 : #if defined(AE_COMPILE_VARIANCETESTS) || !defined(AE_PARTIAL_BUILD)
72 :
73 : #endif
74 :
75 : #if defined(AE_COMPILE_BASESTAT) || !defined(AE_PARTIAL_BUILD)
76 : /*************************************************************************
77 : Calculation of the distribution moments: mean, variance, skewness, kurtosis.
78 :
79 : INPUT PARAMETERS:
80 : X - sample
81 : N - N>=0, sample size:
82 : * if given, only leading N elements of X are processed
83 : * if not given, automatically determined from size of X
84 :
85 : OUTPUT PARAMETERS
86 : Mean - mean.
87 : Variance- variance.
88 : Skewness- skewness (if variance<>0; zero otherwise).
89 : Kurtosis- kurtosis (if variance<>0; zero otherwise).
90 :
91 : NOTE: variance is calculated by dividing sum of squares by N-1, not N.
92 :
93 : -- ALGLIB --
94 : Copyright 06.09.2006 by Bochkanov Sergey
95 : *************************************************************************/
96 0 : void samplemoments(const real_1d_array &x, const ae_int_t n, double &mean, double &variance, double &skewness, double &kurtosis, const xparams _xparams)
97 : {
98 : jmp_buf _break_jump;
99 : alglib_impl::ae_state _alglib_env_state;
100 0 : alglib_impl::ae_state_init(&_alglib_env_state);
101 0 : if( setjmp(_break_jump) )
102 : {
103 : #if !defined(AE_NO_EXCEPTIONS)
104 0 : _ALGLIB_CPP_EXCEPTION(_alglib_env_state.error_msg);
105 : #else
106 : _ALGLIB_SET_ERROR_FLAG(_alglib_env_state.error_msg);
107 : return;
108 : #endif
109 : }
110 0 : ae_state_set_break_jump(&_alglib_env_state, &_break_jump);
111 0 : if( _xparams.flags!=0x0 )
112 0 : ae_state_set_flags(&_alglib_env_state, _xparams.flags);
113 0 : alglib_impl::samplemoments(const_cast<alglib_impl::ae_vector*>(x.c_ptr()), n, &mean, &variance, &skewness, &kurtosis, &_alglib_env_state);
114 0 : alglib_impl::ae_state_clear(&_alglib_env_state);
115 0 : return;
116 : }
117 :
118 : /*************************************************************************
119 : Calculation of the distribution moments: mean, variance, skewness, kurtosis.
120 :
121 : INPUT PARAMETERS:
122 : X - sample
123 : N - N>=0, sample size:
124 : * if given, only leading N elements of X are processed
125 : * if not given, automatically determined from size of X
126 :
127 : OUTPUT PARAMETERS
128 : Mean - mean.
129 : Variance- variance.
130 : Skewness- skewness (if variance<>0; zero otherwise).
131 : Kurtosis- kurtosis (if variance<>0; zero otherwise).
132 :
133 : NOTE: variance is calculated by dividing sum of squares by N-1, not N.
134 :
135 : -- ALGLIB --
136 : Copyright 06.09.2006 by Bochkanov Sergey
137 : *************************************************************************/
138 : #if !defined(AE_NO_EXCEPTIONS)
139 0 : void samplemoments(const real_1d_array &x, double &mean, double &variance, double &skewness, double &kurtosis, const xparams _xparams)
140 : {
141 : jmp_buf _break_jump;
142 : alglib_impl::ae_state _alglib_env_state;
143 : ae_int_t n;
144 :
145 0 : n = x.length();
146 0 : alglib_impl::ae_state_init(&_alglib_env_state);
147 0 : if( setjmp(_break_jump) )
148 0 : _ALGLIB_CPP_EXCEPTION(_alglib_env_state.error_msg);
149 0 : ae_state_set_break_jump(&_alglib_env_state, &_break_jump);
150 0 : if( _xparams.flags!=0x0 )
151 0 : ae_state_set_flags(&_alglib_env_state, _xparams.flags);
152 0 : alglib_impl::samplemoments(const_cast<alglib_impl::ae_vector*>(x.c_ptr()), n, &mean, &variance, &skewness, &kurtosis, &_alglib_env_state);
153 :
154 0 : alglib_impl::ae_state_clear(&_alglib_env_state);
155 0 : return;
156 : }
157 : #endif
158 :
159 : /*************************************************************************
160 : Calculation of the mean.
161 :
162 : INPUT PARAMETERS:
163 : X - sample
164 : N - N>=0, sample size:
165 : * if given, only leading N elements of X are processed
166 : * if not given, automatically determined from size of X
167 :
168 : NOTE:
169 :
170 : This function return result which calculated by 'SampleMoments' function
171 : and stored at 'Mean' variable.
172 :
173 :
174 : -- ALGLIB --
175 : Copyright 06.09.2006 by Bochkanov Sergey
176 : *************************************************************************/
177 0 : double samplemean(const real_1d_array &x, const ae_int_t n, const xparams _xparams)
178 : {
179 : jmp_buf _break_jump;
180 : alglib_impl::ae_state _alglib_env_state;
181 0 : alglib_impl::ae_state_init(&_alglib_env_state);
182 0 : if( setjmp(_break_jump) )
183 : {
184 : #if !defined(AE_NO_EXCEPTIONS)
185 0 : _ALGLIB_CPP_EXCEPTION(_alglib_env_state.error_msg);
186 : #else
187 : _ALGLIB_SET_ERROR_FLAG(_alglib_env_state.error_msg);
188 : return 0;
189 : #endif
190 : }
191 0 : ae_state_set_break_jump(&_alglib_env_state, &_break_jump);
192 0 : if( _xparams.flags!=0x0 )
193 0 : ae_state_set_flags(&_alglib_env_state, _xparams.flags);
194 0 : double result = alglib_impl::samplemean(const_cast<alglib_impl::ae_vector*>(x.c_ptr()), n, &_alglib_env_state);
195 0 : alglib_impl::ae_state_clear(&_alglib_env_state);
196 0 : return *(reinterpret_cast<double*>(&result));
197 : }
198 :
199 : /*************************************************************************
200 : Calculation of the mean.
201 :
202 : INPUT PARAMETERS:
203 : X - sample
204 : N - N>=0, sample size:
205 : * if given, only leading N elements of X are processed
206 : * if not given, automatically determined from size of X
207 :
208 : NOTE:
209 :
210 : This function return result which calculated by 'SampleMoments' function
211 : and stored at 'Mean' variable.
212 :
213 :
214 : -- ALGLIB --
215 : Copyright 06.09.2006 by Bochkanov Sergey
216 : *************************************************************************/
217 : #if !defined(AE_NO_EXCEPTIONS)
218 0 : double samplemean(const real_1d_array &x, const xparams _xparams)
219 : {
220 : jmp_buf _break_jump;
221 : alglib_impl::ae_state _alglib_env_state;
222 : ae_int_t n;
223 :
224 0 : n = x.length();
225 0 : alglib_impl::ae_state_init(&_alglib_env_state);
226 0 : if( setjmp(_break_jump) )
227 0 : _ALGLIB_CPP_EXCEPTION(_alglib_env_state.error_msg);
228 0 : ae_state_set_break_jump(&_alglib_env_state, &_break_jump);
229 0 : if( _xparams.flags!=0x0 )
230 0 : ae_state_set_flags(&_alglib_env_state, _xparams.flags);
231 0 : double result = alglib_impl::samplemean(const_cast<alglib_impl::ae_vector*>(x.c_ptr()), n, &_alglib_env_state);
232 :
233 0 : alglib_impl::ae_state_clear(&_alglib_env_state);
234 0 : return *(reinterpret_cast<double*>(&result));
235 : }
236 : #endif
237 :
238 : /*************************************************************************
239 : Calculation of the variance.
240 :
241 : INPUT PARAMETERS:
242 : X - sample
243 : N - N>=0, sample size:
244 : * if given, only leading N elements of X are processed
245 : * if not given, automatically determined from size of X
246 :
247 : NOTE:
248 :
249 : This function return result which calculated by 'SampleMoments' function
250 : and stored at 'Variance' variable.
251 :
252 :
253 : -- ALGLIB --
254 : Copyright 06.09.2006 by Bochkanov Sergey
255 : *************************************************************************/
256 0 : double samplevariance(const real_1d_array &x, const ae_int_t n, const xparams _xparams)
257 : {
258 : jmp_buf _break_jump;
259 : alglib_impl::ae_state _alglib_env_state;
260 0 : alglib_impl::ae_state_init(&_alglib_env_state);
261 0 : if( setjmp(_break_jump) )
262 : {
263 : #if !defined(AE_NO_EXCEPTIONS)
264 0 : _ALGLIB_CPP_EXCEPTION(_alglib_env_state.error_msg);
265 : #else
266 : _ALGLIB_SET_ERROR_FLAG(_alglib_env_state.error_msg);
267 : return 0;
268 : #endif
269 : }
270 0 : ae_state_set_break_jump(&_alglib_env_state, &_break_jump);
271 0 : if( _xparams.flags!=0x0 )
272 0 : ae_state_set_flags(&_alglib_env_state, _xparams.flags);
273 0 : double result = alglib_impl::samplevariance(const_cast<alglib_impl::ae_vector*>(x.c_ptr()), n, &_alglib_env_state);
274 0 : alglib_impl::ae_state_clear(&_alglib_env_state);
275 0 : return *(reinterpret_cast<double*>(&result));
276 : }
277 :
278 : /*************************************************************************
279 : Calculation of the variance.
280 :
281 : INPUT PARAMETERS:
282 : X - sample
283 : N - N>=0, sample size:
284 : * if given, only leading N elements of X are processed
285 : * if not given, automatically determined from size of X
286 :
287 : NOTE:
288 :
289 : This function return result which calculated by 'SampleMoments' function
290 : and stored at 'Variance' variable.
291 :
292 :
293 : -- ALGLIB --
294 : Copyright 06.09.2006 by Bochkanov Sergey
295 : *************************************************************************/
296 : #if !defined(AE_NO_EXCEPTIONS)
297 0 : double samplevariance(const real_1d_array &x, const xparams _xparams)
298 : {
299 : jmp_buf _break_jump;
300 : alglib_impl::ae_state _alglib_env_state;
301 : ae_int_t n;
302 :
303 0 : n = x.length();
304 0 : alglib_impl::ae_state_init(&_alglib_env_state);
305 0 : if( setjmp(_break_jump) )
306 0 : _ALGLIB_CPP_EXCEPTION(_alglib_env_state.error_msg);
307 0 : ae_state_set_break_jump(&_alglib_env_state, &_break_jump);
308 0 : if( _xparams.flags!=0x0 )
309 0 : ae_state_set_flags(&_alglib_env_state, _xparams.flags);
310 0 : double result = alglib_impl::samplevariance(const_cast<alglib_impl::ae_vector*>(x.c_ptr()), n, &_alglib_env_state);
311 :
312 0 : alglib_impl::ae_state_clear(&_alglib_env_state);
313 0 : return *(reinterpret_cast<double*>(&result));
314 : }
315 : #endif
316 :
317 : /*************************************************************************
318 : Calculation of the skewness.
319 :
320 : INPUT PARAMETERS:
321 : X - sample
322 : N - N>=0, sample size:
323 : * if given, only leading N elements of X are processed
324 : * if not given, automatically determined from size of X
325 :
326 : NOTE:
327 :
328 : This function return result which calculated by 'SampleMoments' function
329 : and stored at 'Skewness' variable.
330 :
331 :
332 : -- ALGLIB --
333 : Copyright 06.09.2006 by Bochkanov Sergey
334 : *************************************************************************/
335 0 : double sampleskewness(const real_1d_array &x, const ae_int_t n, const xparams _xparams)
336 : {
337 : jmp_buf _break_jump;
338 : alglib_impl::ae_state _alglib_env_state;
339 0 : alglib_impl::ae_state_init(&_alglib_env_state);
340 0 : if( setjmp(_break_jump) )
341 : {
342 : #if !defined(AE_NO_EXCEPTIONS)
343 0 : _ALGLIB_CPP_EXCEPTION(_alglib_env_state.error_msg);
344 : #else
345 : _ALGLIB_SET_ERROR_FLAG(_alglib_env_state.error_msg);
346 : return 0;
347 : #endif
348 : }
349 0 : ae_state_set_break_jump(&_alglib_env_state, &_break_jump);
350 0 : if( _xparams.flags!=0x0 )
351 0 : ae_state_set_flags(&_alglib_env_state, _xparams.flags);
352 0 : double result = alglib_impl::sampleskewness(const_cast<alglib_impl::ae_vector*>(x.c_ptr()), n, &_alglib_env_state);
353 0 : alglib_impl::ae_state_clear(&_alglib_env_state);
354 0 : return *(reinterpret_cast<double*>(&result));
355 : }
356 :
357 : /*************************************************************************
358 : Calculation of the skewness.
359 :
360 : INPUT PARAMETERS:
361 : X - sample
362 : N - N>=0, sample size:
363 : * if given, only leading N elements of X are processed
364 : * if not given, automatically determined from size of X
365 :
366 : NOTE:
367 :
368 : This function return result which calculated by 'SampleMoments' function
369 : and stored at 'Skewness' variable.
370 :
371 :
372 : -- ALGLIB --
373 : Copyright 06.09.2006 by Bochkanov Sergey
374 : *************************************************************************/
375 : #if !defined(AE_NO_EXCEPTIONS)
376 0 : double sampleskewness(const real_1d_array &x, const xparams _xparams)
377 : {
378 : jmp_buf _break_jump;
379 : alglib_impl::ae_state _alglib_env_state;
380 : ae_int_t n;
381 :
382 0 : n = x.length();
383 0 : alglib_impl::ae_state_init(&_alglib_env_state);
384 0 : if( setjmp(_break_jump) )
385 0 : _ALGLIB_CPP_EXCEPTION(_alglib_env_state.error_msg);
386 0 : ae_state_set_break_jump(&_alglib_env_state, &_break_jump);
387 0 : if( _xparams.flags!=0x0 )
388 0 : ae_state_set_flags(&_alglib_env_state, _xparams.flags);
389 0 : double result = alglib_impl::sampleskewness(const_cast<alglib_impl::ae_vector*>(x.c_ptr()), n, &_alglib_env_state);
390 :
391 0 : alglib_impl::ae_state_clear(&_alglib_env_state);
392 0 : return *(reinterpret_cast<double*>(&result));
393 : }
394 : #endif
395 :
396 : /*************************************************************************
397 : Calculation of the kurtosis.
398 :
399 : INPUT PARAMETERS:
400 : X - sample
401 : N - N>=0, sample size:
402 : * if given, only leading N elements of X are processed
403 : * if not given, automatically determined from size of X
404 :
405 : NOTE:
406 :
407 : This function return result which calculated by 'SampleMoments' function
408 : and stored at 'Kurtosis' variable.
409 :
410 :
411 : -- ALGLIB --
412 : Copyright 06.09.2006 by Bochkanov Sergey
413 : *************************************************************************/
414 0 : double samplekurtosis(const real_1d_array &x, const ae_int_t n, const xparams _xparams)
415 : {
416 : jmp_buf _break_jump;
417 : alglib_impl::ae_state _alglib_env_state;
418 0 : alglib_impl::ae_state_init(&_alglib_env_state);
419 0 : if( setjmp(_break_jump) )
420 : {
421 : #if !defined(AE_NO_EXCEPTIONS)
422 0 : _ALGLIB_CPP_EXCEPTION(_alglib_env_state.error_msg);
423 : #else
424 : _ALGLIB_SET_ERROR_FLAG(_alglib_env_state.error_msg);
425 : return 0;
426 : #endif
427 : }
428 0 : ae_state_set_break_jump(&_alglib_env_state, &_break_jump);
429 0 : if( _xparams.flags!=0x0 )
430 0 : ae_state_set_flags(&_alglib_env_state, _xparams.flags);
431 0 : double result = alglib_impl::samplekurtosis(const_cast<alglib_impl::ae_vector*>(x.c_ptr()), n, &_alglib_env_state);
432 0 : alglib_impl::ae_state_clear(&_alglib_env_state);
433 0 : return *(reinterpret_cast<double*>(&result));
434 : }
435 :
436 : /*************************************************************************
437 : Calculation of the kurtosis.
438 :
439 : INPUT PARAMETERS:
440 : X - sample
441 : N - N>=0, sample size:
442 : * if given, only leading N elements of X are processed
443 : * if not given, automatically determined from size of X
444 :
445 : NOTE:
446 :
447 : This function return result which calculated by 'SampleMoments' function
448 : and stored at 'Kurtosis' variable.
449 :
450 :
451 : -- ALGLIB --
452 : Copyright 06.09.2006 by Bochkanov Sergey
453 : *************************************************************************/
454 : #if !defined(AE_NO_EXCEPTIONS)
455 0 : double samplekurtosis(const real_1d_array &x, const xparams _xparams)
456 : {
457 : jmp_buf _break_jump;
458 : alglib_impl::ae_state _alglib_env_state;
459 : ae_int_t n;
460 :
461 0 : n = x.length();
462 0 : alglib_impl::ae_state_init(&_alglib_env_state);
463 0 : if( setjmp(_break_jump) )
464 0 : _ALGLIB_CPP_EXCEPTION(_alglib_env_state.error_msg);
465 0 : ae_state_set_break_jump(&_alglib_env_state, &_break_jump);
466 0 : if( _xparams.flags!=0x0 )
467 0 : ae_state_set_flags(&_alglib_env_state, _xparams.flags);
468 0 : double result = alglib_impl::samplekurtosis(const_cast<alglib_impl::ae_vector*>(x.c_ptr()), n, &_alglib_env_state);
469 :
470 0 : alglib_impl::ae_state_clear(&_alglib_env_state);
471 0 : return *(reinterpret_cast<double*>(&result));
472 : }
473 : #endif
474 :
475 : /*************************************************************************
476 : ADev
477 :
478 : Input parameters:
479 : X - sample
480 : N - N>=0, sample size:
481 : * if given, only leading N elements of X are processed
482 : * if not given, automatically determined from size of X
483 :
484 : Output parameters:
485 : ADev- ADev
486 :
487 : -- ALGLIB --
488 : Copyright 06.09.2006 by Bochkanov Sergey
489 : *************************************************************************/
490 0 : void sampleadev(const real_1d_array &x, const ae_int_t n, double &adev, const xparams _xparams)
491 : {
492 : jmp_buf _break_jump;
493 : alglib_impl::ae_state _alglib_env_state;
494 0 : alglib_impl::ae_state_init(&_alglib_env_state);
495 0 : if( setjmp(_break_jump) )
496 : {
497 : #if !defined(AE_NO_EXCEPTIONS)
498 0 : _ALGLIB_CPP_EXCEPTION(_alglib_env_state.error_msg);
499 : #else
500 : _ALGLIB_SET_ERROR_FLAG(_alglib_env_state.error_msg);
501 : return;
502 : #endif
503 : }
504 0 : ae_state_set_break_jump(&_alglib_env_state, &_break_jump);
505 0 : if( _xparams.flags!=0x0 )
506 0 : ae_state_set_flags(&_alglib_env_state, _xparams.flags);
507 0 : alglib_impl::sampleadev(const_cast<alglib_impl::ae_vector*>(x.c_ptr()), n, &adev, &_alglib_env_state);
508 0 : alglib_impl::ae_state_clear(&_alglib_env_state);
509 0 : return;
510 : }
511 :
512 : /*************************************************************************
513 : ADev
514 :
515 : Input parameters:
516 : X - sample
517 : N - N>=0, sample size:
518 : * if given, only leading N elements of X are processed
519 : * if not given, automatically determined from size of X
520 :
521 : Output parameters:
522 : ADev- ADev
523 :
524 : -- ALGLIB --
525 : Copyright 06.09.2006 by Bochkanov Sergey
526 : *************************************************************************/
527 : #if !defined(AE_NO_EXCEPTIONS)
528 0 : void sampleadev(const real_1d_array &x, double &adev, const xparams _xparams)
529 : {
530 : jmp_buf _break_jump;
531 : alglib_impl::ae_state _alglib_env_state;
532 : ae_int_t n;
533 :
534 0 : n = x.length();
535 0 : alglib_impl::ae_state_init(&_alglib_env_state);
536 0 : if( setjmp(_break_jump) )
537 0 : _ALGLIB_CPP_EXCEPTION(_alglib_env_state.error_msg);
538 0 : ae_state_set_break_jump(&_alglib_env_state, &_break_jump);
539 0 : if( _xparams.flags!=0x0 )
540 0 : ae_state_set_flags(&_alglib_env_state, _xparams.flags);
541 0 : alglib_impl::sampleadev(const_cast<alglib_impl::ae_vector*>(x.c_ptr()), n, &adev, &_alglib_env_state);
542 :
543 0 : alglib_impl::ae_state_clear(&_alglib_env_state);
544 0 : return;
545 : }
546 : #endif
547 :
548 : /*************************************************************************
549 : Median calculation.
550 :
551 : Input parameters:
552 : X - sample (array indexes: [0..N-1])
553 : N - N>=0, sample size:
554 : * if given, only leading N elements of X are processed
555 : * if not given, automatically determined from size of X
556 :
557 : Output parameters:
558 : Median
559 :
560 : -- ALGLIB --
561 : Copyright 06.09.2006 by Bochkanov Sergey
562 : *************************************************************************/
563 0 : void samplemedian(const real_1d_array &x, const ae_int_t n, double &median, const xparams _xparams)
564 : {
565 : jmp_buf _break_jump;
566 : alglib_impl::ae_state _alglib_env_state;
567 0 : alglib_impl::ae_state_init(&_alglib_env_state);
568 0 : if( setjmp(_break_jump) )
569 : {
570 : #if !defined(AE_NO_EXCEPTIONS)
571 0 : _ALGLIB_CPP_EXCEPTION(_alglib_env_state.error_msg);
572 : #else
573 : _ALGLIB_SET_ERROR_FLAG(_alglib_env_state.error_msg);
574 : return;
575 : #endif
576 : }
577 0 : ae_state_set_break_jump(&_alglib_env_state, &_break_jump);
578 0 : if( _xparams.flags!=0x0 )
579 0 : ae_state_set_flags(&_alglib_env_state, _xparams.flags);
580 0 : alglib_impl::samplemedian(const_cast<alglib_impl::ae_vector*>(x.c_ptr()), n, &median, &_alglib_env_state);
581 0 : alglib_impl::ae_state_clear(&_alglib_env_state);
582 0 : return;
583 : }
584 :
585 : /*************************************************************************
586 : Median calculation.
587 :
588 : Input parameters:
589 : X - sample (array indexes: [0..N-1])
590 : N - N>=0, sample size:
591 : * if given, only leading N elements of X are processed
592 : * if not given, automatically determined from size of X
593 :
594 : Output parameters:
595 : Median
596 :
597 : -- ALGLIB --
598 : Copyright 06.09.2006 by Bochkanov Sergey
599 : *************************************************************************/
600 : #if !defined(AE_NO_EXCEPTIONS)
601 0 : void samplemedian(const real_1d_array &x, double &median, const xparams _xparams)
602 : {
603 : jmp_buf _break_jump;
604 : alglib_impl::ae_state _alglib_env_state;
605 : ae_int_t n;
606 :
607 0 : n = x.length();
608 0 : alglib_impl::ae_state_init(&_alglib_env_state);
609 0 : if( setjmp(_break_jump) )
610 0 : _ALGLIB_CPP_EXCEPTION(_alglib_env_state.error_msg);
611 0 : ae_state_set_break_jump(&_alglib_env_state, &_break_jump);
612 0 : if( _xparams.flags!=0x0 )
613 0 : ae_state_set_flags(&_alglib_env_state, _xparams.flags);
614 0 : alglib_impl::samplemedian(const_cast<alglib_impl::ae_vector*>(x.c_ptr()), n, &median, &_alglib_env_state);
615 :
616 0 : alglib_impl::ae_state_clear(&_alglib_env_state);
617 0 : return;
618 : }
619 : #endif
620 :
621 : /*************************************************************************
622 : Percentile calculation.
623 :
624 : Input parameters:
625 : X - sample (array indexes: [0..N-1])
626 : N - N>=0, sample size:
627 : * if given, only leading N elements of X are processed
628 : * if not given, automatically determined from size of X
629 : P - percentile (0<=P<=1)
630 :
631 : Output parameters:
632 : V - percentile
633 :
634 : -- ALGLIB --
635 : Copyright 01.03.2008 by Bochkanov Sergey
636 : *************************************************************************/
637 0 : void samplepercentile(const real_1d_array &x, const ae_int_t n, const double p, double &v, const xparams _xparams)
638 : {
639 : jmp_buf _break_jump;
640 : alglib_impl::ae_state _alglib_env_state;
641 0 : alglib_impl::ae_state_init(&_alglib_env_state);
642 0 : if( setjmp(_break_jump) )
643 : {
644 : #if !defined(AE_NO_EXCEPTIONS)
645 0 : _ALGLIB_CPP_EXCEPTION(_alglib_env_state.error_msg);
646 : #else
647 : _ALGLIB_SET_ERROR_FLAG(_alglib_env_state.error_msg);
648 : return;
649 : #endif
650 : }
651 0 : ae_state_set_break_jump(&_alglib_env_state, &_break_jump);
652 0 : if( _xparams.flags!=0x0 )
653 0 : ae_state_set_flags(&_alglib_env_state, _xparams.flags);
654 0 : alglib_impl::samplepercentile(const_cast<alglib_impl::ae_vector*>(x.c_ptr()), n, p, &v, &_alglib_env_state);
655 0 : alglib_impl::ae_state_clear(&_alglib_env_state);
656 0 : return;
657 : }
658 :
659 : /*************************************************************************
660 : Percentile calculation.
661 :
662 : Input parameters:
663 : X - sample (array indexes: [0..N-1])
664 : N - N>=0, sample size:
665 : * if given, only leading N elements of X are processed
666 : * if not given, automatically determined from size of X
667 : P - percentile (0<=P<=1)
668 :
669 : Output parameters:
670 : V - percentile
671 :
672 : -- ALGLIB --
673 : Copyright 01.03.2008 by Bochkanov Sergey
674 : *************************************************************************/
675 : #if !defined(AE_NO_EXCEPTIONS)
676 0 : void samplepercentile(const real_1d_array &x, const double p, double &v, const xparams _xparams)
677 : {
678 : jmp_buf _break_jump;
679 : alglib_impl::ae_state _alglib_env_state;
680 : ae_int_t n;
681 :
682 0 : n = x.length();
683 0 : alglib_impl::ae_state_init(&_alglib_env_state);
684 0 : if( setjmp(_break_jump) )
685 0 : _ALGLIB_CPP_EXCEPTION(_alglib_env_state.error_msg);
686 0 : ae_state_set_break_jump(&_alglib_env_state, &_break_jump);
687 0 : if( _xparams.flags!=0x0 )
688 0 : ae_state_set_flags(&_alglib_env_state, _xparams.flags);
689 0 : alglib_impl::samplepercentile(const_cast<alglib_impl::ae_vector*>(x.c_ptr()), n, p, &v, &_alglib_env_state);
690 :
691 0 : alglib_impl::ae_state_clear(&_alglib_env_state);
692 0 : return;
693 : }
694 : #endif
695 :
696 : /*************************************************************************
697 : 2-sample covariance
698 :
699 : Input parameters:
700 : X - sample 1 (array indexes: [0..N-1])
701 : Y - sample 2 (array indexes: [0..N-1])
702 : N - N>=0, sample size:
703 : * if given, only N leading elements of X/Y are processed
704 : * if not given, automatically determined from input sizes
705 :
706 : Result:
707 : covariance (zero for N=0 or N=1)
708 :
709 : -- ALGLIB --
710 : Copyright 28.10.2010 by Bochkanov Sergey
711 : *************************************************************************/
712 0 : double cov2(const real_1d_array &x, const real_1d_array &y, const ae_int_t n, const xparams _xparams)
713 : {
714 : jmp_buf _break_jump;
715 : alglib_impl::ae_state _alglib_env_state;
716 0 : alglib_impl::ae_state_init(&_alglib_env_state);
717 0 : if( setjmp(_break_jump) )
718 : {
719 : #if !defined(AE_NO_EXCEPTIONS)
720 0 : _ALGLIB_CPP_EXCEPTION(_alglib_env_state.error_msg);
721 : #else
722 : _ALGLIB_SET_ERROR_FLAG(_alglib_env_state.error_msg);
723 : return 0;
724 : #endif
725 : }
726 0 : ae_state_set_break_jump(&_alglib_env_state, &_break_jump);
727 0 : if( _xparams.flags!=0x0 )
728 0 : ae_state_set_flags(&_alglib_env_state, _xparams.flags);
729 0 : double result = alglib_impl::cov2(const_cast<alglib_impl::ae_vector*>(x.c_ptr()), const_cast<alglib_impl::ae_vector*>(y.c_ptr()), n, &_alglib_env_state);
730 0 : alglib_impl::ae_state_clear(&_alglib_env_state);
731 0 : return *(reinterpret_cast<double*>(&result));
732 : }
733 :
734 : /*************************************************************************
735 : 2-sample covariance
736 :
737 : Input parameters:
738 : X - sample 1 (array indexes: [0..N-1])
739 : Y - sample 2 (array indexes: [0..N-1])
740 : N - N>=0, sample size:
741 : * if given, only N leading elements of X/Y are processed
742 : * if not given, automatically determined from input sizes
743 :
744 : Result:
745 : covariance (zero for N=0 or N=1)
746 :
747 : -- ALGLIB --
748 : Copyright 28.10.2010 by Bochkanov Sergey
749 : *************************************************************************/
750 : #if !defined(AE_NO_EXCEPTIONS)
751 0 : double cov2(const real_1d_array &x, const real_1d_array &y, const xparams _xparams)
752 : {
753 : jmp_buf _break_jump;
754 : alglib_impl::ae_state _alglib_env_state;
755 : ae_int_t n;
756 0 : if( (x.length()!=y.length()))
757 0 : _ALGLIB_CPP_EXCEPTION("Error while calling 'cov2': looks like one of arguments has wrong size");
758 0 : n = x.length();
759 0 : alglib_impl::ae_state_init(&_alglib_env_state);
760 0 : if( setjmp(_break_jump) )
761 0 : _ALGLIB_CPP_EXCEPTION(_alglib_env_state.error_msg);
762 0 : ae_state_set_break_jump(&_alglib_env_state, &_break_jump);
763 0 : if( _xparams.flags!=0x0 )
764 0 : ae_state_set_flags(&_alglib_env_state, _xparams.flags);
765 0 : double result = alglib_impl::cov2(const_cast<alglib_impl::ae_vector*>(x.c_ptr()), const_cast<alglib_impl::ae_vector*>(y.c_ptr()), n, &_alglib_env_state);
766 :
767 0 : alglib_impl::ae_state_clear(&_alglib_env_state);
768 0 : return *(reinterpret_cast<double*>(&result));
769 : }
770 : #endif
771 :
772 : /*************************************************************************
773 : Pearson product-moment correlation coefficient
774 :
775 : Input parameters:
776 : X - sample 1 (array indexes: [0..N-1])
777 : Y - sample 2 (array indexes: [0..N-1])
778 : N - N>=0, sample size:
779 : * if given, only N leading elements of X/Y are processed
780 : * if not given, automatically determined from input sizes
781 :
782 : Result:
783 : Pearson product-moment correlation coefficient
784 : (zero for N=0 or N=1)
785 :
786 : -- ALGLIB --
787 : Copyright 28.10.2010 by Bochkanov Sergey
788 : *************************************************************************/
789 0 : double pearsoncorr2(const real_1d_array &x, const real_1d_array &y, const ae_int_t n, const xparams _xparams)
790 : {
791 : jmp_buf _break_jump;
792 : alglib_impl::ae_state _alglib_env_state;
793 0 : alglib_impl::ae_state_init(&_alglib_env_state);
794 0 : if( setjmp(_break_jump) )
795 : {
796 : #if !defined(AE_NO_EXCEPTIONS)
797 0 : _ALGLIB_CPP_EXCEPTION(_alglib_env_state.error_msg);
798 : #else
799 : _ALGLIB_SET_ERROR_FLAG(_alglib_env_state.error_msg);
800 : return 0;
801 : #endif
802 : }
803 0 : ae_state_set_break_jump(&_alglib_env_state, &_break_jump);
804 0 : if( _xparams.flags!=0x0 )
805 0 : ae_state_set_flags(&_alglib_env_state, _xparams.flags);
806 0 : double result = alglib_impl::pearsoncorr2(const_cast<alglib_impl::ae_vector*>(x.c_ptr()), const_cast<alglib_impl::ae_vector*>(y.c_ptr()), n, &_alglib_env_state);
807 0 : alglib_impl::ae_state_clear(&_alglib_env_state);
808 0 : return *(reinterpret_cast<double*>(&result));
809 : }
810 :
811 : /*************************************************************************
812 : Pearson product-moment correlation coefficient
813 :
814 : Input parameters:
815 : X - sample 1 (array indexes: [0..N-1])
816 : Y - sample 2 (array indexes: [0..N-1])
817 : N - N>=0, sample size:
818 : * if given, only N leading elements of X/Y are processed
819 : * if not given, automatically determined from input sizes
820 :
821 : Result:
822 : Pearson product-moment correlation coefficient
823 : (zero for N=0 or N=1)
824 :
825 : -- ALGLIB --
826 : Copyright 28.10.2010 by Bochkanov Sergey
827 : *************************************************************************/
828 : #if !defined(AE_NO_EXCEPTIONS)
829 0 : double pearsoncorr2(const real_1d_array &x, const real_1d_array &y, const xparams _xparams)
830 : {
831 : jmp_buf _break_jump;
832 : alglib_impl::ae_state _alglib_env_state;
833 : ae_int_t n;
834 0 : if( (x.length()!=y.length()))
835 0 : _ALGLIB_CPP_EXCEPTION("Error while calling 'pearsoncorr2': looks like one of arguments has wrong size");
836 0 : n = x.length();
837 0 : alglib_impl::ae_state_init(&_alglib_env_state);
838 0 : if( setjmp(_break_jump) )
839 0 : _ALGLIB_CPP_EXCEPTION(_alglib_env_state.error_msg);
840 0 : ae_state_set_break_jump(&_alglib_env_state, &_break_jump);
841 0 : if( _xparams.flags!=0x0 )
842 0 : ae_state_set_flags(&_alglib_env_state, _xparams.flags);
843 0 : double result = alglib_impl::pearsoncorr2(const_cast<alglib_impl::ae_vector*>(x.c_ptr()), const_cast<alglib_impl::ae_vector*>(y.c_ptr()), n, &_alglib_env_state);
844 :
845 0 : alglib_impl::ae_state_clear(&_alglib_env_state);
846 0 : return *(reinterpret_cast<double*>(&result));
847 : }
848 : #endif
849 :
850 : /*************************************************************************
851 : Spearman's rank correlation coefficient
852 :
853 : Input parameters:
854 : X - sample 1 (array indexes: [0..N-1])
855 : Y - sample 2 (array indexes: [0..N-1])
856 : N - N>=0, sample size:
857 : * if given, only N leading elements of X/Y are processed
858 : * if not given, automatically determined from input sizes
859 :
860 : Result:
861 : Spearman's rank correlation coefficient
862 : (zero for N=0 or N=1)
863 :
864 : -- ALGLIB --
865 : Copyright 09.04.2007 by Bochkanov Sergey
866 : *************************************************************************/
867 0 : double spearmancorr2(const real_1d_array &x, const real_1d_array &y, const ae_int_t n, const xparams _xparams)
868 : {
869 : jmp_buf _break_jump;
870 : alglib_impl::ae_state _alglib_env_state;
871 0 : alglib_impl::ae_state_init(&_alglib_env_state);
872 0 : if( setjmp(_break_jump) )
873 : {
874 : #if !defined(AE_NO_EXCEPTIONS)
875 0 : _ALGLIB_CPP_EXCEPTION(_alglib_env_state.error_msg);
876 : #else
877 : _ALGLIB_SET_ERROR_FLAG(_alglib_env_state.error_msg);
878 : return 0;
879 : #endif
880 : }
881 0 : ae_state_set_break_jump(&_alglib_env_state, &_break_jump);
882 0 : if( _xparams.flags!=0x0 )
883 0 : ae_state_set_flags(&_alglib_env_state, _xparams.flags);
884 0 : double result = alglib_impl::spearmancorr2(const_cast<alglib_impl::ae_vector*>(x.c_ptr()), const_cast<alglib_impl::ae_vector*>(y.c_ptr()), n, &_alglib_env_state);
885 0 : alglib_impl::ae_state_clear(&_alglib_env_state);
886 0 : return *(reinterpret_cast<double*>(&result));
887 : }
888 :
889 : /*************************************************************************
890 : Spearman's rank correlation coefficient
891 :
892 : Input parameters:
893 : X - sample 1 (array indexes: [0..N-1])
894 : Y - sample 2 (array indexes: [0..N-1])
895 : N - N>=0, sample size:
896 : * if given, only N leading elements of X/Y are processed
897 : * if not given, automatically determined from input sizes
898 :
899 : Result:
900 : Spearman's rank correlation coefficient
901 : (zero for N=0 or N=1)
902 :
903 : -- ALGLIB --
904 : Copyright 09.04.2007 by Bochkanov Sergey
905 : *************************************************************************/
906 : #if !defined(AE_NO_EXCEPTIONS)
907 0 : double spearmancorr2(const real_1d_array &x, const real_1d_array &y, const xparams _xparams)
908 : {
909 : jmp_buf _break_jump;
910 : alglib_impl::ae_state _alglib_env_state;
911 : ae_int_t n;
912 0 : if( (x.length()!=y.length()))
913 0 : _ALGLIB_CPP_EXCEPTION("Error while calling 'spearmancorr2': looks like one of arguments has wrong size");
914 0 : n = x.length();
915 0 : alglib_impl::ae_state_init(&_alglib_env_state);
916 0 : if( setjmp(_break_jump) )
917 0 : _ALGLIB_CPP_EXCEPTION(_alglib_env_state.error_msg);
918 0 : ae_state_set_break_jump(&_alglib_env_state, &_break_jump);
919 0 : if( _xparams.flags!=0x0 )
920 0 : ae_state_set_flags(&_alglib_env_state, _xparams.flags);
921 0 : double result = alglib_impl::spearmancorr2(const_cast<alglib_impl::ae_vector*>(x.c_ptr()), const_cast<alglib_impl::ae_vector*>(y.c_ptr()), n, &_alglib_env_state);
922 :
923 0 : alglib_impl::ae_state_clear(&_alglib_env_state);
924 0 : return *(reinterpret_cast<double*>(&result));
925 : }
926 : #endif
927 :
928 : /*************************************************************************
929 : Covariance matrix
930 :
931 : ! COMMERCIAL EDITION OF ALGLIB:
932 : !
933 : ! Commercial Edition of ALGLIB includes following important improvements
934 : ! of this function:
935 : ! * high-performance native backend with same C# interface (C# version)
936 : ! * multithreading support (C++ and C# versions)
937 : ! * hardware vendor (Intel) implementations of linear algebra primitives
938 : ! (C++ and C# versions, x86/x64 platform)
939 : !
940 : ! We recommend you to read 'Working with commercial version' section of
941 : ! ALGLIB Reference Manual in order to find out how to use performance-
942 : ! related features provided by commercial edition of ALGLIB.
943 :
944 : INPUT PARAMETERS:
945 : X - array[N,M], sample matrix:
946 : * J-th column corresponds to J-th variable
947 : * I-th row corresponds to I-th observation
948 : N - N>=0, number of observations:
949 : * if given, only leading N rows of X are used
950 : * if not given, automatically determined from input size
951 : M - M>0, number of variables:
952 : * if given, only leading M columns of X are used
953 : * if not given, automatically determined from input size
954 :
955 : OUTPUT PARAMETERS:
956 : C - array[M,M], covariance matrix (zero if N=0 or N=1)
957 :
958 : -- ALGLIB --
959 : Copyright 28.10.2010 by Bochkanov Sergey
960 : *************************************************************************/
961 0 : void covm(const real_2d_array &x, const ae_int_t n, const ae_int_t m, real_2d_array &c, const xparams _xparams)
962 : {
963 : jmp_buf _break_jump;
964 : alglib_impl::ae_state _alglib_env_state;
965 0 : alglib_impl::ae_state_init(&_alglib_env_state);
966 0 : if( setjmp(_break_jump) )
967 : {
968 : #if !defined(AE_NO_EXCEPTIONS)
969 0 : _ALGLIB_CPP_EXCEPTION(_alglib_env_state.error_msg);
970 : #else
971 : _ALGLIB_SET_ERROR_FLAG(_alglib_env_state.error_msg);
972 : return;
973 : #endif
974 : }
975 0 : ae_state_set_break_jump(&_alglib_env_state, &_break_jump);
976 0 : if( _xparams.flags!=0x0 )
977 0 : ae_state_set_flags(&_alglib_env_state, _xparams.flags);
978 0 : alglib_impl::covm(const_cast<alglib_impl::ae_matrix*>(x.c_ptr()), n, m, const_cast<alglib_impl::ae_matrix*>(c.c_ptr()), &_alglib_env_state);
979 0 : alglib_impl::ae_state_clear(&_alglib_env_state);
980 0 : return;
981 : }
982 :
983 : /*************************************************************************
984 : Covariance matrix
985 :
986 : ! COMMERCIAL EDITION OF ALGLIB:
987 : !
988 : ! Commercial Edition of ALGLIB includes following important improvements
989 : ! of this function:
990 : ! * high-performance native backend with same C# interface (C# version)
991 : ! * multithreading support (C++ and C# versions)
992 : ! * hardware vendor (Intel) implementations of linear algebra primitives
993 : ! (C++ and C# versions, x86/x64 platform)
994 : !
995 : ! We recommend you to read 'Working with commercial version' section of
996 : ! ALGLIB Reference Manual in order to find out how to use performance-
997 : ! related features provided by commercial edition of ALGLIB.
998 :
999 : INPUT PARAMETERS:
1000 : X - array[N,M], sample matrix:
1001 : * J-th column corresponds to J-th variable
1002 : * I-th row corresponds to I-th observation
1003 : N - N>=0, number of observations:
1004 : * if given, only leading N rows of X are used
1005 : * if not given, automatically determined from input size
1006 : M - M>0, number of variables:
1007 : * if given, only leading M columns of X are used
1008 : * if not given, automatically determined from input size
1009 :
1010 : OUTPUT PARAMETERS:
1011 : C - array[M,M], covariance matrix (zero if N=0 or N=1)
1012 :
1013 : -- ALGLIB --
1014 : Copyright 28.10.2010 by Bochkanov Sergey
1015 : *************************************************************************/
1016 : #if !defined(AE_NO_EXCEPTIONS)
1017 0 : void covm(const real_2d_array &x, real_2d_array &c, const xparams _xparams)
1018 : {
1019 : jmp_buf _break_jump;
1020 : alglib_impl::ae_state _alglib_env_state;
1021 : ae_int_t n;
1022 : ae_int_t m;
1023 :
1024 0 : n = x.rows();
1025 0 : m = x.cols();
1026 0 : alglib_impl::ae_state_init(&_alglib_env_state);
1027 0 : if( setjmp(_break_jump) )
1028 0 : _ALGLIB_CPP_EXCEPTION(_alglib_env_state.error_msg);
1029 0 : ae_state_set_break_jump(&_alglib_env_state, &_break_jump);
1030 0 : if( _xparams.flags!=0x0 )
1031 0 : ae_state_set_flags(&_alglib_env_state, _xparams.flags);
1032 0 : alglib_impl::covm(const_cast<alglib_impl::ae_matrix*>(x.c_ptr()), n, m, const_cast<alglib_impl::ae_matrix*>(c.c_ptr()), &_alglib_env_state);
1033 :
1034 0 : alglib_impl::ae_state_clear(&_alglib_env_state);
1035 0 : return;
1036 : }
1037 : #endif
1038 :
1039 : /*************************************************************************
1040 : Pearson product-moment correlation matrix
1041 :
1042 : ! COMMERCIAL EDITION OF ALGLIB:
1043 : !
1044 : ! Commercial Edition of ALGLIB includes following important improvements
1045 : ! of this function:
1046 : ! * high-performance native backend with same C# interface (C# version)
1047 : ! * multithreading support (C++ and C# versions)
1048 : ! * hardware vendor (Intel) implementations of linear algebra primitives
1049 : ! (C++ and C# versions, x86/x64 platform)
1050 : !
1051 : ! We recommend you to read 'Working with commercial version' section of
1052 : ! ALGLIB Reference Manual in order to find out how to use performance-
1053 : ! related features provided by commercial edition of ALGLIB.
1054 :
1055 : INPUT PARAMETERS:
1056 : X - array[N,M], sample matrix:
1057 : * J-th column corresponds to J-th variable
1058 : * I-th row corresponds to I-th observation
1059 : N - N>=0, number of observations:
1060 : * if given, only leading N rows of X are used
1061 : * if not given, automatically determined from input size
1062 : M - M>0, number of variables:
1063 : * if given, only leading M columns of X are used
1064 : * if not given, automatically determined from input size
1065 :
1066 : OUTPUT PARAMETERS:
1067 : C - array[M,M], correlation matrix (zero if N=0 or N=1)
1068 :
1069 : -- ALGLIB --
1070 : Copyright 28.10.2010 by Bochkanov Sergey
1071 : *************************************************************************/
1072 0 : void pearsoncorrm(const real_2d_array &x, const ae_int_t n, const ae_int_t m, real_2d_array &c, const xparams _xparams)
1073 : {
1074 : jmp_buf _break_jump;
1075 : alglib_impl::ae_state _alglib_env_state;
1076 0 : alglib_impl::ae_state_init(&_alglib_env_state);
1077 0 : if( setjmp(_break_jump) )
1078 : {
1079 : #if !defined(AE_NO_EXCEPTIONS)
1080 0 : _ALGLIB_CPP_EXCEPTION(_alglib_env_state.error_msg);
1081 : #else
1082 : _ALGLIB_SET_ERROR_FLAG(_alglib_env_state.error_msg);
1083 : return;
1084 : #endif
1085 : }
1086 0 : ae_state_set_break_jump(&_alglib_env_state, &_break_jump);
1087 0 : if( _xparams.flags!=0x0 )
1088 0 : ae_state_set_flags(&_alglib_env_state, _xparams.flags);
1089 0 : alglib_impl::pearsoncorrm(const_cast<alglib_impl::ae_matrix*>(x.c_ptr()), n, m, const_cast<alglib_impl::ae_matrix*>(c.c_ptr()), &_alglib_env_state);
1090 0 : alglib_impl::ae_state_clear(&_alglib_env_state);
1091 0 : return;
1092 : }
1093 :
1094 : /*************************************************************************
1095 : Pearson product-moment correlation matrix
1096 :
1097 : ! COMMERCIAL EDITION OF ALGLIB:
1098 : !
1099 : ! Commercial Edition of ALGLIB includes following important improvements
1100 : ! of this function:
1101 : ! * high-performance native backend with same C# interface (C# version)
1102 : ! * multithreading support (C++ and C# versions)
1103 : ! * hardware vendor (Intel) implementations of linear algebra primitives
1104 : ! (C++ and C# versions, x86/x64 platform)
1105 : !
1106 : ! We recommend you to read 'Working with commercial version' section of
1107 : ! ALGLIB Reference Manual in order to find out how to use performance-
1108 : ! related features provided by commercial edition of ALGLIB.
1109 :
1110 : INPUT PARAMETERS:
1111 : X - array[N,M], sample matrix:
1112 : * J-th column corresponds to J-th variable
1113 : * I-th row corresponds to I-th observation
1114 : N - N>=0, number of observations:
1115 : * if given, only leading N rows of X are used
1116 : * if not given, automatically determined from input size
1117 : M - M>0, number of variables:
1118 : * if given, only leading M columns of X are used
1119 : * if not given, automatically determined from input size
1120 :
1121 : OUTPUT PARAMETERS:
1122 : C - array[M,M], correlation matrix (zero if N=0 or N=1)
1123 :
1124 : -- ALGLIB --
1125 : Copyright 28.10.2010 by Bochkanov Sergey
1126 : *************************************************************************/
1127 : #if !defined(AE_NO_EXCEPTIONS)
1128 0 : void pearsoncorrm(const real_2d_array &x, real_2d_array &c, const xparams _xparams)
1129 : {
1130 : jmp_buf _break_jump;
1131 : alglib_impl::ae_state _alglib_env_state;
1132 : ae_int_t n;
1133 : ae_int_t m;
1134 :
1135 0 : n = x.rows();
1136 0 : m = x.cols();
1137 0 : alglib_impl::ae_state_init(&_alglib_env_state);
1138 0 : if( setjmp(_break_jump) )
1139 0 : _ALGLIB_CPP_EXCEPTION(_alglib_env_state.error_msg);
1140 0 : ae_state_set_break_jump(&_alglib_env_state, &_break_jump);
1141 0 : if( _xparams.flags!=0x0 )
1142 0 : ae_state_set_flags(&_alglib_env_state, _xparams.flags);
1143 0 : alglib_impl::pearsoncorrm(const_cast<alglib_impl::ae_matrix*>(x.c_ptr()), n, m, const_cast<alglib_impl::ae_matrix*>(c.c_ptr()), &_alglib_env_state);
1144 :
1145 0 : alglib_impl::ae_state_clear(&_alglib_env_state);
1146 0 : return;
1147 : }
1148 : #endif
1149 :
1150 : /*************************************************************************
1151 : Spearman's rank correlation matrix
1152 :
1153 : ! COMMERCIAL EDITION OF ALGLIB:
1154 : !
1155 : ! Commercial Edition of ALGLIB includes following important improvements
1156 : ! of this function:
1157 : ! * high-performance native backend with same C# interface (C# version)
1158 : ! * multithreading support (C++ and C# versions)
1159 : ! * hardware vendor (Intel) implementations of linear algebra primitives
1160 : ! (C++ and C# versions, x86/x64 platform)
1161 : !
1162 : ! We recommend you to read 'Working with commercial version' section of
1163 : ! ALGLIB Reference Manual in order to find out how to use performance-
1164 : ! related features provided by commercial edition of ALGLIB.
1165 :
1166 : INPUT PARAMETERS:
1167 : X - array[N,M], sample matrix:
1168 : * J-th column corresponds to J-th variable
1169 : * I-th row corresponds to I-th observation
1170 : N - N>=0, number of observations:
1171 : * if given, only leading N rows of X are used
1172 : * if not given, automatically determined from input size
1173 : M - M>0, number of variables:
1174 : * if given, only leading M columns of X are used
1175 : * if not given, automatically determined from input size
1176 :
1177 : OUTPUT PARAMETERS:
1178 : C - array[M,M], correlation matrix (zero if N=0 or N=1)
1179 :
1180 : -- ALGLIB --
1181 : Copyright 28.10.2010 by Bochkanov Sergey
1182 : *************************************************************************/
1183 0 : void spearmancorrm(const real_2d_array &x, const ae_int_t n, const ae_int_t m, real_2d_array &c, const xparams _xparams)
1184 : {
1185 : jmp_buf _break_jump;
1186 : alglib_impl::ae_state _alglib_env_state;
1187 0 : alglib_impl::ae_state_init(&_alglib_env_state);
1188 0 : if( setjmp(_break_jump) )
1189 : {
1190 : #if !defined(AE_NO_EXCEPTIONS)
1191 0 : _ALGLIB_CPP_EXCEPTION(_alglib_env_state.error_msg);
1192 : #else
1193 : _ALGLIB_SET_ERROR_FLAG(_alglib_env_state.error_msg);
1194 : return;
1195 : #endif
1196 : }
1197 0 : ae_state_set_break_jump(&_alglib_env_state, &_break_jump);
1198 0 : if( _xparams.flags!=0x0 )
1199 0 : ae_state_set_flags(&_alglib_env_state, _xparams.flags);
1200 0 : alglib_impl::spearmancorrm(const_cast<alglib_impl::ae_matrix*>(x.c_ptr()), n, m, const_cast<alglib_impl::ae_matrix*>(c.c_ptr()), &_alglib_env_state);
1201 0 : alglib_impl::ae_state_clear(&_alglib_env_state);
1202 0 : return;
1203 : }
1204 :
1205 : /*************************************************************************
1206 : Spearman's rank correlation matrix
1207 :
1208 : ! COMMERCIAL EDITION OF ALGLIB:
1209 : !
1210 : ! Commercial Edition of ALGLIB includes following important improvements
1211 : ! of this function:
1212 : ! * high-performance native backend with same C# interface (C# version)
1213 : ! * multithreading support (C++ and C# versions)
1214 : ! * hardware vendor (Intel) implementations of linear algebra primitives
1215 : ! (C++ and C# versions, x86/x64 platform)
1216 : !
1217 : ! We recommend you to read 'Working with commercial version' section of
1218 : ! ALGLIB Reference Manual in order to find out how to use performance-
1219 : ! related features provided by commercial edition of ALGLIB.
1220 :
1221 : INPUT PARAMETERS:
1222 : X - array[N,M], sample matrix:
1223 : * J-th column corresponds to J-th variable
1224 : * I-th row corresponds to I-th observation
1225 : N - N>=0, number of observations:
1226 : * if given, only leading N rows of X are used
1227 : * if not given, automatically determined from input size
1228 : M - M>0, number of variables:
1229 : * if given, only leading M columns of X are used
1230 : * if not given, automatically determined from input size
1231 :
1232 : OUTPUT PARAMETERS:
1233 : C - array[M,M], correlation matrix (zero if N=0 or N=1)
1234 :
1235 : -- ALGLIB --
1236 : Copyright 28.10.2010 by Bochkanov Sergey
1237 : *************************************************************************/
1238 : #if !defined(AE_NO_EXCEPTIONS)
1239 0 : void spearmancorrm(const real_2d_array &x, real_2d_array &c, const xparams _xparams)
1240 : {
1241 : jmp_buf _break_jump;
1242 : alglib_impl::ae_state _alglib_env_state;
1243 : ae_int_t n;
1244 : ae_int_t m;
1245 :
1246 0 : n = x.rows();
1247 0 : m = x.cols();
1248 0 : alglib_impl::ae_state_init(&_alglib_env_state);
1249 0 : if( setjmp(_break_jump) )
1250 0 : _ALGLIB_CPP_EXCEPTION(_alglib_env_state.error_msg);
1251 0 : ae_state_set_break_jump(&_alglib_env_state, &_break_jump);
1252 0 : if( _xparams.flags!=0x0 )
1253 0 : ae_state_set_flags(&_alglib_env_state, _xparams.flags);
1254 0 : alglib_impl::spearmancorrm(const_cast<alglib_impl::ae_matrix*>(x.c_ptr()), n, m, const_cast<alglib_impl::ae_matrix*>(c.c_ptr()), &_alglib_env_state);
1255 :
1256 0 : alglib_impl::ae_state_clear(&_alglib_env_state);
1257 0 : return;
1258 : }
1259 : #endif
1260 :
1261 : /*************************************************************************
1262 : Cross-covariance matrix
1263 :
1264 : ! COMMERCIAL EDITION OF ALGLIB:
1265 : !
1266 : ! Commercial Edition of ALGLIB includes following important improvements
1267 : ! of this function:
1268 : ! * high-performance native backend with same C# interface (C# version)
1269 : ! * multithreading support (C++ and C# versions)
1270 : ! * hardware vendor (Intel) implementations of linear algebra primitives
1271 : ! (C++ and C# versions, x86/x64 platform)
1272 : !
1273 : ! We recommend you to read 'Working with commercial version' section of
1274 : ! ALGLIB Reference Manual in order to find out how to use performance-
1275 : ! related features provided by commercial edition of ALGLIB.
1276 :
1277 : INPUT PARAMETERS:
1278 : X - array[N,M1], sample matrix:
1279 : * J-th column corresponds to J-th variable
1280 : * I-th row corresponds to I-th observation
1281 : Y - array[N,M2], sample matrix:
1282 : * J-th column corresponds to J-th variable
1283 : * I-th row corresponds to I-th observation
1284 : N - N>=0, number of observations:
1285 : * if given, only leading N rows of X/Y are used
1286 : * if not given, automatically determined from input sizes
1287 : M1 - M1>0, number of variables in X:
1288 : * if given, only leading M1 columns of X are used
1289 : * if not given, automatically determined from input size
1290 : M2 - M2>0, number of variables in Y:
1291 : * if given, only leading M1 columns of X are used
1292 : * if not given, automatically determined from input size
1293 :
1294 : OUTPUT PARAMETERS:
1295 : C - array[M1,M2], cross-covariance matrix (zero if N=0 or N=1)
1296 :
1297 : -- ALGLIB --
1298 : Copyright 28.10.2010 by Bochkanov Sergey
1299 : *************************************************************************/
1300 0 : void covm2(const real_2d_array &x, const real_2d_array &y, const ae_int_t n, const ae_int_t m1, const ae_int_t m2, real_2d_array &c, const xparams _xparams)
1301 : {
1302 : jmp_buf _break_jump;
1303 : alglib_impl::ae_state _alglib_env_state;
1304 0 : alglib_impl::ae_state_init(&_alglib_env_state);
1305 0 : if( setjmp(_break_jump) )
1306 : {
1307 : #if !defined(AE_NO_EXCEPTIONS)
1308 0 : _ALGLIB_CPP_EXCEPTION(_alglib_env_state.error_msg);
1309 : #else
1310 : _ALGLIB_SET_ERROR_FLAG(_alglib_env_state.error_msg);
1311 : return;
1312 : #endif
1313 : }
1314 0 : ae_state_set_break_jump(&_alglib_env_state, &_break_jump);
1315 0 : if( _xparams.flags!=0x0 )
1316 0 : ae_state_set_flags(&_alglib_env_state, _xparams.flags);
1317 0 : alglib_impl::covm2(const_cast<alglib_impl::ae_matrix*>(x.c_ptr()), const_cast<alglib_impl::ae_matrix*>(y.c_ptr()), n, m1, m2, const_cast<alglib_impl::ae_matrix*>(c.c_ptr()), &_alglib_env_state);
1318 0 : alglib_impl::ae_state_clear(&_alglib_env_state);
1319 0 : return;
1320 : }
1321 :
1322 : /*************************************************************************
1323 : Cross-covariance matrix
1324 :
1325 : ! COMMERCIAL EDITION OF ALGLIB:
1326 : !
1327 : ! Commercial Edition of ALGLIB includes following important improvements
1328 : ! of this function:
1329 : ! * high-performance native backend with same C# interface (C# version)
1330 : ! * multithreading support (C++ and C# versions)
1331 : ! * hardware vendor (Intel) implementations of linear algebra primitives
1332 : ! (C++ and C# versions, x86/x64 platform)
1333 : !
1334 : ! We recommend you to read 'Working with commercial version' section of
1335 : ! ALGLIB Reference Manual in order to find out how to use performance-
1336 : ! related features provided by commercial edition of ALGLIB.
1337 :
1338 : INPUT PARAMETERS:
1339 : X - array[N,M1], sample matrix:
1340 : * J-th column corresponds to J-th variable
1341 : * I-th row corresponds to I-th observation
1342 : Y - array[N,M2], sample matrix:
1343 : * J-th column corresponds to J-th variable
1344 : * I-th row corresponds to I-th observation
1345 : N - N>=0, number of observations:
1346 : * if given, only leading N rows of X/Y are used
1347 : * if not given, automatically determined from input sizes
1348 : M1 - M1>0, number of variables in X:
1349 : * if given, only leading M1 columns of X are used
1350 : * if not given, automatically determined from input size
1351 : M2 - M2>0, number of variables in Y:
1352 : * if given, only leading M1 columns of X are used
1353 : * if not given, automatically determined from input size
1354 :
1355 : OUTPUT PARAMETERS:
1356 : C - array[M1,M2], cross-covariance matrix (zero if N=0 or N=1)
1357 :
1358 : -- ALGLIB --
1359 : Copyright 28.10.2010 by Bochkanov Sergey
1360 : *************************************************************************/
1361 : #if !defined(AE_NO_EXCEPTIONS)
1362 0 : void covm2(const real_2d_array &x, const real_2d_array &y, real_2d_array &c, const xparams _xparams)
1363 : {
1364 : jmp_buf _break_jump;
1365 : alglib_impl::ae_state _alglib_env_state;
1366 : ae_int_t n;
1367 : ae_int_t m1;
1368 : ae_int_t m2;
1369 0 : if( (x.rows()!=y.rows()))
1370 0 : _ALGLIB_CPP_EXCEPTION("Error while calling 'covm2': looks like one of arguments has wrong size");
1371 0 : n = x.rows();
1372 0 : m1 = x.cols();
1373 0 : m2 = y.cols();
1374 0 : alglib_impl::ae_state_init(&_alglib_env_state);
1375 0 : if( setjmp(_break_jump) )
1376 0 : _ALGLIB_CPP_EXCEPTION(_alglib_env_state.error_msg);
1377 0 : ae_state_set_break_jump(&_alglib_env_state, &_break_jump);
1378 0 : if( _xparams.flags!=0x0 )
1379 0 : ae_state_set_flags(&_alglib_env_state, _xparams.flags);
1380 0 : alglib_impl::covm2(const_cast<alglib_impl::ae_matrix*>(x.c_ptr()), const_cast<alglib_impl::ae_matrix*>(y.c_ptr()), n, m1, m2, const_cast<alglib_impl::ae_matrix*>(c.c_ptr()), &_alglib_env_state);
1381 :
1382 0 : alglib_impl::ae_state_clear(&_alglib_env_state);
1383 0 : return;
1384 : }
1385 : #endif
1386 :
1387 : /*************************************************************************
1388 : Pearson product-moment cross-correlation matrix
1389 :
1390 : ! COMMERCIAL EDITION OF ALGLIB:
1391 : !
1392 : ! Commercial Edition of ALGLIB includes following important improvements
1393 : ! of this function:
1394 : ! * high-performance native backend with same C# interface (C# version)
1395 : ! * multithreading support (C++ and C# versions)
1396 : ! * hardware vendor (Intel) implementations of linear algebra primitives
1397 : ! (C++ and C# versions, x86/x64 platform)
1398 : !
1399 : ! We recommend you to read 'Working with commercial version' section of
1400 : ! ALGLIB Reference Manual in order to find out how to use performance-
1401 : ! related features provided by commercial edition of ALGLIB.
1402 :
1403 : INPUT PARAMETERS:
1404 : X - array[N,M1], sample matrix:
1405 : * J-th column corresponds to J-th variable
1406 : * I-th row corresponds to I-th observation
1407 : Y - array[N,M2], sample matrix:
1408 : * J-th column corresponds to J-th variable
1409 : * I-th row corresponds to I-th observation
1410 : N - N>=0, number of observations:
1411 : * if given, only leading N rows of X/Y are used
1412 : * if not given, automatically determined from input sizes
1413 : M1 - M1>0, number of variables in X:
1414 : * if given, only leading M1 columns of X are used
1415 : * if not given, automatically determined from input size
1416 : M2 - M2>0, number of variables in Y:
1417 : * if given, only leading M1 columns of X are used
1418 : * if not given, automatically determined from input size
1419 :
1420 : OUTPUT PARAMETERS:
1421 : C - array[M1,M2], cross-correlation matrix (zero if N=0 or N=1)
1422 :
1423 : -- ALGLIB --
1424 : Copyright 28.10.2010 by Bochkanov Sergey
1425 : *************************************************************************/
1426 0 : void pearsoncorrm2(const real_2d_array &x, const real_2d_array &y, const ae_int_t n, const ae_int_t m1, const ae_int_t m2, real_2d_array &c, const xparams _xparams)
1427 : {
1428 : jmp_buf _break_jump;
1429 : alglib_impl::ae_state _alglib_env_state;
1430 0 : alglib_impl::ae_state_init(&_alglib_env_state);
1431 0 : if( setjmp(_break_jump) )
1432 : {
1433 : #if !defined(AE_NO_EXCEPTIONS)
1434 0 : _ALGLIB_CPP_EXCEPTION(_alglib_env_state.error_msg);
1435 : #else
1436 : _ALGLIB_SET_ERROR_FLAG(_alglib_env_state.error_msg);
1437 : return;
1438 : #endif
1439 : }
1440 0 : ae_state_set_break_jump(&_alglib_env_state, &_break_jump);
1441 0 : if( _xparams.flags!=0x0 )
1442 0 : ae_state_set_flags(&_alglib_env_state, _xparams.flags);
1443 0 : alglib_impl::pearsoncorrm2(const_cast<alglib_impl::ae_matrix*>(x.c_ptr()), const_cast<alglib_impl::ae_matrix*>(y.c_ptr()), n, m1, m2, const_cast<alglib_impl::ae_matrix*>(c.c_ptr()), &_alglib_env_state);
1444 0 : alglib_impl::ae_state_clear(&_alglib_env_state);
1445 0 : return;
1446 : }
1447 :
1448 : /*************************************************************************
1449 : Pearson product-moment cross-correlation matrix
1450 :
1451 : ! COMMERCIAL EDITION OF ALGLIB:
1452 : !
1453 : ! Commercial Edition of ALGLIB includes following important improvements
1454 : ! of this function:
1455 : ! * high-performance native backend with same C# interface (C# version)
1456 : ! * multithreading support (C++ and C# versions)
1457 : ! * hardware vendor (Intel) implementations of linear algebra primitives
1458 : ! (C++ and C# versions, x86/x64 platform)
1459 : !
1460 : ! We recommend you to read 'Working with commercial version' section of
1461 : ! ALGLIB Reference Manual in order to find out how to use performance-
1462 : ! related features provided by commercial edition of ALGLIB.
1463 :
1464 : INPUT PARAMETERS:
1465 : X - array[N,M1], sample matrix:
1466 : * J-th column corresponds to J-th variable
1467 : * I-th row corresponds to I-th observation
1468 : Y - array[N,M2], sample matrix:
1469 : * J-th column corresponds to J-th variable
1470 : * I-th row corresponds to I-th observation
1471 : N - N>=0, number of observations:
1472 : * if given, only leading N rows of X/Y are used
1473 : * if not given, automatically determined from input sizes
1474 : M1 - M1>0, number of variables in X:
1475 : * if given, only leading M1 columns of X are used
1476 : * if not given, automatically determined from input size
1477 : M2 - M2>0, number of variables in Y:
1478 : * if given, only leading M1 columns of X are used
1479 : * if not given, automatically determined from input size
1480 :
1481 : OUTPUT PARAMETERS:
1482 : C - array[M1,M2], cross-correlation matrix (zero if N=0 or N=1)
1483 :
1484 : -- ALGLIB --
1485 : Copyright 28.10.2010 by Bochkanov Sergey
1486 : *************************************************************************/
1487 : #if !defined(AE_NO_EXCEPTIONS)
1488 0 : void pearsoncorrm2(const real_2d_array &x, const real_2d_array &y, real_2d_array &c, const xparams _xparams)
1489 : {
1490 : jmp_buf _break_jump;
1491 : alglib_impl::ae_state _alglib_env_state;
1492 : ae_int_t n;
1493 : ae_int_t m1;
1494 : ae_int_t m2;
1495 0 : if( (x.rows()!=y.rows()))
1496 0 : _ALGLIB_CPP_EXCEPTION("Error while calling 'pearsoncorrm2': looks like one of arguments has wrong size");
1497 0 : n = x.rows();
1498 0 : m1 = x.cols();
1499 0 : m2 = y.cols();
1500 0 : alglib_impl::ae_state_init(&_alglib_env_state);
1501 0 : if( setjmp(_break_jump) )
1502 0 : _ALGLIB_CPP_EXCEPTION(_alglib_env_state.error_msg);
1503 0 : ae_state_set_break_jump(&_alglib_env_state, &_break_jump);
1504 0 : if( _xparams.flags!=0x0 )
1505 0 : ae_state_set_flags(&_alglib_env_state, _xparams.flags);
1506 0 : alglib_impl::pearsoncorrm2(const_cast<alglib_impl::ae_matrix*>(x.c_ptr()), const_cast<alglib_impl::ae_matrix*>(y.c_ptr()), n, m1, m2, const_cast<alglib_impl::ae_matrix*>(c.c_ptr()), &_alglib_env_state);
1507 :
1508 0 : alglib_impl::ae_state_clear(&_alglib_env_state);
1509 0 : return;
1510 : }
1511 : #endif
1512 :
1513 : /*************************************************************************
1514 : Spearman's rank cross-correlation matrix
1515 :
1516 : ! COMMERCIAL EDITION OF ALGLIB:
1517 : !
1518 : ! Commercial Edition of ALGLIB includes following important improvements
1519 : ! of this function:
1520 : ! * high-performance native backend with same C# interface (C# version)
1521 : ! * multithreading support (C++ and C# versions)
1522 : ! * hardware vendor (Intel) implementations of linear algebra primitives
1523 : ! (C++ and C# versions, x86/x64 platform)
1524 : !
1525 : ! We recommend you to read 'Working with commercial version' section of
1526 : ! ALGLIB Reference Manual in order to find out how to use performance-
1527 : ! related features provided by commercial edition of ALGLIB.
1528 :
1529 : INPUT PARAMETERS:
1530 : X - array[N,M1], sample matrix:
1531 : * J-th column corresponds to J-th variable
1532 : * I-th row corresponds to I-th observation
1533 : Y - array[N,M2], sample matrix:
1534 : * J-th column corresponds to J-th variable
1535 : * I-th row corresponds to I-th observation
1536 : N - N>=0, number of observations:
1537 : * if given, only leading N rows of X/Y are used
1538 : * if not given, automatically determined from input sizes
1539 : M1 - M1>0, number of variables in X:
1540 : * if given, only leading M1 columns of X are used
1541 : * if not given, automatically determined from input size
1542 : M2 - M2>0, number of variables in Y:
1543 : * if given, only leading M1 columns of X are used
1544 : * if not given, automatically determined from input size
1545 :
1546 : OUTPUT PARAMETERS:
1547 : C - array[M1,M2], cross-correlation matrix (zero if N=0 or N=1)
1548 :
1549 : -- ALGLIB --
1550 : Copyright 28.10.2010 by Bochkanov Sergey
1551 : *************************************************************************/
1552 0 : void spearmancorrm2(const real_2d_array &x, const real_2d_array &y, const ae_int_t n, const ae_int_t m1, const ae_int_t m2, real_2d_array &c, const xparams _xparams)
1553 : {
1554 : jmp_buf _break_jump;
1555 : alglib_impl::ae_state _alglib_env_state;
1556 0 : alglib_impl::ae_state_init(&_alglib_env_state);
1557 0 : if( setjmp(_break_jump) )
1558 : {
1559 : #if !defined(AE_NO_EXCEPTIONS)
1560 0 : _ALGLIB_CPP_EXCEPTION(_alglib_env_state.error_msg);
1561 : #else
1562 : _ALGLIB_SET_ERROR_FLAG(_alglib_env_state.error_msg);
1563 : return;
1564 : #endif
1565 : }
1566 0 : ae_state_set_break_jump(&_alglib_env_state, &_break_jump);
1567 0 : if( _xparams.flags!=0x0 )
1568 0 : ae_state_set_flags(&_alglib_env_state, _xparams.flags);
1569 0 : alglib_impl::spearmancorrm2(const_cast<alglib_impl::ae_matrix*>(x.c_ptr()), const_cast<alglib_impl::ae_matrix*>(y.c_ptr()), n, m1, m2, const_cast<alglib_impl::ae_matrix*>(c.c_ptr()), &_alglib_env_state);
1570 0 : alglib_impl::ae_state_clear(&_alglib_env_state);
1571 0 : return;
1572 : }
1573 :
1574 : /*************************************************************************
1575 : Spearman's rank cross-correlation matrix
1576 :
1577 : ! COMMERCIAL EDITION OF ALGLIB:
1578 : !
1579 : ! Commercial Edition of ALGLIB includes following important improvements
1580 : ! of this function:
1581 : ! * high-performance native backend with same C# interface (C# version)
1582 : ! * multithreading support (C++ and C# versions)
1583 : ! * hardware vendor (Intel) implementations of linear algebra primitives
1584 : ! (C++ and C# versions, x86/x64 platform)
1585 : !
1586 : ! We recommend you to read 'Working with commercial version' section of
1587 : ! ALGLIB Reference Manual in order to find out how to use performance-
1588 : ! related features provided by commercial edition of ALGLIB.
1589 :
1590 : INPUT PARAMETERS:
1591 : X - array[N,M1], sample matrix:
1592 : * J-th column corresponds to J-th variable
1593 : * I-th row corresponds to I-th observation
1594 : Y - array[N,M2], sample matrix:
1595 : * J-th column corresponds to J-th variable
1596 : * I-th row corresponds to I-th observation
1597 : N - N>=0, number of observations:
1598 : * if given, only leading N rows of X/Y are used
1599 : * if not given, automatically determined from input sizes
1600 : M1 - M1>0, number of variables in X:
1601 : * if given, only leading M1 columns of X are used
1602 : * if not given, automatically determined from input size
1603 : M2 - M2>0, number of variables in Y:
1604 : * if given, only leading M1 columns of X are used
1605 : * if not given, automatically determined from input size
1606 :
1607 : OUTPUT PARAMETERS:
1608 : C - array[M1,M2], cross-correlation matrix (zero if N=0 or N=1)
1609 :
1610 : -- ALGLIB --
1611 : Copyright 28.10.2010 by Bochkanov Sergey
1612 : *************************************************************************/
1613 : #if !defined(AE_NO_EXCEPTIONS)
1614 0 : void spearmancorrm2(const real_2d_array &x, const real_2d_array &y, real_2d_array &c, const xparams _xparams)
1615 : {
1616 : jmp_buf _break_jump;
1617 : alglib_impl::ae_state _alglib_env_state;
1618 : ae_int_t n;
1619 : ae_int_t m1;
1620 : ae_int_t m2;
1621 0 : if( (x.rows()!=y.rows()))
1622 0 : _ALGLIB_CPP_EXCEPTION("Error while calling 'spearmancorrm2': looks like one of arguments has wrong size");
1623 0 : n = x.rows();
1624 0 : m1 = x.cols();
1625 0 : m2 = y.cols();
1626 0 : alglib_impl::ae_state_init(&_alglib_env_state);
1627 0 : if( setjmp(_break_jump) )
1628 0 : _ALGLIB_CPP_EXCEPTION(_alglib_env_state.error_msg);
1629 0 : ae_state_set_break_jump(&_alglib_env_state, &_break_jump);
1630 0 : if( _xparams.flags!=0x0 )
1631 0 : ae_state_set_flags(&_alglib_env_state, _xparams.flags);
1632 0 : alglib_impl::spearmancorrm2(const_cast<alglib_impl::ae_matrix*>(x.c_ptr()), const_cast<alglib_impl::ae_matrix*>(y.c_ptr()), n, m1, m2, const_cast<alglib_impl::ae_matrix*>(c.c_ptr()), &_alglib_env_state);
1633 :
1634 0 : alglib_impl::ae_state_clear(&_alglib_env_state);
1635 0 : return;
1636 : }
1637 : #endif
1638 :
1639 : /*************************************************************************
1640 : This function replaces data in XY by their ranks:
1641 : * XY is processed row-by-row
1642 : * rows are processed separately
1643 : * tied data are correctly handled (tied ranks are calculated)
1644 : * ranking starts from 0, ends at NFeatures-1
1645 : * sum of within-row values is equal to (NFeatures-1)*NFeatures/2
1646 :
1647 : ! COMMERCIAL EDITION OF ALGLIB:
1648 : !
1649 : ! Commercial Edition of ALGLIB includes following important improvements
1650 : ! of this function:
1651 : ! * high-performance native backend with same C# interface (C# version)
1652 : ! * multithreading support (C++ and C# versions)
1653 : !
1654 : ! We recommend you to read 'Working with commercial version' section of
1655 : ! ALGLIB Reference Manual in order to find out how to use performance-
1656 : ! related features provided by commercial edition of ALGLIB.
1657 :
1658 : INPUT PARAMETERS:
1659 : XY - array[NPoints,NFeatures], dataset
1660 : NPoints - number of points
1661 : NFeatures- number of features
1662 :
1663 : OUTPUT PARAMETERS:
1664 : XY - data are replaced by their within-row ranks;
1665 : ranking starts from 0, ends at NFeatures-1
1666 :
1667 : -- ALGLIB --
1668 : Copyright 18.04.2013 by Bochkanov Sergey
1669 : *************************************************************************/
1670 0 : void rankdata(const real_2d_array &xy, const ae_int_t npoints, const ae_int_t nfeatures, const xparams _xparams)
1671 : {
1672 : jmp_buf _break_jump;
1673 : alglib_impl::ae_state _alglib_env_state;
1674 0 : alglib_impl::ae_state_init(&_alglib_env_state);
1675 0 : if( setjmp(_break_jump) )
1676 : {
1677 : #if !defined(AE_NO_EXCEPTIONS)
1678 0 : _ALGLIB_CPP_EXCEPTION(_alglib_env_state.error_msg);
1679 : #else
1680 : _ALGLIB_SET_ERROR_FLAG(_alglib_env_state.error_msg);
1681 : return;
1682 : #endif
1683 : }
1684 0 : ae_state_set_break_jump(&_alglib_env_state, &_break_jump);
1685 0 : if( _xparams.flags!=0x0 )
1686 0 : ae_state_set_flags(&_alglib_env_state, _xparams.flags);
1687 0 : alglib_impl::rankdata(const_cast<alglib_impl::ae_matrix*>(xy.c_ptr()), npoints, nfeatures, &_alglib_env_state);
1688 0 : alglib_impl::ae_state_clear(&_alglib_env_state);
1689 0 : return;
1690 : }
1691 :
1692 : /*************************************************************************
1693 : This function replaces data in XY by their ranks:
1694 : * XY is processed row-by-row
1695 : * rows are processed separately
1696 : * tied data are correctly handled (tied ranks are calculated)
1697 : * ranking starts from 0, ends at NFeatures-1
1698 : * sum of within-row values is equal to (NFeatures-1)*NFeatures/2
1699 :
1700 : ! COMMERCIAL EDITION OF ALGLIB:
1701 : !
1702 : ! Commercial Edition of ALGLIB includes following important improvements
1703 : ! of this function:
1704 : ! * high-performance native backend with same C# interface (C# version)
1705 : ! * multithreading support (C++ and C# versions)
1706 : !
1707 : ! We recommend you to read 'Working with commercial version' section of
1708 : ! ALGLIB Reference Manual in order to find out how to use performance-
1709 : ! related features provided by commercial edition of ALGLIB.
1710 :
1711 : INPUT PARAMETERS:
1712 : XY - array[NPoints,NFeatures], dataset
1713 : NPoints - number of points
1714 : NFeatures- number of features
1715 :
1716 : OUTPUT PARAMETERS:
1717 : XY - data are replaced by their within-row ranks;
1718 : ranking starts from 0, ends at NFeatures-1
1719 :
1720 : -- ALGLIB --
1721 : Copyright 18.04.2013 by Bochkanov Sergey
1722 : *************************************************************************/
1723 : #if !defined(AE_NO_EXCEPTIONS)
1724 0 : void rankdata(real_2d_array &xy, const xparams _xparams)
1725 : {
1726 : jmp_buf _break_jump;
1727 : alglib_impl::ae_state _alglib_env_state;
1728 : ae_int_t npoints;
1729 : ae_int_t nfeatures;
1730 :
1731 0 : npoints = xy.rows();
1732 0 : nfeatures = xy.cols();
1733 0 : alglib_impl::ae_state_init(&_alglib_env_state);
1734 0 : if( setjmp(_break_jump) )
1735 0 : _ALGLIB_CPP_EXCEPTION(_alglib_env_state.error_msg);
1736 0 : ae_state_set_break_jump(&_alglib_env_state, &_break_jump);
1737 0 : if( _xparams.flags!=0x0 )
1738 0 : ae_state_set_flags(&_alglib_env_state, _xparams.flags);
1739 0 : alglib_impl::rankdata(const_cast<alglib_impl::ae_matrix*>(xy.c_ptr()), npoints, nfeatures, &_alglib_env_state);
1740 :
1741 0 : alglib_impl::ae_state_clear(&_alglib_env_state);
1742 0 : return;
1743 : }
1744 : #endif
1745 :
1746 : /*************************************************************************
1747 : This function replaces data in XY by their CENTERED ranks:
1748 : * XY is processed row-by-row
1749 : * rows are processed separately
1750 : * tied data are correctly handled (tied ranks are calculated)
1751 : * centered ranks are just usual ranks, but centered in such way that sum
1752 : of within-row values is equal to 0.0.
1753 : * centering is performed by subtracting mean from each row, i.e it changes
1754 : mean value, but does NOT change higher moments
1755 :
1756 : ! COMMERCIAL EDITION OF ALGLIB:
1757 : !
1758 : ! Commercial Edition of ALGLIB includes following important improvements
1759 : ! of this function:
1760 : ! * high-performance native backend with same C# interface (C# version)
1761 : ! * multithreading support (C++ and C# versions)
1762 : !
1763 : ! We recommend you to read 'Working with commercial version' section of
1764 : ! ALGLIB Reference Manual in order to find out how to use performance-
1765 : ! related features provided by commercial edition of ALGLIB.
1766 :
1767 : INPUT PARAMETERS:
1768 : XY - array[NPoints,NFeatures], dataset
1769 : NPoints - number of points
1770 : NFeatures- number of features
1771 :
1772 : OUTPUT PARAMETERS:
1773 : XY - data are replaced by their within-row ranks;
1774 : ranking starts from 0, ends at NFeatures-1
1775 :
1776 : -- ALGLIB --
1777 : Copyright 18.04.2013 by Bochkanov Sergey
1778 : *************************************************************************/
1779 0 : void rankdatacentered(const real_2d_array &xy, const ae_int_t npoints, const ae_int_t nfeatures, const xparams _xparams)
1780 : {
1781 : jmp_buf _break_jump;
1782 : alglib_impl::ae_state _alglib_env_state;
1783 0 : alglib_impl::ae_state_init(&_alglib_env_state);
1784 0 : if( setjmp(_break_jump) )
1785 : {
1786 : #if !defined(AE_NO_EXCEPTIONS)
1787 0 : _ALGLIB_CPP_EXCEPTION(_alglib_env_state.error_msg);
1788 : #else
1789 : _ALGLIB_SET_ERROR_FLAG(_alglib_env_state.error_msg);
1790 : return;
1791 : #endif
1792 : }
1793 0 : ae_state_set_break_jump(&_alglib_env_state, &_break_jump);
1794 0 : if( _xparams.flags!=0x0 )
1795 0 : ae_state_set_flags(&_alglib_env_state, _xparams.flags);
1796 0 : alglib_impl::rankdatacentered(const_cast<alglib_impl::ae_matrix*>(xy.c_ptr()), npoints, nfeatures, &_alglib_env_state);
1797 0 : alglib_impl::ae_state_clear(&_alglib_env_state);
1798 0 : return;
1799 : }
1800 :
1801 : /*************************************************************************
1802 : This function replaces data in XY by their CENTERED ranks:
1803 : * XY is processed row-by-row
1804 : * rows are processed separately
1805 : * tied data are correctly handled (tied ranks are calculated)
1806 : * centered ranks are just usual ranks, but centered in such way that sum
1807 : of within-row values is equal to 0.0.
1808 : * centering is performed by subtracting mean from each row, i.e it changes
1809 : mean value, but does NOT change higher moments
1810 :
1811 : ! COMMERCIAL EDITION OF ALGLIB:
1812 : !
1813 : ! Commercial Edition of ALGLIB includes following important improvements
1814 : ! of this function:
1815 : ! * high-performance native backend with same C# interface (C# version)
1816 : ! * multithreading support (C++ and C# versions)
1817 : !
1818 : ! We recommend you to read 'Working with commercial version' section of
1819 : ! ALGLIB Reference Manual in order to find out how to use performance-
1820 : ! related features provided by commercial edition of ALGLIB.
1821 :
1822 : INPUT PARAMETERS:
1823 : XY - array[NPoints,NFeatures], dataset
1824 : NPoints - number of points
1825 : NFeatures- number of features
1826 :
1827 : OUTPUT PARAMETERS:
1828 : XY - data are replaced by their within-row ranks;
1829 : ranking starts from 0, ends at NFeatures-1
1830 :
1831 : -- ALGLIB --
1832 : Copyright 18.04.2013 by Bochkanov Sergey
1833 : *************************************************************************/
1834 : #if !defined(AE_NO_EXCEPTIONS)
1835 0 : void rankdatacentered(real_2d_array &xy, const xparams _xparams)
1836 : {
1837 : jmp_buf _break_jump;
1838 : alglib_impl::ae_state _alglib_env_state;
1839 : ae_int_t npoints;
1840 : ae_int_t nfeatures;
1841 :
1842 0 : npoints = xy.rows();
1843 0 : nfeatures = xy.cols();
1844 0 : alglib_impl::ae_state_init(&_alglib_env_state);
1845 0 : if( setjmp(_break_jump) )
1846 0 : _ALGLIB_CPP_EXCEPTION(_alglib_env_state.error_msg);
1847 0 : ae_state_set_break_jump(&_alglib_env_state, &_break_jump);
1848 0 : if( _xparams.flags!=0x0 )
1849 0 : ae_state_set_flags(&_alglib_env_state, _xparams.flags);
1850 0 : alglib_impl::rankdatacentered(const_cast<alglib_impl::ae_matrix*>(xy.c_ptr()), npoints, nfeatures, &_alglib_env_state);
1851 :
1852 0 : alglib_impl::ae_state_clear(&_alglib_env_state);
1853 0 : return;
1854 : }
1855 : #endif
1856 :
1857 : /*************************************************************************
1858 : Obsolete function, we recommend to use PearsonCorr2().
1859 :
1860 : -- ALGLIB --
1861 : Copyright 09.04.2007 by Bochkanov Sergey
1862 : *************************************************************************/
1863 0 : double pearsoncorrelation(const real_1d_array &x, const real_1d_array &y, const ae_int_t n, const xparams _xparams)
1864 : {
1865 : jmp_buf _break_jump;
1866 : alglib_impl::ae_state _alglib_env_state;
1867 0 : alglib_impl::ae_state_init(&_alglib_env_state);
1868 0 : if( setjmp(_break_jump) )
1869 : {
1870 : #if !defined(AE_NO_EXCEPTIONS)
1871 0 : _ALGLIB_CPP_EXCEPTION(_alglib_env_state.error_msg);
1872 : #else
1873 : _ALGLIB_SET_ERROR_FLAG(_alglib_env_state.error_msg);
1874 : return 0;
1875 : #endif
1876 : }
1877 0 : ae_state_set_break_jump(&_alglib_env_state, &_break_jump);
1878 0 : if( _xparams.flags!=0x0 )
1879 0 : ae_state_set_flags(&_alglib_env_state, _xparams.flags);
1880 0 : double result = alglib_impl::pearsoncorrelation(const_cast<alglib_impl::ae_vector*>(x.c_ptr()), const_cast<alglib_impl::ae_vector*>(y.c_ptr()), n, &_alglib_env_state);
1881 0 : alglib_impl::ae_state_clear(&_alglib_env_state);
1882 0 : return *(reinterpret_cast<double*>(&result));
1883 : }
1884 :
1885 : /*************************************************************************
1886 : Obsolete function, we recommend to use SpearmanCorr2().
1887 :
1888 : -- ALGLIB --
1889 : Copyright 09.04.2007 by Bochkanov Sergey
1890 : *************************************************************************/
1891 0 : double spearmanrankcorrelation(const real_1d_array &x, const real_1d_array &y, const ae_int_t n, const xparams _xparams)
1892 : {
1893 : jmp_buf _break_jump;
1894 : alglib_impl::ae_state _alglib_env_state;
1895 0 : alglib_impl::ae_state_init(&_alglib_env_state);
1896 0 : if( setjmp(_break_jump) )
1897 : {
1898 : #if !defined(AE_NO_EXCEPTIONS)
1899 0 : _ALGLIB_CPP_EXCEPTION(_alglib_env_state.error_msg);
1900 : #else
1901 : _ALGLIB_SET_ERROR_FLAG(_alglib_env_state.error_msg);
1902 : return 0;
1903 : #endif
1904 : }
1905 0 : ae_state_set_break_jump(&_alglib_env_state, &_break_jump);
1906 0 : if( _xparams.flags!=0x0 )
1907 0 : ae_state_set_flags(&_alglib_env_state, _xparams.flags);
1908 0 : double result = alglib_impl::spearmanrankcorrelation(const_cast<alglib_impl::ae_vector*>(x.c_ptr()), const_cast<alglib_impl::ae_vector*>(y.c_ptr()), n, &_alglib_env_state);
1909 0 : alglib_impl::ae_state_clear(&_alglib_env_state);
1910 0 : return *(reinterpret_cast<double*>(&result));
1911 : }
1912 : #endif
1913 :
1914 : #if defined(AE_COMPILE_WSR) || !defined(AE_PARTIAL_BUILD)
1915 : /*************************************************************************
1916 : Wilcoxon signed-rank test
1917 :
1918 : This test checks three hypotheses about the median of the given sample.
1919 : The following tests are performed:
1920 : * two-tailed test (null hypothesis - the median is equal to the given
1921 : value)
1922 : * left-tailed test (null hypothesis - the median is greater than or
1923 : equal to the given value)
1924 : * right-tailed test (null hypothesis - the median is less than or
1925 : equal to the given value)
1926 :
1927 : Requirements:
1928 : * the scale of measurement should be ordinal, interval or ratio (i.e.
1929 : the test could not be applied to nominal variables).
1930 : * the distribution should be continuous and symmetric relative to its
1931 : median.
1932 : * number of distinct values in the X array should be greater than 4
1933 :
1934 : The test is non-parametric and doesn't require distribution X to be normal
1935 :
1936 : Input parameters:
1937 : X - sample. Array whose index goes from 0 to N-1.
1938 : N - size of the sample.
1939 : Median - assumed median value.
1940 :
1941 : Output parameters:
1942 : BothTails - p-value for two-tailed test.
1943 : If BothTails is less than the given significance level
1944 : the null hypothesis is rejected.
1945 : LeftTail - p-value for left-tailed test.
1946 : If LeftTail is less than the given significance level,
1947 : the null hypothesis is rejected.
1948 : RightTail - p-value for right-tailed test.
1949 : If RightTail is less than the given significance level
1950 : the null hypothesis is rejected.
1951 :
1952 : To calculate p-values, special approximation is used. This method lets us
1953 : calculate p-values with two decimal places in interval [0.0001, 1].
1954 :
1955 : "Two decimal places" does not sound very impressive, but in practice the
1956 : relative error of less than 1% is enough to make a decision.
1957 :
1958 : There is no approximation outside the [0.0001, 1] interval. Therefore, if
1959 : the significance level outlies this interval, the test returns 0.0001.
1960 :
1961 : -- ALGLIB --
1962 : Copyright 08.09.2006 by Bochkanov Sergey
1963 : *************************************************************************/
1964 0 : void wilcoxonsignedranktest(const real_1d_array &x, const ae_int_t n, const double e, double &bothtails, double &lefttail, double &righttail, const xparams _xparams)
1965 : {
1966 : jmp_buf _break_jump;
1967 : alglib_impl::ae_state _alglib_env_state;
1968 0 : alglib_impl::ae_state_init(&_alglib_env_state);
1969 0 : if( setjmp(_break_jump) )
1970 : {
1971 : #if !defined(AE_NO_EXCEPTIONS)
1972 0 : _ALGLIB_CPP_EXCEPTION(_alglib_env_state.error_msg);
1973 : #else
1974 : _ALGLIB_SET_ERROR_FLAG(_alglib_env_state.error_msg);
1975 : return;
1976 : #endif
1977 : }
1978 0 : ae_state_set_break_jump(&_alglib_env_state, &_break_jump);
1979 0 : if( _xparams.flags!=0x0 )
1980 0 : ae_state_set_flags(&_alglib_env_state, _xparams.flags);
1981 0 : alglib_impl::wilcoxonsignedranktest(const_cast<alglib_impl::ae_vector*>(x.c_ptr()), n, e, &bothtails, &lefttail, &righttail, &_alglib_env_state);
1982 0 : alglib_impl::ae_state_clear(&_alglib_env_state);
1983 0 : return;
1984 : }
1985 : #endif
1986 :
1987 : #if defined(AE_COMPILE_STEST) || !defined(AE_PARTIAL_BUILD)
1988 : /*************************************************************************
1989 : Sign test
1990 :
1991 : This test checks three hypotheses about the median of the given sample.
1992 : The following tests are performed:
1993 : * two-tailed test (null hypothesis - the median is equal to the given
1994 : value)
1995 : * left-tailed test (null hypothesis - the median is greater than or
1996 : equal to the given value)
1997 : * right-tailed test (null hypothesis - the median is less than or
1998 : equal to the given value)
1999 :
2000 : Requirements:
2001 : * the scale of measurement should be ordinal, interval or ratio (i.e.
2002 : the test could not be applied to nominal variables).
2003 :
2004 : The test is non-parametric and doesn't require distribution X to be normal
2005 :
2006 : Input parameters:
2007 : X - sample. Array whose index goes from 0 to N-1.
2008 : N - size of the sample.
2009 : Median - assumed median value.
2010 :
2011 : Output parameters:
2012 : BothTails - p-value for two-tailed test.
2013 : If BothTails is less than the given significance level
2014 : the null hypothesis is rejected.
2015 : LeftTail - p-value for left-tailed test.
2016 : If LeftTail is less than the given significance level,
2017 : the null hypothesis is rejected.
2018 : RightTail - p-value for right-tailed test.
2019 : If RightTail is less than the given significance level
2020 : the null hypothesis is rejected.
2021 :
2022 : While calculating p-values high-precision binomial distribution
2023 : approximation is used, so significance levels have about 15 exact digits.
2024 :
2025 : -- ALGLIB --
2026 : Copyright 08.09.2006 by Bochkanov Sergey
2027 : *************************************************************************/
2028 0 : void onesamplesigntest(const real_1d_array &x, const ae_int_t n, const double median, double &bothtails, double &lefttail, double &righttail, const xparams _xparams)
2029 : {
2030 : jmp_buf _break_jump;
2031 : alglib_impl::ae_state _alglib_env_state;
2032 0 : alglib_impl::ae_state_init(&_alglib_env_state);
2033 0 : if( setjmp(_break_jump) )
2034 : {
2035 : #if !defined(AE_NO_EXCEPTIONS)
2036 0 : _ALGLIB_CPP_EXCEPTION(_alglib_env_state.error_msg);
2037 : #else
2038 : _ALGLIB_SET_ERROR_FLAG(_alglib_env_state.error_msg);
2039 : return;
2040 : #endif
2041 : }
2042 0 : ae_state_set_break_jump(&_alglib_env_state, &_break_jump);
2043 0 : if( _xparams.flags!=0x0 )
2044 0 : ae_state_set_flags(&_alglib_env_state, _xparams.flags);
2045 0 : alglib_impl::onesamplesigntest(const_cast<alglib_impl::ae_vector*>(x.c_ptr()), n, median, &bothtails, &lefttail, &righttail, &_alglib_env_state);
2046 0 : alglib_impl::ae_state_clear(&_alglib_env_state);
2047 0 : return;
2048 : }
2049 : #endif
2050 :
2051 : #if defined(AE_COMPILE_CORRELATIONTESTS) || !defined(AE_PARTIAL_BUILD)
2052 : /*************************************************************************
2053 : Pearson's correlation coefficient significance test
2054 :
2055 : This test checks hypotheses about whether X and Y are samples of two
2056 : continuous distributions having zero correlation or whether their
2057 : correlation is non-zero.
2058 :
2059 : The following tests are performed:
2060 : * two-tailed test (null hypothesis - X and Y have zero correlation)
2061 : * left-tailed test (null hypothesis - the correlation coefficient is
2062 : greater than or equal to 0)
2063 : * right-tailed test (null hypothesis - the correlation coefficient is
2064 : less than or equal to 0).
2065 :
2066 : Requirements:
2067 : * the number of elements in each sample is not less than 5
2068 : * normality of distributions of X and Y.
2069 :
2070 : Input parameters:
2071 : R - Pearson's correlation coefficient for X and Y
2072 : N - number of elements in samples, N>=5.
2073 :
2074 : Output parameters:
2075 : BothTails - p-value for two-tailed test.
2076 : If BothTails is less than the given significance level
2077 : the null hypothesis is rejected.
2078 : LeftTail - p-value for left-tailed test.
2079 : If LeftTail is less than the given significance level,
2080 : the null hypothesis is rejected.
2081 : RightTail - p-value for right-tailed test.
2082 : If RightTail is less than the given significance level
2083 : the null hypothesis is rejected.
2084 :
2085 : -- ALGLIB --
2086 : Copyright 09.04.2007 by Bochkanov Sergey
2087 : *************************************************************************/
2088 0 : void pearsoncorrelationsignificance(const double r, const ae_int_t n, double &bothtails, double &lefttail, double &righttail, const xparams _xparams)
2089 : {
2090 : jmp_buf _break_jump;
2091 : alglib_impl::ae_state _alglib_env_state;
2092 0 : alglib_impl::ae_state_init(&_alglib_env_state);
2093 0 : if( setjmp(_break_jump) )
2094 : {
2095 : #if !defined(AE_NO_EXCEPTIONS)
2096 0 : _ALGLIB_CPP_EXCEPTION(_alglib_env_state.error_msg);
2097 : #else
2098 : _ALGLIB_SET_ERROR_FLAG(_alglib_env_state.error_msg);
2099 : return;
2100 : #endif
2101 : }
2102 0 : ae_state_set_break_jump(&_alglib_env_state, &_break_jump);
2103 0 : if( _xparams.flags!=0x0 )
2104 0 : ae_state_set_flags(&_alglib_env_state, _xparams.flags);
2105 0 : alglib_impl::pearsoncorrelationsignificance(r, n, &bothtails, &lefttail, &righttail, &_alglib_env_state);
2106 0 : alglib_impl::ae_state_clear(&_alglib_env_state);
2107 0 : return;
2108 : }
2109 :
2110 : /*************************************************************************
2111 : Spearman's rank correlation coefficient significance test
2112 :
2113 : This test checks hypotheses about whether X and Y are samples of two
2114 : continuous distributions having zero correlation or whether their
2115 : correlation is non-zero.
2116 :
2117 : The following tests are performed:
2118 : * two-tailed test (null hypothesis - X and Y have zero correlation)
2119 : * left-tailed test (null hypothesis - the correlation coefficient is
2120 : greater than or equal to 0)
2121 : * right-tailed test (null hypothesis - the correlation coefficient is
2122 : less than or equal to 0).
2123 :
2124 : Requirements:
2125 : * the number of elements in each sample is not less than 5.
2126 :
2127 : The test is non-parametric and doesn't require distributions X and Y to be
2128 : normal.
2129 :
2130 : Input parameters:
2131 : R - Spearman's rank correlation coefficient for X and Y
2132 : N - number of elements in samples, N>=5.
2133 :
2134 : Output parameters:
2135 : BothTails - p-value for two-tailed test.
2136 : If BothTails is less than the given significance level
2137 : the null hypothesis is rejected.
2138 : LeftTail - p-value for left-tailed test.
2139 : If LeftTail is less than the given significance level,
2140 : the null hypothesis is rejected.
2141 : RightTail - p-value for right-tailed test.
2142 : If RightTail is less than the given significance level
2143 : the null hypothesis is rejected.
2144 :
2145 : -- ALGLIB --
2146 : Copyright 09.04.2007 by Bochkanov Sergey
2147 : *************************************************************************/
2148 0 : void spearmanrankcorrelationsignificance(const double r, const ae_int_t n, double &bothtails, double &lefttail, double &righttail, const xparams _xparams)
2149 : {
2150 : jmp_buf _break_jump;
2151 : alglib_impl::ae_state _alglib_env_state;
2152 0 : alglib_impl::ae_state_init(&_alglib_env_state);
2153 0 : if( setjmp(_break_jump) )
2154 : {
2155 : #if !defined(AE_NO_EXCEPTIONS)
2156 0 : _ALGLIB_CPP_EXCEPTION(_alglib_env_state.error_msg);
2157 : #else
2158 : _ALGLIB_SET_ERROR_FLAG(_alglib_env_state.error_msg);
2159 : return;
2160 : #endif
2161 : }
2162 0 : ae_state_set_break_jump(&_alglib_env_state, &_break_jump);
2163 0 : if( _xparams.flags!=0x0 )
2164 0 : ae_state_set_flags(&_alglib_env_state, _xparams.flags);
2165 0 : alglib_impl::spearmanrankcorrelationsignificance(r, n, &bothtails, &lefttail, &righttail, &_alglib_env_state);
2166 0 : alglib_impl::ae_state_clear(&_alglib_env_state);
2167 0 : return;
2168 : }
2169 : #endif
2170 :
2171 : #if defined(AE_COMPILE_STUDENTTTESTS) || !defined(AE_PARTIAL_BUILD)
2172 : /*************************************************************************
2173 : One-sample t-test
2174 :
2175 : This test checks three hypotheses about the mean of the given sample. The
2176 : following tests are performed:
2177 : * two-tailed test (null hypothesis - the mean is equal to the given
2178 : value)
2179 : * left-tailed test (null hypothesis - the mean is greater than or
2180 : equal to the given value)
2181 : * right-tailed test (null hypothesis - the mean is less than or equal
2182 : to the given value).
2183 :
2184 : The test is based on the assumption that a given sample has a normal
2185 : distribution and an unknown dispersion. If the distribution sharply
2186 : differs from normal, the test will work incorrectly.
2187 :
2188 : INPUT PARAMETERS:
2189 : X - sample. Array whose index goes from 0 to N-1.
2190 : N - size of sample, N>=0
2191 : Mean - assumed value of the mean.
2192 :
2193 : OUTPUT PARAMETERS:
2194 : BothTails - p-value for two-tailed test.
2195 : If BothTails is less than the given significance level
2196 : the null hypothesis is rejected.
2197 : LeftTail - p-value for left-tailed test.
2198 : If LeftTail is less than the given significance level,
2199 : the null hypothesis is rejected.
2200 : RightTail - p-value for right-tailed test.
2201 : If RightTail is less than the given significance level
2202 : the null hypothesis is rejected.
2203 :
2204 : NOTE: this function correctly handles degenerate cases:
2205 : * when N=0, all p-values are set to 1.0
2206 : * when variance of X[] is exactly zero, p-values are set
2207 : to 1.0 or 0.0, depending on difference between sample mean and
2208 : value of mean being tested.
2209 :
2210 :
2211 : -- ALGLIB --
2212 : Copyright 08.09.2006 by Bochkanov Sergey
2213 : *************************************************************************/
2214 0 : void studentttest1(const real_1d_array &x, const ae_int_t n, const double mean, double &bothtails, double &lefttail, double &righttail, const xparams _xparams)
2215 : {
2216 : jmp_buf _break_jump;
2217 : alglib_impl::ae_state _alglib_env_state;
2218 0 : alglib_impl::ae_state_init(&_alglib_env_state);
2219 0 : if( setjmp(_break_jump) )
2220 : {
2221 : #if !defined(AE_NO_EXCEPTIONS)
2222 0 : _ALGLIB_CPP_EXCEPTION(_alglib_env_state.error_msg);
2223 : #else
2224 : _ALGLIB_SET_ERROR_FLAG(_alglib_env_state.error_msg);
2225 : return;
2226 : #endif
2227 : }
2228 0 : ae_state_set_break_jump(&_alglib_env_state, &_break_jump);
2229 0 : if( _xparams.flags!=0x0 )
2230 0 : ae_state_set_flags(&_alglib_env_state, _xparams.flags);
2231 0 : alglib_impl::studentttest1(const_cast<alglib_impl::ae_vector*>(x.c_ptr()), n, mean, &bothtails, &lefttail, &righttail, &_alglib_env_state);
2232 0 : alglib_impl::ae_state_clear(&_alglib_env_state);
2233 0 : return;
2234 : }
2235 :
2236 : /*************************************************************************
2237 : Two-sample pooled test
2238 :
2239 : This test checks three hypotheses about the mean of the given samples. The
2240 : following tests are performed:
2241 : * two-tailed test (null hypothesis - the means are equal)
2242 : * left-tailed test (null hypothesis - the mean of the first sample is
2243 : greater than or equal to the mean of the second sample)
2244 : * right-tailed test (null hypothesis - the mean of the first sample is
2245 : less than or equal to the mean of the second sample).
2246 :
2247 : Test is based on the following assumptions:
2248 : * given samples have normal distributions
2249 : * dispersions are equal
2250 : * samples are independent.
2251 :
2252 : Input parameters:
2253 : X - sample 1. Array whose index goes from 0 to N-1.
2254 : N - size of sample.
2255 : Y - sample 2. Array whose index goes from 0 to M-1.
2256 : M - size of sample.
2257 :
2258 : Output parameters:
2259 : BothTails - p-value for two-tailed test.
2260 : If BothTails is less than the given significance level
2261 : the null hypothesis is rejected.
2262 : LeftTail - p-value for left-tailed test.
2263 : If LeftTail is less than the given significance level,
2264 : the null hypothesis is rejected.
2265 : RightTail - p-value for right-tailed test.
2266 : If RightTail is less than the given significance level
2267 : the null hypothesis is rejected.
2268 :
2269 : NOTE: this function correctly handles degenerate cases:
2270 : * when N=0 or M=0, all p-values are set to 1.0
2271 : * when both samples has exactly zero variance, p-values are set
2272 : to 1.0 or 0.0, depending on difference between means.
2273 :
2274 : -- ALGLIB --
2275 : Copyright 18.09.2006 by Bochkanov Sergey
2276 : *************************************************************************/
2277 0 : void studentttest2(const real_1d_array &x, const ae_int_t n, const real_1d_array &y, const ae_int_t m, double &bothtails, double &lefttail, double &righttail, const xparams _xparams)
2278 : {
2279 : jmp_buf _break_jump;
2280 : alglib_impl::ae_state _alglib_env_state;
2281 0 : alglib_impl::ae_state_init(&_alglib_env_state);
2282 0 : if( setjmp(_break_jump) )
2283 : {
2284 : #if !defined(AE_NO_EXCEPTIONS)
2285 0 : _ALGLIB_CPP_EXCEPTION(_alglib_env_state.error_msg);
2286 : #else
2287 : _ALGLIB_SET_ERROR_FLAG(_alglib_env_state.error_msg);
2288 : return;
2289 : #endif
2290 : }
2291 0 : ae_state_set_break_jump(&_alglib_env_state, &_break_jump);
2292 0 : if( _xparams.flags!=0x0 )
2293 0 : ae_state_set_flags(&_alglib_env_state, _xparams.flags);
2294 0 : alglib_impl::studentttest2(const_cast<alglib_impl::ae_vector*>(x.c_ptr()), n, const_cast<alglib_impl::ae_vector*>(y.c_ptr()), m, &bothtails, &lefttail, &righttail, &_alglib_env_state);
2295 0 : alglib_impl::ae_state_clear(&_alglib_env_state);
2296 0 : return;
2297 : }
2298 :
2299 : /*************************************************************************
2300 : Two-sample unpooled test
2301 :
2302 : This test checks three hypotheses about the mean of the given samples. The
2303 : following tests are performed:
2304 : * two-tailed test (null hypothesis - the means are equal)
2305 : * left-tailed test (null hypothesis - the mean of the first sample is
2306 : greater than or equal to the mean of the second sample)
2307 : * right-tailed test (null hypothesis - the mean of the first sample is
2308 : less than or equal to the mean of the second sample).
2309 :
2310 : Test is based on the following assumptions:
2311 : * given samples have normal distributions
2312 : * samples are independent.
2313 : Equality of variances is NOT required.
2314 :
2315 : Input parameters:
2316 : X - sample 1. Array whose index goes from 0 to N-1.
2317 : N - size of the sample.
2318 : Y - sample 2. Array whose index goes from 0 to M-1.
2319 : M - size of the sample.
2320 :
2321 : Output parameters:
2322 : BothTails - p-value for two-tailed test.
2323 : If BothTails is less than the given significance level
2324 : the null hypothesis is rejected.
2325 : LeftTail - p-value for left-tailed test.
2326 : If LeftTail is less than the given significance level,
2327 : the null hypothesis is rejected.
2328 : RightTail - p-value for right-tailed test.
2329 : If RightTail is less than the given significance level
2330 : the null hypothesis is rejected.
2331 :
2332 : NOTE: this function correctly handles degenerate cases:
2333 : * when N=0 or M=0, all p-values are set to 1.0
2334 : * when both samples has zero variance, p-values are set
2335 : to 1.0 or 0.0, depending on difference between means.
2336 : * when only one sample has zero variance, test reduces to 1-sample
2337 : version.
2338 :
2339 : -- ALGLIB --
2340 : Copyright 18.09.2006 by Bochkanov Sergey
2341 : *************************************************************************/
2342 0 : void unequalvariancettest(const real_1d_array &x, const ae_int_t n, const real_1d_array &y, const ae_int_t m, double &bothtails, double &lefttail, double &righttail, const xparams _xparams)
2343 : {
2344 : jmp_buf _break_jump;
2345 : alglib_impl::ae_state _alglib_env_state;
2346 0 : alglib_impl::ae_state_init(&_alglib_env_state);
2347 0 : if( setjmp(_break_jump) )
2348 : {
2349 : #if !defined(AE_NO_EXCEPTIONS)
2350 0 : _ALGLIB_CPP_EXCEPTION(_alglib_env_state.error_msg);
2351 : #else
2352 : _ALGLIB_SET_ERROR_FLAG(_alglib_env_state.error_msg);
2353 : return;
2354 : #endif
2355 : }
2356 0 : ae_state_set_break_jump(&_alglib_env_state, &_break_jump);
2357 0 : if( _xparams.flags!=0x0 )
2358 0 : ae_state_set_flags(&_alglib_env_state, _xparams.flags);
2359 0 : alglib_impl::unequalvariancettest(const_cast<alglib_impl::ae_vector*>(x.c_ptr()), n, const_cast<alglib_impl::ae_vector*>(y.c_ptr()), m, &bothtails, &lefttail, &righttail, &_alglib_env_state);
2360 0 : alglib_impl::ae_state_clear(&_alglib_env_state);
2361 0 : return;
2362 : }
2363 : #endif
2364 :
2365 : #if defined(AE_COMPILE_MANNWHITNEYU) || !defined(AE_PARTIAL_BUILD)
2366 : /*************************************************************************
2367 : Mann-Whitney U-test
2368 :
2369 : This test checks hypotheses about whether X and Y are samples of two
2370 : continuous distributions of the same shape and same median or whether
2371 : their medians are different.
2372 :
2373 : The following tests are performed:
2374 : * two-tailed test (null hypothesis - the medians are equal)
2375 : * left-tailed test (null hypothesis - the median of the first sample
2376 : is greater than or equal to the median of the second sample)
2377 : * right-tailed test (null hypothesis - the median of the first sample
2378 : is less than or equal to the median of the second sample).
2379 :
2380 : Requirements:
2381 : * the samples are independent
2382 : * X and Y are continuous distributions (or discrete distributions well-
2383 : approximating continuous distributions)
2384 : * distributions of X and Y have the same shape. The only possible
2385 : difference is their position (i.e. the value of the median)
2386 : * the number of elements in each sample is not less than 5
2387 : * the scale of measurement should be ordinal, interval or ratio (i.e.
2388 : the test could not be applied to nominal variables).
2389 :
2390 : The test is non-parametric and doesn't require distributions to be normal.
2391 :
2392 : Input parameters:
2393 : X - sample 1. Array whose index goes from 0 to N-1.
2394 : N - size of the sample. N>=5
2395 : Y - sample 2. Array whose index goes from 0 to M-1.
2396 : M - size of the sample. M>=5
2397 :
2398 : Output parameters:
2399 : BothTails - p-value for two-tailed test.
2400 : If BothTails is less than the given significance level
2401 : the null hypothesis is rejected.
2402 : LeftTail - p-value for left-tailed test.
2403 : If LeftTail is less than the given significance level,
2404 : the null hypothesis is rejected.
2405 : RightTail - p-value for right-tailed test.
2406 : If RightTail is less than the given significance level
2407 : the null hypothesis is rejected.
2408 :
2409 : To calculate p-values, special approximation is used. This method lets us
2410 : calculate p-values with satisfactory accuracy in interval [0.0001, 1].
2411 : There is no approximation outside the [0.0001, 1] interval. Therefore, if
2412 : the significance level outlies this interval, the test returns 0.0001.
2413 :
2414 : Relative precision of approximation of p-value:
2415 :
2416 : N M Max.err. Rms.err.
2417 : 5..10 N..10 1.4e-02 6.0e-04
2418 : 5..10 N..100 2.2e-02 5.3e-06
2419 : 10..15 N..15 1.0e-02 3.2e-04
2420 : 10..15 N..100 1.0e-02 2.2e-05
2421 : 15..100 N..100 6.1e-03 2.7e-06
2422 :
2423 : For N,M>100 accuracy checks weren't put into practice, but taking into
2424 : account characteristics of asymptotic approximation used, precision should
2425 : not be sharply different from the values for interval [5, 100].
2426 :
2427 : NOTE: P-value approximation was optimized for 0.0001<=p<=0.2500. Thus,
2428 : P's outside of this interval are enforced to these bounds. Say, you
2429 : may quite often get P equal to exactly 0.25 or 0.0001.
2430 :
2431 : -- ALGLIB --
2432 : Copyright 09.04.2007 by Bochkanov Sergey
2433 : *************************************************************************/
2434 0 : void mannwhitneyutest(const real_1d_array &x, const ae_int_t n, const real_1d_array &y, const ae_int_t m, double &bothtails, double &lefttail, double &righttail, const xparams _xparams)
2435 : {
2436 : jmp_buf _break_jump;
2437 : alglib_impl::ae_state _alglib_env_state;
2438 0 : alglib_impl::ae_state_init(&_alglib_env_state);
2439 0 : if( setjmp(_break_jump) )
2440 : {
2441 : #if !defined(AE_NO_EXCEPTIONS)
2442 0 : _ALGLIB_CPP_EXCEPTION(_alglib_env_state.error_msg);
2443 : #else
2444 : _ALGLIB_SET_ERROR_FLAG(_alglib_env_state.error_msg);
2445 : return;
2446 : #endif
2447 : }
2448 0 : ae_state_set_break_jump(&_alglib_env_state, &_break_jump);
2449 0 : if( _xparams.flags!=0x0 )
2450 0 : ae_state_set_flags(&_alglib_env_state, _xparams.flags);
2451 0 : alglib_impl::mannwhitneyutest(const_cast<alglib_impl::ae_vector*>(x.c_ptr()), n, const_cast<alglib_impl::ae_vector*>(y.c_ptr()), m, &bothtails, &lefttail, &righttail, &_alglib_env_state);
2452 0 : alglib_impl::ae_state_clear(&_alglib_env_state);
2453 0 : return;
2454 : }
2455 : #endif
2456 :
2457 : #if defined(AE_COMPILE_JARQUEBERA) || !defined(AE_PARTIAL_BUILD)
2458 : /*************************************************************************
2459 : Jarque-Bera test
2460 :
2461 : This test checks hypotheses about the fact that a given sample X is a
2462 : sample of normal random variable.
2463 :
2464 : Requirements:
2465 : * the number of elements in the sample is not less than 5.
2466 :
2467 : Input parameters:
2468 : X - sample. Array whose index goes from 0 to N-1.
2469 : N - size of the sample. N>=5
2470 :
2471 : Output parameters:
2472 : P - p-value for the test
2473 :
2474 : Accuracy of the approximation used (5<=N<=1951):
2475 :
2476 : p-value relative error (5<=N<=1951)
2477 : [1, 0.1] < 1%
2478 : [0.1, 0.01] < 2%
2479 : [0.01, 0.001] < 6%
2480 : [0.001, 0] wasn't measured
2481 :
2482 : For N>1951 accuracy wasn't measured but it shouldn't be sharply different
2483 : from table values.
2484 :
2485 : -- ALGLIB --
2486 : Copyright 09.04.2007 by Bochkanov Sergey
2487 : *************************************************************************/
2488 0 : void jarqueberatest(const real_1d_array &x, const ae_int_t n, double &p, const xparams _xparams)
2489 : {
2490 : jmp_buf _break_jump;
2491 : alglib_impl::ae_state _alglib_env_state;
2492 0 : alglib_impl::ae_state_init(&_alglib_env_state);
2493 0 : if( setjmp(_break_jump) )
2494 : {
2495 : #if !defined(AE_NO_EXCEPTIONS)
2496 0 : _ALGLIB_CPP_EXCEPTION(_alglib_env_state.error_msg);
2497 : #else
2498 : _ALGLIB_SET_ERROR_FLAG(_alglib_env_state.error_msg);
2499 : return;
2500 : #endif
2501 : }
2502 0 : ae_state_set_break_jump(&_alglib_env_state, &_break_jump);
2503 0 : if( _xparams.flags!=0x0 )
2504 0 : ae_state_set_flags(&_alglib_env_state, _xparams.flags);
2505 0 : alglib_impl::jarqueberatest(const_cast<alglib_impl::ae_vector*>(x.c_ptr()), n, &p, &_alglib_env_state);
2506 0 : alglib_impl::ae_state_clear(&_alglib_env_state);
2507 0 : return;
2508 : }
2509 : #endif
2510 :
2511 : #if defined(AE_COMPILE_VARIANCETESTS) || !defined(AE_PARTIAL_BUILD)
2512 : /*************************************************************************
2513 : Two-sample F-test
2514 :
2515 : This test checks three hypotheses about dispersions of the given samples.
2516 : The following tests are performed:
2517 : * two-tailed test (null hypothesis - the dispersions are equal)
2518 : * left-tailed test (null hypothesis - the dispersion of the first
2519 : sample is greater than or equal to the dispersion of the second
2520 : sample).
2521 : * right-tailed test (null hypothesis - the dispersion of the first
2522 : sample is less than or equal to the dispersion of the second sample)
2523 :
2524 : The test is based on the following assumptions:
2525 : * the given samples have normal distributions
2526 : * the samples are independent.
2527 :
2528 : Input parameters:
2529 : X - sample 1. Array whose index goes from 0 to N-1.
2530 : N - sample size.
2531 : Y - sample 2. Array whose index goes from 0 to M-1.
2532 : M - sample size.
2533 :
2534 : Output parameters:
2535 : BothTails - p-value for two-tailed test.
2536 : If BothTails is less than the given significance level
2537 : the null hypothesis is rejected.
2538 : LeftTail - p-value for left-tailed test.
2539 : If LeftTail is less than the given significance level,
2540 : the null hypothesis is rejected.
2541 : RightTail - p-value for right-tailed test.
2542 : If RightTail is less than the given significance level
2543 : the null hypothesis is rejected.
2544 :
2545 : -- ALGLIB --
2546 : Copyright 19.09.2006 by Bochkanov Sergey
2547 : *************************************************************************/
2548 0 : void ftest(const real_1d_array &x, const ae_int_t n, const real_1d_array &y, const ae_int_t m, double &bothtails, double &lefttail, double &righttail, const xparams _xparams)
2549 : {
2550 : jmp_buf _break_jump;
2551 : alglib_impl::ae_state _alglib_env_state;
2552 0 : alglib_impl::ae_state_init(&_alglib_env_state);
2553 0 : if( setjmp(_break_jump) )
2554 : {
2555 : #if !defined(AE_NO_EXCEPTIONS)
2556 0 : _ALGLIB_CPP_EXCEPTION(_alglib_env_state.error_msg);
2557 : #else
2558 : _ALGLIB_SET_ERROR_FLAG(_alglib_env_state.error_msg);
2559 : return;
2560 : #endif
2561 : }
2562 0 : ae_state_set_break_jump(&_alglib_env_state, &_break_jump);
2563 0 : if( _xparams.flags!=0x0 )
2564 0 : ae_state_set_flags(&_alglib_env_state, _xparams.flags);
2565 0 : alglib_impl::ftest(const_cast<alglib_impl::ae_vector*>(x.c_ptr()), n, const_cast<alglib_impl::ae_vector*>(y.c_ptr()), m, &bothtails, &lefttail, &righttail, &_alglib_env_state);
2566 0 : alglib_impl::ae_state_clear(&_alglib_env_state);
2567 0 : return;
2568 : }
2569 :
2570 : /*************************************************************************
2571 : One-sample chi-square test
2572 :
2573 : This test checks three hypotheses about the dispersion of the given sample
2574 : The following tests are performed:
2575 : * two-tailed test (null hypothesis - the dispersion equals the given
2576 : number)
2577 : * left-tailed test (null hypothesis - the dispersion is greater than
2578 : or equal to the given number)
2579 : * right-tailed test (null hypothesis - dispersion is less than or
2580 : equal to the given number).
2581 :
2582 : Test is based on the following assumptions:
2583 : * the given sample has a normal distribution.
2584 :
2585 : Input parameters:
2586 : X - sample 1. Array whose index goes from 0 to N-1.
2587 : N - size of the sample.
2588 : Variance - dispersion value to compare with.
2589 :
2590 : Output parameters:
2591 : BothTails - p-value for two-tailed test.
2592 : If BothTails is less than the given significance level
2593 : the null hypothesis is rejected.
2594 : LeftTail - p-value for left-tailed test.
2595 : If LeftTail is less than the given significance level,
2596 : the null hypothesis is rejected.
2597 : RightTail - p-value for right-tailed test.
2598 : If RightTail is less than the given significance level
2599 : the null hypothesis is rejected.
2600 :
2601 : -- ALGLIB --
2602 : Copyright 19.09.2006 by Bochkanov Sergey
2603 : *************************************************************************/
2604 0 : void onesamplevariancetest(const real_1d_array &x, const ae_int_t n, const double variance, double &bothtails, double &lefttail, double &righttail, const xparams _xparams)
2605 : {
2606 : jmp_buf _break_jump;
2607 : alglib_impl::ae_state _alglib_env_state;
2608 0 : alglib_impl::ae_state_init(&_alglib_env_state);
2609 0 : if( setjmp(_break_jump) )
2610 : {
2611 : #if !defined(AE_NO_EXCEPTIONS)
2612 0 : _ALGLIB_CPP_EXCEPTION(_alglib_env_state.error_msg);
2613 : #else
2614 : _ALGLIB_SET_ERROR_FLAG(_alglib_env_state.error_msg);
2615 : return;
2616 : #endif
2617 : }
2618 0 : ae_state_set_break_jump(&_alglib_env_state, &_break_jump);
2619 0 : if( _xparams.flags!=0x0 )
2620 0 : ae_state_set_flags(&_alglib_env_state, _xparams.flags);
2621 0 : alglib_impl::onesamplevariancetest(const_cast<alglib_impl::ae_vector*>(x.c_ptr()), n, variance, &bothtails, &lefttail, &righttail, &_alglib_env_state);
2622 0 : alglib_impl::ae_state_clear(&_alglib_env_state);
2623 0 : return;
2624 : }
2625 : #endif
2626 : }
2627 :
2628 : /////////////////////////////////////////////////////////////////////////
2629 : //
2630 : // THIS SECTION CONTAINS IMPLEMENTATION OF COMPUTATIONAL CORE
2631 : //
2632 : /////////////////////////////////////////////////////////////////////////
2633 : namespace alglib_impl
2634 : {
2635 : #if defined(AE_COMPILE_BASESTAT) || !defined(AE_PARTIAL_BUILD)
2636 : static void basestat_rankdatarec(/* Real */ ae_matrix* xy,
2637 : ae_int_t i0,
2638 : ae_int_t i1,
2639 : ae_int_t nfeatures,
2640 : ae_bool iscentered,
2641 : ae_shared_pool* pool,
2642 : ae_int_t basecasecost,
2643 : ae_state *_state);
2644 : ae_bool _trypexec_basestat_rankdatarec(/* Real */ ae_matrix* xy,
2645 : ae_int_t i0,
2646 : ae_int_t i1,
2647 : ae_int_t nfeatures,
2648 : ae_bool iscentered,
2649 : ae_shared_pool* pool,
2650 : ae_int_t basecasecost, ae_state *_state);
2651 : static void basestat_rankdatabasecase(/* Real */ ae_matrix* xy,
2652 : ae_int_t i0,
2653 : ae_int_t i1,
2654 : ae_int_t nfeatures,
2655 : ae_bool iscentered,
2656 : apbuffers* buf0,
2657 : apbuffers* buf1,
2658 : ae_state *_state);
2659 : ae_bool _trypexec_basestat_rankdatabasecase(/* Real */ ae_matrix* xy,
2660 : ae_int_t i0,
2661 : ae_int_t i1,
2662 : ae_int_t nfeatures,
2663 : ae_bool iscentered,
2664 : apbuffers* buf0,
2665 : apbuffers* buf1, ae_state *_state);
2666 :
2667 :
2668 : #endif
2669 : #if defined(AE_COMPILE_WSR) || !defined(AE_PARTIAL_BUILD)
2670 : static void wsr_wcheb(double x,
2671 : double c,
2672 : double* tj,
2673 : double* tj1,
2674 : double* r,
2675 : ae_state *_state);
2676 : static double wsr_w5(double s, ae_state *_state);
2677 : static double wsr_w6(double s, ae_state *_state);
2678 : static double wsr_w7(double s, ae_state *_state);
2679 : static double wsr_w8(double s, ae_state *_state);
2680 : static double wsr_w9(double s, ae_state *_state);
2681 : static double wsr_w10(double s, ae_state *_state);
2682 : static double wsr_w11(double s, ae_state *_state);
2683 : static double wsr_w12(double s, ae_state *_state);
2684 : static double wsr_w13(double s, ae_state *_state);
2685 : static double wsr_w14(double s, ae_state *_state);
2686 : static double wsr_w15(double s, ae_state *_state);
2687 : static double wsr_w16(double s, ae_state *_state);
2688 : static double wsr_w17(double s, ae_state *_state);
2689 : static double wsr_w18(double s, ae_state *_state);
2690 : static double wsr_w19(double s, ae_state *_state);
2691 : static double wsr_w20(double s, ae_state *_state);
2692 : static double wsr_w21(double s, ae_state *_state);
2693 : static double wsr_w22(double s, ae_state *_state);
2694 : static double wsr_w23(double s, ae_state *_state);
2695 : static double wsr_w24(double s, ae_state *_state);
2696 : static double wsr_w25(double s, ae_state *_state);
2697 : static double wsr_w26(double s, ae_state *_state);
2698 : static double wsr_w27(double s, ae_state *_state);
2699 : static double wsr_w28(double s, ae_state *_state);
2700 : static double wsr_w29(double s, ae_state *_state);
2701 : static double wsr_w30(double s, ae_state *_state);
2702 : static double wsr_w40(double s, ae_state *_state);
2703 : static double wsr_w60(double s, ae_state *_state);
2704 : static double wsr_w120(double s, ae_state *_state);
2705 : static double wsr_w200(double s, ae_state *_state);
2706 : static double wsr_wsigma(double s, ae_int_t n, ae_state *_state);
2707 :
2708 :
2709 : #endif
2710 : #if defined(AE_COMPILE_STEST) || !defined(AE_PARTIAL_BUILD)
2711 :
2712 :
2713 : #endif
2714 : #if defined(AE_COMPILE_CORRELATIONTESTS) || !defined(AE_PARTIAL_BUILD)
2715 : static double correlationtests_spearmantail5(double s, ae_state *_state);
2716 : static double correlationtests_spearmantail6(double s, ae_state *_state);
2717 : static double correlationtests_spearmantail7(double s, ae_state *_state);
2718 : static double correlationtests_spearmantail8(double s, ae_state *_state);
2719 : static double correlationtests_spearmantail9(double s, ae_state *_state);
2720 : static double correlationtests_spearmantail(double t,
2721 : ae_int_t n,
2722 : ae_state *_state);
2723 :
2724 :
2725 : #endif
2726 : #if defined(AE_COMPILE_STUDENTTTESTS) || !defined(AE_PARTIAL_BUILD)
2727 :
2728 :
2729 : #endif
2730 : #if defined(AE_COMPILE_MANNWHITNEYU) || !defined(AE_PARTIAL_BUILD)
2731 : static void mannwhitneyu_ucheb(double x,
2732 : double c,
2733 : double* tj,
2734 : double* tj1,
2735 : double* r,
2736 : ae_state *_state);
2737 : static double mannwhitneyu_uninterpolate(double p1,
2738 : double p2,
2739 : double p3,
2740 : ae_int_t n,
2741 : ae_state *_state);
2742 : static double mannwhitneyu_usigma000(ae_int_t n1,
2743 : ae_int_t n2,
2744 : ae_state *_state);
2745 : static double mannwhitneyu_usigma075(ae_int_t n1,
2746 : ae_int_t n2,
2747 : ae_state *_state);
2748 : static double mannwhitneyu_usigma150(ae_int_t n1,
2749 : ae_int_t n2,
2750 : ae_state *_state);
2751 : static double mannwhitneyu_usigma225(ae_int_t n1,
2752 : ae_int_t n2,
2753 : ae_state *_state);
2754 : static double mannwhitneyu_usigma300(ae_int_t n1,
2755 : ae_int_t n2,
2756 : ae_state *_state);
2757 : static double mannwhitneyu_usigma333(ae_int_t n1,
2758 : ae_int_t n2,
2759 : ae_state *_state);
2760 : static double mannwhitneyu_usigma367(ae_int_t n1,
2761 : ae_int_t n2,
2762 : ae_state *_state);
2763 : static double mannwhitneyu_usigma400(ae_int_t n1,
2764 : ae_int_t n2,
2765 : ae_state *_state);
2766 : static double mannwhitneyu_utbln5n5(double s, ae_state *_state);
2767 : static double mannwhitneyu_utbln5n6(double s, ae_state *_state);
2768 : static double mannwhitneyu_utbln5n7(double s, ae_state *_state);
2769 : static double mannwhitneyu_utbln5n8(double s, ae_state *_state);
2770 : static double mannwhitneyu_utbln5n9(double s, ae_state *_state);
2771 : static double mannwhitneyu_utbln5n10(double s, ae_state *_state);
2772 : static double mannwhitneyu_utbln5n11(double s, ae_state *_state);
2773 : static double mannwhitneyu_utbln5n12(double s, ae_state *_state);
2774 : static double mannwhitneyu_utbln5n13(double s, ae_state *_state);
2775 : static double mannwhitneyu_utbln5n14(double s, ae_state *_state);
2776 : static double mannwhitneyu_utbln5n15(double s, ae_state *_state);
2777 : static double mannwhitneyu_utbln5n16(double s, ae_state *_state);
2778 : static double mannwhitneyu_utbln5n17(double s, ae_state *_state);
2779 : static double mannwhitneyu_utbln5n18(double s, ae_state *_state);
2780 : static double mannwhitneyu_utbln5n19(double s, ae_state *_state);
2781 : static double mannwhitneyu_utbln5n20(double s, ae_state *_state);
2782 : static double mannwhitneyu_utbln5n21(double s, ae_state *_state);
2783 : static double mannwhitneyu_utbln5n22(double s, ae_state *_state);
2784 : static double mannwhitneyu_utbln5n23(double s, ae_state *_state);
2785 : static double mannwhitneyu_utbln5n24(double s, ae_state *_state);
2786 : static double mannwhitneyu_utbln5n25(double s, ae_state *_state);
2787 : static double mannwhitneyu_utbln5n26(double s, ae_state *_state);
2788 : static double mannwhitneyu_utbln5n27(double s, ae_state *_state);
2789 : static double mannwhitneyu_utbln5n28(double s, ae_state *_state);
2790 : static double mannwhitneyu_utbln5n29(double s, ae_state *_state);
2791 : static double mannwhitneyu_utbln5n30(double s, ae_state *_state);
2792 : static double mannwhitneyu_utbln5n100(double s, ae_state *_state);
2793 : static double mannwhitneyu_utbln6n6(double s, ae_state *_state);
2794 : static double mannwhitneyu_utbln6n7(double s, ae_state *_state);
2795 : static double mannwhitneyu_utbln6n8(double s, ae_state *_state);
2796 : static double mannwhitneyu_utbln6n9(double s, ae_state *_state);
2797 : static double mannwhitneyu_utbln6n10(double s, ae_state *_state);
2798 : static double mannwhitneyu_utbln6n11(double s, ae_state *_state);
2799 : static double mannwhitneyu_utbln6n12(double s, ae_state *_state);
2800 : static double mannwhitneyu_utbln6n13(double s, ae_state *_state);
2801 : static double mannwhitneyu_utbln6n14(double s, ae_state *_state);
2802 : static double mannwhitneyu_utbln6n15(double s, ae_state *_state);
2803 : static double mannwhitneyu_utbln6n30(double s, ae_state *_state);
2804 : static double mannwhitneyu_utbln6n100(double s, ae_state *_state);
2805 : static double mannwhitneyu_utbln7n7(double s, ae_state *_state);
2806 : static double mannwhitneyu_utbln7n8(double s, ae_state *_state);
2807 : static double mannwhitneyu_utbln7n9(double s, ae_state *_state);
2808 : static double mannwhitneyu_utbln7n10(double s, ae_state *_state);
2809 : static double mannwhitneyu_utbln7n11(double s, ae_state *_state);
2810 : static double mannwhitneyu_utbln7n12(double s, ae_state *_state);
2811 : static double mannwhitneyu_utbln7n13(double s, ae_state *_state);
2812 : static double mannwhitneyu_utbln7n14(double s, ae_state *_state);
2813 : static double mannwhitneyu_utbln7n15(double s, ae_state *_state);
2814 : static double mannwhitneyu_utbln7n30(double s, ae_state *_state);
2815 : static double mannwhitneyu_utbln7n100(double s, ae_state *_state);
2816 : static double mannwhitneyu_utbln8n8(double s, ae_state *_state);
2817 : static double mannwhitneyu_utbln8n9(double s, ae_state *_state);
2818 : static double mannwhitneyu_utbln8n10(double s, ae_state *_state);
2819 : static double mannwhitneyu_utbln8n11(double s, ae_state *_state);
2820 : static double mannwhitneyu_utbln8n12(double s, ae_state *_state);
2821 : static double mannwhitneyu_utbln8n13(double s, ae_state *_state);
2822 : static double mannwhitneyu_utbln8n14(double s, ae_state *_state);
2823 : static double mannwhitneyu_utbln8n15(double s, ae_state *_state);
2824 : static double mannwhitneyu_utbln8n30(double s, ae_state *_state);
2825 : static double mannwhitneyu_utbln8n100(double s, ae_state *_state);
2826 : static double mannwhitneyu_utbln9n9(double s, ae_state *_state);
2827 : static double mannwhitneyu_utbln9n10(double s, ae_state *_state);
2828 : static double mannwhitneyu_utbln9n11(double s, ae_state *_state);
2829 : static double mannwhitneyu_utbln9n12(double s, ae_state *_state);
2830 : static double mannwhitneyu_utbln9n13(double s, ae_state *_state);
2831 : static double mannwhitneyu_utbln9n14(double s, ae_state *_state);
2832 : static double mannwhitneyu_utbln9n15(double s, ae_state *_state);
2833 : static double mannwhitneyu_utbln9n30(double s, ae_state *_state);
2834 : static double mannwhitneyu_utbln9n100(double s, ae_state *_state);
2835 : static double mannwhitneyu_utbln10n10(double s, ae_state *_state);
2836 : static double mannwhitneyu_utbln10n11(double s, ae_state *_state);
2837 : static double mannwhitneyu_utbln10n12(double s, ae_state *_state);
2838 : static double mannwhitneyu_utbln10n13(double s, ae_state *_state);
2839 : static double mannwhitneyu_utbln10n14(double s, ae_state *_state);
2840 : static double mannwhitneyu_utbln10n15(double s, ae_state *_state);
2841 : static double mannwhitneyu_utbln10n30(double s, ae_state *_state);
2842 : static double mannwhitneyu_utbln10n100(double s, ae_state *_state);
2843 : static double mannwhitneyu_utbln11n11(double s, ae_state *_state);
2844 : static double mannwhitneyu_utbln11n12(double s, ae_state *_state);
2845 : static double mannwhitneyu_utbln11n13(double s, ae_state *_state);
2846 : static double mannwhitneyu_utbln11n14(double s, ae_state *_state);
2847 : static double mannwhitneyu_utbln11n15(double s, ae_state *_state);
2848 : static double mannwhitneyu_utbln11n30(double s, ae_state *_state);
2849 : static double mannwhitneyu_utbln11n100(double s, ae_state *_state);
2850 : static double mannwhitneyu_utbln12n12(double s, ae_state *_state);
2851 : static double mannwhitneyu_utbln12n13(double s, ae_state *_state);
2852 : static double mannwhitneyu_utbln12n14(double s, ae_state *_state);
2853 : static double mannwhitneyu_utbln12n15(double s, ae_state *_state);
2854 : static double mannwhitneyu_utbln12n30(double s, ae_state *_state);
2855 : static double mannwhitneyu_utbln12n100(double s, ae_state *_state);
2856 : static double mannwhitneyu_utbln13n13(double s, ae_state *_state);
2857 : static double mannwhitneyu_utbln13n14(double s, ae_state *_state);
2858 : static double mannwhitneyu_utbln13n15(double s, ae_state *_state);
2859 : static double mannwhitneyu_utbln13n30(double s, ae_state *_state);
2860 : static double mannwhitneyu_utbln13n100(double s, ae_state *_state);
2861 : static double mannwhitneyu_utbln14n14(double s, ae_state *_state);
2862 : static double mannwhitneyu_utbln14n15(double s, ae_state *_state);
2863 : static double mannwhitneyu_utbln14n30(double s, ae_state *_state);
2864 : static double mannwhitneyu_utbln14n100(double s, ae_state *_state);
2865 : static double mannwhitneyu_usigma(double s,
2866 : ae_int_t n1,
2867 : ae_int_t n2,
2868 : ae_state *_state);
2869 :
2870 :
2871 : #endif
2872 : #if defined(AE_COMPILE_JARQUEBERA) || !defined(AE_PARTIAL_BUILD)
2873 : static void jarquebera_jarqueberastatistic(/* Real */ ae_vector* x,
2874 : ae_int_t n,
2875 : double* s,
2876 : ae_state *_state);
2877 : static double jarquebera_jarqueberaapprox(ae_int_t n,
2878 : double s,
2879 : ae_state *_state);
2880 : static double jarquebera_jbtbl5(double s, ae_state *_state);
2881 : static double jarquebera_jbtbl6(double s, ae_state *_state);
2882 : static double jarquebera_jbtbl7(double s, ae_state *_state);
2883 : static double jarquebera_jbtbl8(double s, ae_state *_state);
2884 : static double jarquebera_jbtbl9(double s, ae_state *_state);
2885 : static double jarquebera_jbtbl10(double s, ae_state *_state);
2886 : static double jarquebera_jbtbl11(double s, ae_state *_state);
2887 : static double jarquebera_jbtbl12(double s, ae_state *_state);
2888 : static double jarquebera_jbtbl13(double s, ae_state *_state);
2889 : static double jarquebera_jbtbl14(double s, ae_state *_state);
2890 : static double jarquebera_jbtbl15(double s, ae_state *_state);
2891 : static double jarquebera_jbtbl16(double s, ae_state *_state);
2892 : static double jarquebera_jbtbl17(double s, ae_state *_state);
2893 : static double jarquebera_jbtbl18(double s, ae_state *_state);
2894 : static double jarquebera_jbtbl19(double s, ae_state *_state);
2895 : static double jarquebera_jbtbl20(double s, ae_state *_state);
2896 : static double jarquebera_jbtbl30(double s, ae_state *_state);
2897 : static double jarquebera_jbtbl50(double s, ae_state *_state);
2898 : static double jarquebera_jbtbl65(double s, ae_state *_state);
2899 : static double jarquebera_jbtbl100(double s, ae_state *_state);
2900 : static double jarquebera_jbtbl130(double s, ae_state *_state);
2901 : static double jarquebera_jbtbl200(double s, ae_state *_state);
2902 : static double jarquebera_jbtbl301(double s, ae_state *_state);
2903 : static double jarquebera_jbtbl501(double s, ae_state *_state);
2904 : static double jarquebera_jbtbl701(double s, ae_state *_state);
2905 : static double jarquebera_jbtbl1401(double s, ae_state *_state);
2906 : static void jarquebera_jbcheb(double x,
2907 : double c,
2908 : double* tj,
2909 : double* tj1,
2910 : double* r,
2911 : ae_state *_state);
2912 :
2913 :
2914 : #endif
2915 : #if defined(AE_COMPILE_VARIANCETESTS) || !defined(AE_PARTIAL_BUILD)
2916 :
2917 :
2918 : #endif
2919 :
2920 : #if defined(AE_COMPILE_BASESTAT) || !defined(AE_PARTIAL_BUILD)
2921 :
2922 :
2923 : /*************************************************************************
2924 : Calculation of the distribution moments: mean, variance, skewness, kurtosis.
2925 :
2926 : INPUT PARAMETERS:
2927 : X - sample
2928 : N - N>=0, sample size:
2929 : * if given, only leading N elements of X are processed
2930 : * if not given, automatically determined from size of X
2931 :
2932 : OUTPUT PARAMETERS
2933 : Mean - mean.
2934 : Variance- variance.
2935 : Skewness- skewness (if variance<>0; zero otherwise).
2936 : Kurtosis- kurtosis (if variance<>0; zero otherwise).
2937 :
2938 : NOTE: variance is calculated by dividing sum of squares by N-1, not N.
2939 :
2940 : -- ALGLIB --
2941 : Copyright 06.09.2006 by Bochkanov Sergey
2942 : *************************************************************************/
2943 0 : void samplemoments(/* Real */ ae_vector* x,
2944 : ae_int_t n,
2945 : double* mean,
2946 : double* variance,
2947 : double* skewness,
2948 : double* kurtosis,
2949 : ae_state *_state)
2950 : {
2951 : ae_int_t i;
2952 : double v;
2953 : double v1;
2954 : double v2;
2955 : double stddev;
2956 :
2957 0 : *mean = 0;
2958 0 : *variance = 0;
2959 0 : *skewness = 0;
2960 0 : *kurtosis = 0;
2961 :
2962 0 : ae_assert(n>=0, "SampleMoments: N<0", _state);
2963 0 : ae_assert(x->cnt>=n, "SampleMoments: Length(X)<N!", _state);
2964 0 : ae_assert(isfinitevector(x, n, _state), "SampleMoments: X is not finite vector", _state);
2965 :
2966 : /*
2967 : * Init, special case 'N=0'
2968 : */
2969 0 : *mean = (double)(0);
2970 0 : *variance = (double)(0);
2971 0 : *skewness = (double)(0);
2972 0 : *kurtosis = (double)(0);
2973 0 : stddev = (double)(0);
2974 0 : if( n<=0 )
2975 : {
2976 0 : return;
2977 : }
2978 :
2979 : /*
2980 : * Mean
2981 : */
2982 0 : for(i=0; i<=n-1; i++)
2983 : {
2984 0 : *mean = *mean+x->ptr.p_double[i];
2985 : }
2986 0 : *mean = *mean/n;
2987 :
2988 : /*
2989 : * Variance (using corrected two-pass algorithm)
2990 : */
2991 0 : if( n!=1 )
2992 : {
2993 0 : v1 = (double)(0);
2994 0 : for(i=0; i<=n-1; i++)
2995 : {
2996 0 : v1 = v1+ae_sqr(x->ptr.p_double[i]-(*mean), _state);
2997 : }
2998 0 : v2 = (double)(0);
2999 0 : for(i=0; i<=n-1; i++)
3000 : {
3001 0 : v2 = v2+(x->ptr.p_double[i]-(*mean));
3002 : }
3003 0 : v2 = ae_sqr(v2, _state)/n;
3004 0 : *variance = (v1-v2)/(n-1);
3005 0 : if( ae_fp_less(*variance,(double)(0)) )
3006 : {
3007 0 : *variance = (double)(0);
3008 : }
3009 0 : stddev = ae_sqrt(*variance, _state);
3010 : }
3011 :
3012 : /*
3013 : * Skewness and kurtosis
3014 : */
3015 0 : if( ae_fp_neq(stddev,(double)(0)) )
3016 : {
3017 0 : for(i=0; i<=n-1; i++)
3018 : {
3019 0 : v = (x->ptr.p_double[i]-(*mean))/stddev;
3020 0 : v2 = ae_sqr(v, _state);
3021 0 : *skewness = *skewness+v2*v;
3022 0 : *kurtosis = *kurtosis+ae_sqr(v2, _state);
3023 : }
3024 0 : *skewness = *skewness/n;
3025 0 : *kurtosis = *kurtosis/n-3;
3026 : }
3027 : }
3028 :
3029 :
3030 : /*************************************************************************
3031 : Calculation of the mean.
3032 :
3033 : INPUT PARAMETERS:
3034 : X - sample
3035 : N - N>=0, sample size:
3036 : * if given, only leading N elements of X are processed
3037 : * if not given, automatically determined from size of X
3038 :
3039 : NOTE:
3040 :
3041 : This function return result which calculated by 'SampleMoments' function
3042 : and stored at 'Mean' variable.
3043 :
3044 :
3045 : -- ALGLIB --
3046 : Copyright 06.09.2006 by Bochkanov Sergey
3047 : *************************************************************************/
3048 0 : double samplemean(/* Real */ ae_vector* x,
3049 : ae_int_t n,
3050 : ae_state *_state)
3051 : {
3052 : double mean;
3053 : double tmp0;
3054 : double tmp1;
3055 : double tmp2;
3056 : double result;
3057 :
3058 :
3059 0 : samplemoments(x, n, &mean, &tmp0, &tmp1, &tmp2, _state);
3060 0 : result = mean;
3061 0 : return result;
3062 : }
3063 :
3064 :
3065 : /*************************************************************************
3066 : Calculation of the variance.
3067 :
3068 : INPUT PARAMETERS:
3069 : X - sample
3070 : N - N>=0, sample size:
3071 : * if given, only leading N elements of X are processed
3072 : * if not given, automatically determined from size of X
3073 :
3074 : NOTE:
3075 :
3076 : This function return result which calculated by 'SampleMoments' function
3077 : and stored at 'Variance' variable.
3078 :
3079 :
3080 : -- ALGLIB --
3081 : Copyright 06.09.2006 by Bochkanov Sergey
3082 : *************************************************************************/
3083 0 : double samplevariance(/* Real */ ae_vector* x,
3084 : ae_int_t n,
3085 : ae_state *_state)
3086 : {
3087 : double variance;
3088 : double tmp0;
3089 : double tmp1;
3090 : double tmp2;
3091 : double result;
3092 :
3093 :
3094 0 : samplemoments(x, n, &tmp0, &variance, &tmp1, &tmp2, _state);
3095 0 : result = variance;
3096 0 : return result;
3097 : }
3098 :
3099 :
3100 : /*************************************************************************
3101 : Calculation of the skewness.
3102 :
3103 : INPUT PARAMETERS:
3104 : X - sample
3105 : N - N>=0, sample size:
3106 : * if given, only leading N elements of X are processed
3107 : * if not given, automatically determined from size of X
3108 :
3109 : NOTE:
3110 :
3111 : This function return result which calculated by 'SampleMoments' function
3112 : and stored at 'Skewness' variable.
3113 :
3114 :
3115 : -- ALGLIB --
3116 : Copyright 06.09.2006 by Bochkanov Sergey
3117 : *************************************************************************/
3118 0 : double sampleskewness(/* Real */ ae_vector* x,
3119 : ae_int_t n,
3120 : ae_state *_state)
3121 : {
3122 : double skewness;
3123 : double tmp0;
3124 : double tmp1;
3125 : double tmp2;
3126 : double result;
3127 :
3128 :
3129 0 : samplemoments(x, n, &tmp0, &tmp1, &skewness, &tmp2, _state);
3130 0 : result = skewness;
3131 0 : return result;
3132 : }
3133 :
3134 :
3135 : /*************************************************************************
3136 : Calculation of the kurtosis.
3137 :
3138 : INPUT PARAMETERS:
3139 : X - sample
3140 : N - N>=0, sample size:
3141 : * if given, only leading N elements of X are processed
3142 : * if not given, automatically determined from size of X
3143 :
3144 : NOTE:
3145 :
3146 : This function return result which calculated by 'SampleMoments' function
3147 : and stored at 'Kurtosis' variable.
3148 :
3149 :
3150 : -- ALGLIB --
3151 : Copyright 06.09.2006 by Bochkanov Sergey
3152 : *************************************************************************/
3153 0 : double samplekurtosis(/* Real */ ae_vector* x,
3154 : ae_int_t n,
3155 : ae_state *_state)
3156 : {
3157 : double kurtosis;
3158 : double tmp0;
3159 : double tmp1;
3160 : double tmp2;
3161 : double result;
3162 :
3163 :
3164 0 : samplemoments(x, n, &tmp0, &tmp1, &tmp2, &kurtosis, _state);
3165 0 : result = kurtosis;
3166 0 : return result;
3167 : }
3168 :
3169 :
3170 : /*************************************************************************
3171 : ADev
3172 :
3173 : Input parameters:
3174 : X - sample
3175 : N - N>=0, sample size:
3176 : * if given, only leading N elements of X are processed
3177 : * if not given, automatically determined from size of X
3178 :
3179 : Output parameters:
3180 : ADev- ADev
3181 :
3182 : -- ALGLIB --
3183 : Copyright 06.09.2006 by Bochkanov Sergey
3184 : *************************************************************************/
3185 0 : void sampleadev(/* Real */ ae_vector* x,
3186 : ae_int_t n,
3187 : double* adev,
3188 : ae_state *_state)
3189 : {
3190 : ae_int_t i;
3191 : double mean;
3192 :
3193 0 : *adev = 0;
3194 :
3195 0 : ae_assert(n>=0, "SampleADev: N<0", _state);
3196 0 : ae_assert(x->cnt>=n, "SampleADev: Length(X)<N!", _state);
3197 0 : ae_assert(isfinitevector(x, n, _state), "SampleADev: X is not finite vector", _state);
3198 :
3199 : /*
3200 : * Init, handle N=0
3201 : */
3202 0 : mean = (double)(0);
3203 0 : *adev = (double)(0);
3204 0 : if( n<=0 )
3205 : {
3206 0 : return;
3207 : }
3208 :
3209 : /*
3210 : * Mean
3211 : */
3212 0 : for(i=0; i<=n-1; i++)
3213 : {
3214 0 : mean = mean+x->ptr.p_double[i];
3215 : }
3216 0 : mean = mean/n;
3217 :
3218 : /*
3219 : * ADev
3220 : */
3221 0 : for(i=0; i<=n-1; i++)
3222 : {
3223 0 : *adev = *adev+ae_fabs(x->ptr.p_double[i]-mean, _state);
3224 : }
3225 0 : *adev = *adev/n;
3226 : }
3227 :
3228 :
3229 : /*************************************************************************
3230 : Median calculation.
3231 :
3232 : Input parameters:
3233 : X - sample (array indexes: [0..N-1])
3234 : N - N>=0, sample size:
3235 : * if given, only leading N elements of X are processed
3236 : * if not given, automatically determined from size of X
3237 :
3238 : Output parameters:
3239 : Median
3240 :
3241 : -- ALGLIB --
3242 : Copyright 06.09.2006 by Bochkanov Sergey
3243 : *************************************************************************/
3244 0 : void samplemedian(/* Real */ ae_vector* x,
3245 : ae_int_t n,
3246 : double* median,
3247 : ae_state *_state)
3248 : {
3249 : ae_frame _frame_block;
3250 : ae_vector _x;
3251 : ae_int_t i;
3252 : ae_int_t ir;
3253 : ae_int_t j;
3254 : ae_int_t l;
3255 : ae_int_t midp;
3256 : ae_int_t k;
3257 : double a;
3258 : double tval;
3259 :
3260 0 : ae_frame_make(_state, &_frame_block);
3261 0 : memset(&_x, 0, sizeof(_x));
3262 0 : ae_vector_init_copy(&_x, x, _state, ae_true);
3263 0 : x = &_x;
3264 0 : *median = 0;
3265 :
3266 0 : ae_assert(n>=0, "SampleMedian: N<0", _state);
3267 0 : ae_assert(x->cnt>=n, "SampleMedian: Length(X)<N!", _state);
3268 0 : ae_assert(isfinitevector(x, n, _state), "SampleMedian: X is not finite vector", _state);
3269 :
3270 : /*
3271 : * Some degenerate cases
3272 : */
3273 0 : *median = (double)(0);
3274 0 : if( n<=0 )
3275 : {
3276 0 : ae_frame_leave(_state);
3277 0 : return;
3278 : }
3279 0 : if( n==1 )
3280 : {
3281 0 : *median = x->ptr.p_double[0];
3282 0 : ae_frame_leave(_state);
3283 0 : return;
3284 : }
3285 0 : if( n==2 )
3286 : {
3287 0 : *median = 0.5*(x->ptr.p_double[0]+x->ptr.p_double[1]);
3288 0 : ae_frame_leave(_state);
3289 0 : return;
3290 : }
3291 :
3292 : /*
3293 : * Common case, N>=3.
3294 : * Choose X[(N-1)/2]
3295 : */
3296 0 : l = 0;
3297 0 : ir = n-1;
3298 0 : k = (n-1)/2;
3299 : for(;;)
3300 : {
3301 0 : if( ir<=l+1 )
3302 : {
3303 :
3304 : /*
3305 : * 1 or 2 elements in partition
3306 : */
3307 0 : if( ir==l+1&&ae_fp_less(x->ptr.p_double[ir],x->ptr.p_double[l]) )
3308 : {
3309 0 : tval = x->ptr.p_double[l];
3310 0 : x->ptr.p_double[l] = x->ptr.p_double[ir];
3311 0 : x->ptr.p_double[ir] = tval;
3312 : }
3313 0 : break;
3314 : }
3315 : else
3316 : {
3317 0 : midp = (l+ir)/2;
3318 0 : tval = x->ptr.p_double[midp];
3319 0 : x->ptr.p_double[midp] = x->ptr.p_double[l+1];
3320 0 : x->ptr.p_double[l+1] = tval;
3321 0 : if( ae_fp_greater(x->ptr.p_double[l],x->ptr.p_double[ir]) )
3322 : {
3323 0 : tval = x->ptr.p_double[l];
3324 0 : x->ptr.p_double[l] = x->ptr.p_double[ir];
3325 0 : x->ptr.p_double[ir] = tval;
3326 : }
3327 0 : if( ae_fp_greater(x->ptr.p_double[l+1],x->ptr.p_double[ir]) )
3328 : {
3329 0 : tval = x->ptr.p_double[l+1];
3330 0 : x->ptr.p_double[l+1] = x->ptr.p_double[ir];
3331 0 : x->ptr.p_double[ir] = tval;
3332 : }
3333 0 : if( ae_fp_greater(x->ptr.p_double[l],x->ptr.p_double[l+1]) )
3334 : {
3335 0 : tval = x->ptr.p_double[l];
3336 0 : x->ptr.p_double[l] = x->ptr.p_double[l+1];
3337 0 : x->ptr.p_double[l+1] = tval;
3338 : }
3339 0 : i = l+1;
3340 0 : j = ir;
3341 0 : a = x->ptr.p_double[l+1];
3342 0 : for(;;)
3343 : {
3344 : do
3345 : {
3346 0 : i = i+1;
3347 : }
3348 0 : while(ae_fp_less(x->ptr.p_double[i],a));
3349 : do
3350 : {
3351 0 : j = j-1;
3352 : }
3353 0 : while(ae_fp_greater(x->ptr.p_double[j],a));
3354 0 : if( j<i )
3355 : {
3356 0 : break;
3357 : }
3358 0 : tval = x->ptr.p_double[i];
3359 0 : x->ptr.p_double[i] = x->ptr.p_double[j];
3360 0 : x->ptr.p_double[j] = tval;
3361 : }
3362 0 : x->ptr.p_double[l+1] = x->ptr.p_double[j];
3363 0 : x->ptr.p_double[j] = a;
3364 0 : if( j>=k )
3365 : {
3366 0 : ir = j-1;
3367 : }
3368 0 : if( j<=k )
3369 : {
3370 0 : l = i;
3371 : }
3372 : }
3373 : }
3374 :
3375 : /*
3376 : * If N is odd, return result
3377 : */
3378 0 : if( n%2==1 )
3379 : {
3380 0 : *median = x->ptr.p_double[k];
3381 0 : ae_frame_leave(_state);
3382 0 : return;
3383 : }
3384 0 : a = x->ptr.p_double[n-1];
3385 0 : for(i=k+1; i<=n-1; i++)
3386 : {
3387 0 : if( ae_fp_less(x->ptr.p_double[i],a) )
3388 : {
3389 0 : a = x->ptr.p_double[i];
3390 : }
3391 : }
3392 0 : *median = 0.5*(x->ptr.p_double[k]+a);
3393 0 : ae_frame_leave(_state);
3394 : }
3395 :
3396 :
3397 : /*************************************************************************
3398 : Percentile calculation.
3399 :
3400 : Input parameters:
3401 : X - sample (array indexes: [0..N-1])
3402 : N - N>=0, sample size:
3403 : * if given, only leading N elements of X are processed
3404 : * if not given, automatically determined from size of X
3405 : P - percentile (0<=P<=1)
3406 :
3407 : Output parameters:
3408 : V - percentile
3409 :
3410 : -- ALGLIB --
3411 : Copyright 01.03.2008 by Bochkanov Sergey
3412 : *************************************************************************/
3413 0 : void samplepercentile(/* Real */ ae_vector* x,
3414 : ae_int_t n,
3415 : double p,
3416 : double* v,
3417 : ae_state *_state)
3418 : {
3419 : ae_frame _frame_block;
3420 : ae_vector _x;
3421 : ae_int_t i1;
3422 : double t;
3423 : ae_vector rbuf;
3424 :
3425 0 : ae_frame_make(_state, &_frame_block);
3426 0 : memset(&_x, 0, sizeof(_x));
3427 0 : memset(&rbuf, 0, sizeof(rbuf));
3428 0 : ae_vector_init_copy(&_x, x, _state, ae_true);
3429 0 : x = &_x;
3430 0 : *v = 0;
3431 0 : ae_vector_init(&rbuf, 0, DT_REAL, _state, ae_true);
3432 :
3433 0 : ae_assert(n>=0, "SamplePercentile: N<0", _state);
3434 0 : ae_assert(x->cnt>=n, "SamplePercentile: Length(X)<N!", _state);
3435 0 : ae_assert(isfinitevector(x, n, _state), "SamplePercentile: X is not finite vector", _state);
3436 0 : ae_assert(ae_isfinite(p, _state), "SamplePercentile: incorrect P!", _state);
3437 0 : ae_assert(ae_fp_greater_eq(p,(double)(0))&&ae_fp_less_eq(p,(double)(1)), "SamplePercentile: incorrect P!", _state);
3438 0 : tagsortfast(x, &rbuf, n, _state);
3439 0 : if( ae_fp_eq(p,(double)(0)) )
3440 : {
3441 0 : *v = x->ptr.p_double[0];
3442 0 : ae_frame_leave(_state);
3443 0 : return;
3444 : }
3445 0 : if( ae_fp_eq(p,(double)(1)) )
3446 : {
3447 0 : *v = x->ptr.p_double[n-1];
3448 0 : ae_frame_leave(_state);
3449 0 : return;
3450 : }
3451 0 : t = p*(n-1);
3452 0 : i1 = ae_ifloor(t, _state);
3453 0 : t = t-ae_ifloor(t, _state);
3454 0 : *v = x->ptr.p_double[i1]*(1-t)+x->ptr.p_double[i1+1]*t;
3455 0 : ae_frame_leave(_state);
3456 : }
3457 :
3458 :
3459 : /*************************************************************************
3460 : 2-sample covariance
3461 :
3462 : Input parameters:
3463 : X - sample 1 (array indexes: [0..N-1])
3464 : Y - sample 2 (array indexes: [0..N-1])
3465 : N - N>=0, sample size:
3466 : * if given, only N leading elements of X/Y are processed
3467 : * if not given, automatically determined from input sizes
3468 :
3469 : Result:
3470 : covariance (zero for N=0 or N=1)
3471 :
3472 : -- ALGLIB --
3473 : Copyright 28.10.2010 by Bochkanov Sergey
3474 : *************************************************************************/
3475 0 : double cov2(/* Real */ ae_vector* x,
3476 : /* Real */ ae_vector* y,
3477 : ae_int_t n,
3478 : ae_state *_state)
3479 : {
3480 : ae_int_t i;
3481 : double xmean;
3482 : double ymean;
3483 : double v;
3484 : double x0;
3485 : double y0;
3486 : double s;
3487 : ae_bool samex;
3488 : ae_bool samey;
3489 : double result;
3490 :
3491 :
3492 0 : ae_assert(n>=0, "Cov2: N<0", _state);
3493 0 : ae_assert(x->cnt>=n, "Cov2: Length(X)<N!", _state);
3494 0 : ae_assert(y->cnt>=n, "Cov2: Length(Y)<N!", _state);
3495 0 : ae_assert(isfinitevector(x, n, _state), "Cov2: X is not finite vector", _state);
3496 0 : ae_assert(isfinitevector(y, n, _state), "Cov2: Y is not finite vector", _state);
3497 :
3498 : /*
3499 : * Special case
3500 : */
3501 0 : if( n<=1 )
3502 : {
3503 0 : result = (double)(0);
3504 0 : return result;
3505 : }
3506 :
3507 : /*
3508 : * Calculate mean.
3509 : *
3510 : *
3511 : * Additonally we calculate SameX and SameY -
3512 : * flag variables which are set to True when
3513 : * all X[] (or Y[]) contain exactly same value.
3514 : *
3515 : * If at least one of them is True, we return zero
3516 : * (othwerwise we risk to get nonzero covariation
3517 : * because of roundoff).
3518 : */
3519 0 : xmean = (double)(0);
3520 0 : ymean = (double)(0);
3521 0 : samex = ae_true;
3522 0 : samey = ae_true;
3523 0 : x0 = x->ptr.p_double[0];
3524 0 : y0 = y->ptr.p_double[0];
3525 0 : v = (double)1/(double)n;
3526 0 : for(i=0; i<=n-1; i++)
3527 : {
3528 0 : s = x->ptr.p_double[i];
3529 0 : samex = samex&&ae_fp_eq(s,x0);
3530 0 : xmean = xmean+s*v;
3531 0 : s = y->ptr.p_double[i];
3532 0 : samey = samey&&ae_fp_eq(s,y0);
3533 0 : ymean = ymean+s*v;
3534 : }
3535 0 : if( samex||samey )
3536 : {
3537 0 : result = (double)(0);
3538 0 : return result;
3539 : }
3540 :
3541 : /*
3542 : * covariance
3543 : */
3544 0 : v = (double)1/(double)(n-1);
3545 0 : result = (double)(0);
3546 0 : for(i=0; i<=n-1; i++)
3547 : {
3548 0 : result = result+v*(x->ptr.p_double[i]-xmean)*(y->ptr.p_double[i]-ymean);
3549 : }
3550 0 : return result;
3551 : }
3552 :
3553 :
3554 : /*************************************************************************
3555 : Pearson product-moment correlation coefficient
3556 :
3557 : Input parameters:
3558 : X - sample 1 (array indexes: [0..N-1])
3559 : Y - sample 2 (array indexes: [0..N-1])
3560 : N - N>=0, sample size:
3561 : * if given, only N leading elements of X/Y are processed
3562 : * if not given, automatically determined from input sizes
3563 :
3564 : Result:
3565 : Pearson product-moment correlation coefficient
3566 : (zero for N=0 or N=1)
3567 :
3568 : -- ALGLIB --
3569 : Copyright 28.10.2010 by Bochkanov Sergey
3570 : *************************************************************************/
3571 0 : double pearsoncorr2(/* Real */ ae_vector* x,
3572 : /* Real */ ae_vector* y,
3573 : ae_int_t n,
3574 : ae_state *_state)
3575 : {
3576 : ae_int_t i;
3577 : double xmean;
3578 : double ymean;
3579 : double v;
3580 : double x0;
3581 : double y0;
3582 : double s;
3583 : ae_bool samex;
3584 : ae_bool samey;
3585 : double xv;
3586 : double yv;
3587 : double t1;
3588 : double t2;
3589 : double result;
3590 :
3591 :
3592 0 : ae_assert(n>=0, "PearsonCorr2: N<0", _state);
3593 0 : ae_assert(x->cnt>=n, "PearsonCorr2: Length(X)<N!", _state);
3594 0 : ae_assert(y->cnt>=n, "PearsonCorr2: Length(Y)<N!", _state);
3595 0 : ae_assert(isfinitevector(x, n, _state), "PearsonCorr2: X is not finite vector", _state);
3596 0 : ae_assert(isfinitevector(y, n, _state), "PearsonCorr2: Y is not finite vector", _state);
3597 :
3598 : /*
3599 : * Special case
3600 : */
3601 0 : if( n<=1 )
3602 : {
3603 0 : result = (double)(0);
3604 0 : return result;
3605 : }
3606 :
3607 : /*
3608 : * Calculate mean.
3609 : *
3610 : *
3611 : * Additonally we calculate SameX and SameY -
3612 : * flag variables which are set to True when
3613 : * all X[] (or Y[]) contain exactly same value.
3614 : *
3615 : * If at least one of them is True, we return zero
3616 : * (othwerwise we risk to get nonzero correlation
3617 : * because of roundoff).
3618 : */
3619 0 : xmean = (double)(0);
3620 0 : ymean = (double)(0);
3621 0 : samex = ae_true;
3622 0 : samey = ae_true;
3623 0 : x0 = x->ptr.p_double[0];
3624 0 : y0 = y->ptr.p_double[0];
3625 0 : v = (double)1/(double)n;
3626 0 : for(i=0; i<=n-1; i++)
3627 : {
3628 0 : s = x->ptr.p_double[i];
3629 0 : samex = samex&&ae_fp_eq(s,x0);
3630 0 : xmean = xmean+s*v;
3631 0 : s = y->ptr.p_double[i];
3632 0 : samey = samey&&ae_fp_eq(s,y0);
3633 0 : ymean = ymean+s*v;
3634 : }
3635 0 : if( samex||samey )
3636 : {
3637 0 : result = (double)(0);
3638 0 : return result;
3639 : }
3640 :
3641 : /*
3642 : * numerator and denominator
3643 : */
3644 0 : s = (double)(0);
3645 0 : xv = (double)(0);
3646 0 : yv = (double)(0);
3647 0 : for(i=0; i<=n-1; i++)
3648 : {
3649 0 : t1 = x->ptr.p_double[i]-xmean;
3650 0 : t2 = y->ptr.p_double[i]-ymean;
3651 0 : xv = xv+ae_sqr(t1, _state);
3652 0 : yv = yv+ae_sqr(t2, _state);
3653 0 : s = s+t1*t2;
3654 : }
3655 0 : if( ae_fp_eq(xv,(double)(0))||ae_fp_eq(yv,(double)(0)) )
3656 : {
3657 0 : result = (double)(0);
3658 : }
3659 : else
3660 : {
3661 0 : result = s/(ae_sqrt(xv, _state)*ae_sqrt(yv, _state));
3662 : }
3663 0 : return result;
3664 : }
3665 :
3666 :
3667 : /*************************************************************************
3668 : Spearman's rank correlation coefficient
3669 :
3670 : Input parameters:
3671 : X - sample 1 (array indexes: [0..N-1])
3672 : Y - sample 2 (array indexes: [0..N-1])
3673 : N - N>=0, sample size:
3674 : * if given, only N leading elements of X/Y are processed
3675 : * if not given, automatically determined from input sizes
3676 :
3677 : Result:
3678 : Spearman's rank correlation coefficient
3679 : (zero for N=0 or N=1)
3680 :
3681 : -- ALGLIB --
3682 : Copyright 09.04.2007 by Bochkanov Sergey
3683 : *************************************************************************/
3684 0 : double spearmancorr2(/* Real */ ae_vector* x,
3685 : /* Real */ ae_vector* y,
3686 : ae_int_t n,
3687 : ae_state *_state)
3688 : {
3689 : ae_frame _frame_block;
3690 : ae_vector _x;
3691 : ae_vector _y;
3692 : apbuffers buf;
3693 : double result;
3694 :
3695 0 : ae_frame_make(_state, &_frame_block);
3696 0 : memset(&_x, 0, sizeof(_x));
3697 0 : memset(&_y, 0, sizeof(_y));
3698 0 : memset(&buf, 0, sizeof(buf));
3699 0 : ae_vector_init_copy(&_x, x, _state, ae_true);
3700 0 : x = &_x;
3701 0 : ae_vector_init_copy(&_y, y, _state, ae_true);
3702 0 : y = &_y;
3703 0 : _apbuffers_init(&buf, _state, ae_true);
3704 :
3705 0 : ae_assert(n>=0, "SpearmanCorr2: N<0", _state);
3706 0 : ae_assert(x->cnt>=n, "SpearmanCorr2: Length(X)<N!", _state);
3707 0 : ae_assert(y->cnt>=n, "SpearmanCorr2: Length(Y)<N!", _state);
3708 0 : ae_assert(isfinitevector(x, n, _state), "SpearmanCorr2: X is not finite vector", _state);
3709 0 : ae_assert(isfinitevector(y, n, _state), "SpearmanCorr2: Y is not finite vector", _state);
3710 :
3711 : /*
3712 : * Special case
3713 : */
3714 0 : if( n<=1 )
3715 : {
3716 0 : result = (double)(0);
3717 0 : ae_frame_leave(_state);
3718 0 : return result;
3719 : }
3720 0 : rankx(x, n, ae_false, &buf, _state);
3721 0 : rankx(y, n, ae_false, &buf, _state);
3722 0 : result = pearsoncorr2(x, y, n, _state);
3723 0 : ae_frame_leave(_state);
3724 0 : return result;
3725 : }
3726 :
3727 :
3728 : /*************************************************************************
3729 : Covariance matrix
3730 :
3731 : ! COMMERCIAL EDITION OF ALGLIB:
3732 : !
3733 : ! Commercial Edition of ALGLIB includes following important improvements
3734 : ! of this function:
3735 : ! * high-performance native backend with same C# interface (C# version)
3736 : ! * multithreading support (C++ and C# versions)
3737 : ! * hardware vendor (Intel) implementations of linear algebra primitives
3738 : ! (C++ and C# versions, x86/x64 platform)
3739 : !
3740 : ! We recommend you to read 'Working with commercial version' section of
3741 : ! ALGLIB Reference Manual in order to find out how to use performance-
3742 : ! related features provided by commercial edition of ALGLIB.
3743 :
3744 : INPUT PARAMETERS:
3745 : X - array[N,M], sample matrix:
3746 : * J-th column corresponds to J-th variable
3747 : * I-th row corresponds to I-th observation
3748 : N - N>=0, number of observations:
3749 : * if given, only leading N rows of X are used
3750 : * if not given, automatically determined from input size
3751 : M - M>0, number of variables:
3752 : * if given, only leading M columns of X are used
3753 : * if not given, automatically determined from input size
3754 :
3755 : OUTPUT PARAMETERS:
3756 : C - array[M,M], covariance matrix (zero if N=0 or N=1)
3757 :
3758 : -- ALGLIB --
3759 : Copyright 28.10.2010 by Bochkanov Sergey
3760 : *************************************************************************/
3761 0 : void covm(/* Real */ ae_matrix* x,
3762 : ae_int_t n,
3763 : ae_int_t m,
3764 : /* Real */ ae_matrix* c,
3765 : ae_state *_state)
3766 : {
3767 : ae_frame _frame_block;
3768 : ae_matrix _x;
3769 : ae_int_t i;
3770 : ae_int_t j;
3771 : double v;
3772 : ae_vector t;
3773 : ae_vector x0;
3774 : ae_vector same;
3775 :
3776 0 : ae_frame_make(_state, &_frame_block);
3777 0 : memset(&_x, 0, sizeof(_x));
3778 0 : memset(&t, 0, sizeof(t));
3779 0 : memset(&x0, 0, sizeof(x0));
3780 0 : memset(&same, 0, sizeof(same));
3781 0 : ae_matrix_init_copy(&_x, x, _state, ae_true);
3782 0 : x = &_x;
3783 0 : ae_matrix_clear(c);
3784 0 : ae_vector_init(&t, 0, DT_REAL, _state, ae_true);
3785 0 : ae_vector_init(&x0, 0, DT_REAL, _state, ae_true);
3786 0 : ae_vector_init(&same, 0, DT_BOOL, _state, ae_true);
3787 :
3788 0 : ae_assert(n>=0, "CovM: N<0", _state);
3789 0 : ae_assert(m>=1, "CovM: M<1", _state);
3790 0 : ae_assert(x->rows>=n, "CovM: Rows(X)<N!", _state);
3791 0 : ae_assert(x->cols>=m||n==0, "CovM: Cols(X)<M!", _state);
3792 0 : ae_assert(apservisfinitematrix(x, n, m, _state), "CovM: X contains infinite/NAN elements", _state);
3793 :
3794 : /*
3795 : * N<=1, return zero
3796 : */
3797 0 : if( n<=1 )
3798 : {
3799 0 : ae_matrix_set_length(c, m, m, _state);
3800 0 : for(i=0; i<=m-1; i++)
3801 : {
3802 0 : for(j=0; j<=m-1; j++)
3803 : {
3804 0 : c->ptr.pp_double[i][j] = (double)(0);
3805 : }
3806 : }
3807 0 : ae_frame_leave(_state);
3808 0 : return;
3809 : }
3810 :
3811 : /*
3812 : * Calculate means,
3813 : * check for constant columns
3814 : */
3815 0 : ae_vector_set_length(&t, m, _state);
3816 0 : ae_vector_set_length(&x0, m, _state);
3817 0 : ae_vector_set_length(&same, m, _state);
3818 0 : ae_matrix_set_length(c, m, m, _state);
3819 0 : for(i=0; i<=m-1; i++)
3820 : {
3821 0 : t.ptr.p_double[i] = (double)(0);
3822 0 : same.ptr.p_bool[i] = ae_true;
3823 : }
3824 0 : ae_v_move(&x0.ptr.p_double[0], 1, &x->ptr.pp_double[0][0], 1, ae_v_len(0,m-1));
3825 0 : v = (double)1/(double)n;
3826 0 : for(i=0; i<=n-1; i++)
3827 : {
3828 0 : ae_v_addd(&t.ptr.p_double[0], 1, &x->ptr.pp_double[i][0], 1, ae_v_len(0,m-1), v);
3829 0 : for(j=0; j<=m-1; j++)
3830 : {
3831 0 : same.ptr.p_bool[j] = same.ptr.p_bool[j]&&ae_fp_eq(x->ptr.pp_double[i][j],x0.ptr.p_double[j]);
3832 : }
3833 : }
3834 :
3835 : /*
3836 : * * center variables;
3837 : * * if we have constant columns, these columns are
3838 : * artificially zeroed (they must be zero in exact arithmetics,
3839 : * but unfortunately floating point ops are not exact).
3840 : * * calculate upper half of symmetric covariance matrix
3841 : */
3842 0 : for(i=0; i<=n-1; i++)
3843 : {
3844 0 : ae_v_sub(&x->ptr.pp_double[i][0], 1, &t.ptr.p_double[0], 1, ae_v_len(0,m-1));
3845 0 : for(j=0; j<=m-1; j++)
3846 : {
3847 0 : if( same.ptr.p_bool[j] )
3848 : {
3849 0 : x->ptr.pp_double[i][j] = (double)(0);
3850 : }
3851 : }
3852 : }
3853 0 : rmatrixsyrk(m, n, (double)1/(double)(n-1), x, 0, 0, 1, 0.0, c, 0, 0, ae_true, _state);
3854 0 : rmatrixenforcesymmetricity(c, m, ae_true, _state);
3855 0 : ae_frame_leave(_state);
3856 : }
3857 :
3858 :
3859 : /*************************************************************************
3860 : Pearson product-moment correlation matrix
3861 :
3862 : ! COMMERCIAL EDITION OF ALGLIB:
3863 : !
3864 : ! Commercial Edition of ALGLIB includes following important improvements
3865 : ! of this function:
3866 : ! * high-performance native backend with same C# interface (C# version)
3867 : ! * multithreading support (C++ and C# versions)
3868 : ! * hardware vendor (Intel) implementations of linear algebra primitives
3869 : ! (C++ and C# versions, x86/x64 platform)
3870 : !
3871 : ! We recommend you to read 'Working with commercial version' section of
3872 : ! ALGLIB Reference Manual in order to find out how to use performance-
3873 : ! related features provided by commercial edition of ALGLIB.
3874 :
3875 : INPUT PARAMETERS:
3876 : X - array[N,M], sample matrix:
3877 : * J-th column corresponds to J-th variable
3878 : * I-th row corresponds to I-th observation
3879 : N - N>=0, number of observations:
3880 : * if given, only leading N rows of X are used
3881 : * if not given, automatically determined from input size
3882 : M - M>0, number of variables:
3883 : * if given, only leading M columns of X are used
3884 : * if not given, automatically determined from input size
3885 :
3886 : OUTPUT PARAMETERS:
3887 : C - array[M,M], correlation matrix (zero if N=0 or N=1)
3888 :
3889 : -- ALGLIB --
3890 : Copyright 28.10.2010 by Bochkanov Sergey
3891 : *************************************************************************/
3892 0 : void pearsoncorrm(/* Real */ ae_matrix* x,
3893 : ae_int_t n,
3894 : ae_int_t m,
3895 : /* Real */ ae_matrix* c,
3896 : ae_state *_state)
3897 : {
3898 : ae_frame _frame_block;
3899 : ae_vector t;
3900 : ae_int_t i;
3901 : ae_int_t j;
3902 : double v;
3903 :
3904 0 : ae_frame_make(_state, &_frame_block);
3905 0 : memset(&t, 0, sizeof(t));
3906 0 : ae_matrix_clear(c);
3907 0 : ae_vector_init(&t, 0, DT_REAL, _state, ae_true);
3908 :
3909 0 : ae_assert(n>=0, "PearsonCorrM: N<0", _state);
3910 0 : ae_assert(m>=1, "PearsonCorrM: M<1", _state);
3911 0 : ae_assert(x->rows>=n, "PearsonCorrM: Rows(X)<N!", _state);
3912 0 : ae_assert(x->cols>=m||n==0, "PearsonCorrM: Cols(X)<M!", _state);
3913 0 : ae_assert(apservisfinitematrix(x, n, m, _state), "PearsonCorrM: X contains infinite/NAN elements", _state);
3914 0 : ae_vector_set_length(&t, m, _state);
3915 0 : covm(x, n, m, c, _state);
3916 0 : for(i=0; i<=m-1; i++)
3917 : {
3918 0 : if( ae_fp_greater(c->ptr.pp_double[i][i],(double)(0)) )
3919 : {
3920 0 : t.ptr.p_double[i] = 1/ae_sqrt(c->ptr.pp_double[i][i], _state);
3921 : }
3922 : else
3923 : {
3924 0 : t.ptr.p_double[i] = 0.0;
3925 : }
3926 : }
3927 0 : for(i=0; i<=m-1; i++)
3928 : {
3929 0 : v = t.ptr.p_double[i];
3930 0 : for(j=0; j<=m-1; j++)
3931 : {
3932 0 : c->ptr.pp_double[i][j] = c->ptr.pp_double[i][j]*v*t.ptr.p_double[j];
3933 : }
3934 : }
3935 0 : ae_frame_leave(_state);
3936 0 : }
3937 :
3938 :
3939 : /*************************************************************************
3940 : Spearman's rank correlation matrix
3941 :
3942 : ! COMMERCIAL EDITION OF ALGLIB:
3943 : !
3944 : ! Commercial Edition of ALGLIB includes following important improvements
3945 : ! of this function:
3946 : ! * high-performance native backend with same C# interface (C# version)
3947 : ! * multithreading support (C++ and C# versions)
3948 : ! * hardware vendor (Intel) implementations of linear algebra primitives
3949 : ! (C++ and C# versions, x86/x64 platform)
3950 : !
3951 : ! We recommend you to read 'Working with commercial version' section of
3952 : ! ALGLIB Reference Manual in order to find out how to use performance-
3953 : ! related features provided by commercial edition of ALGLIB.
3954 :
3955 : INPUT PARAMETERS:
3956 : X - array[N,M], sample matrix:
3957 : * J-th column corresponds to J-th variable
3958 : * I-th row corresponds to I-th observation
3959 : N - N>=0, number of observations:
3960 : * if given, only leading N rows of X are used
3961 : * if not given, automatically determined from input size
3962 : M - M>0, number of variables:
3963 : * if given, only leading M columns of X are used
3964 : * if not given, automatically determined from input size
3965 :
3966 : OUTPUT PARAMETERS:
3967 : C - array[M,M], correlation matrix (zero if N=0 or N=1)
3968 :
3969 : -- ALGLIB --
3970 : Copyright 28.10.2010 by Bochkanov Sergey
3971 : *************************************************************************/
3972 0 : void spearmancorrm(/* Real */ ae_matrix* x,
3973 : ae_int_t n,
3974 : ae_int_t m,
3975 : /* Real */ ae_matrix* c,
3976 : ae_state *_state)
3977 : {
3978 : ae_frame _frame_block;
3979 : ae_int_t i;
3980 : ae_int_t j;
3981 : apbuffers buf;
3982 : ae_matrix xc;
3983 : ae_vector t;
3984 : double v;
3985 : double vv;
3986 : double x0;
3987 : ae_bool b;
3988 :
3989 0 : ae_frame_make(_state, &_frame_block);
3990 0 : memset(&buf, 0, sizeof(buf));
3991 0 : memset(&xc, 0, sizeof(xc));
3992 0 : memset(&t, 0, sizeof(t));
3993 0 : ae_matrix_clear(c);
3994 0 : _apbuffers_init(&buf, _state, ae_true);
3995 0 : ae_matrix_init(&xc, 0, 0, DT_REAL, _state, ae_true);
3996 0 : ae_vector_init(&t, 0, DT_REAL, _state, ae_true);
3997 :
3998 0 : ae_assert(n>=0, "SpearmanCorrM: N<0", _state);
3999 0 : ae_assert(m>=1, "SpearmanCorrM: M<1", _state);
4000 0 : ae_assert(x->rows>=n, "SpearmanCorrM: Rows(X)<N!", _state);
4001 0 : ae_assert(x->cols>=m||n==0, "SpearmanCorrM: Cols(X)<M!", _state);
4002 0 : ae_assert(apservisfinitematrix(x, n, m, _state), "SpearmanCorrM: X contains infinite/NAN elements", _state);
4003 :
4004 : /*
4005 : * N<=1, return zero
4006 : */
4007 0 : if( n<=1 )
4008 : {
4009 0 : ae_matrix_set_length(c, m, m, _state);
4010 0 : for(i=0; i<=m-1; i++)
4011 : {
4012 0 : for(j=0; j<=m-1; j++)
4013 : {
4014 0 : c->ptr.pp_double[i][j] = (double)(0);
4015 : }
4016 : }
4017 0 : ae_frame_leave(_state);
4018 0 : return;
4019 : }
4020 :
4021 : /*
4022 : * Allocate
4023 : */
4024 0 : ae_vector_set_length(&t, ae_maxint(n, m, _state), _state);
4025 0 : ae_matrix_set_length(c, m, m, _state);
4026 :
4027 : /*
4028 : * Replace data with ranks
4029 : */
4030 0 : ae_matrix_set_length(&xc, m, n, _state);
4031 0 : rmatrixtranspose(n, m, x, 0, 0, &xc, 0, 0, _state);
4032 0 : rankdata(&xc, m, n, _state);
4033 :
4034 : /*
4035 : * 1. Calculate means, check for constant columns
4036 : * 2. Center variables, constant columns are
4037 : * artificialy zeroed (they must be zero in exact arithmetics,
4038 : * but unfortunately floating point is not exact).
4039 : */
4040 0 : for(i=0; i<=m-1; i++)
4041 : {
4042 :
4043 : /*
4044 : * Calculate:
4045 : * * V - mean value of I-th variable
4046 : * * B - True in case all variable values are same
4047 : */
4048 0 : v = (double)(0);
4049 0 : b = ae_true;
4050 0 : x0 = xc.ptr.pp_double[i][0];
4051 0 : for(j=0; j<=n-1; j++)
4052 : {
4053 0 : vv = xc.ptr.pp_double[i][j];
4054 0 : v = v+vv;
4055 0 : b = b&&ae_fp_eq(vv,x0);
4056 : }
4057 0 : v = v/n;
4058 :
4059 : /*
4060 : * Center/zero I-th variable
4061 : */
4062 0 : if( b )
4063 : {
4064 :
4065 : /*
4066 : * Zero
4067 : */
4068 0 : for(j=0; j<=n-1; j++)
4069 : {
4070 0 : xc.ptr.pp_double[i][j] = 0.0;
4071 : }
4072 : }
4073 : else
4074 : {
4075 :
4076 : /*
4077 : * Center
4078 : */
4079 0 : for(j=0; j<=n-1; j++)
4080 : {
4081 0 : xc.ptr.pp_double[i][j] = xc.ptr.pp_double[i][j]-v;
4082 : }
4083 : }
4084 : }
4085 :
4086 : /*
4087 : * Calculate upper half of symmetric covariance matrix
4088 : */
4089 0 : rmatrixsyrk(m, n, (double)1/(double)(n-1), &xc, 0, 0, 0, 0.0, c, 0, 0, ae_true, _state);
4090 :
4091 : /*
4092 : * Calculate Pearson coefficients (upper triangle)
4093 : */
4094 0 : for(i=0; i<=m-1; i++)
4095 : {
4096 0 : if( ae_fp_greater(c->ptr.pp_double[i][i],(double)(0)) )
4097 : {
4098 0 : t.ptr.p_double[i] = 1/ae_sqrt(c->ptr.pp_double[i][i], _state);
4099 : }
4100 : else
4101 : {
4102 0 : t.ptr.p_double[i] = 0.0;
4103 : }
4104 : }
4105 0 : for(i=0; i<=m-1; i++)
4106 : {
4107 0 : v = t.ptr.p_double[i];
4108 0 : for(j=i; j<=m-1; j++)
4109 : {
4110 0 : c->ptr.pp_double[i][j] = c->ptr.pp_double[i][j]*v*t.ptr.p_double[j];
4111 : }
4112 : }
4113 :
4114 : /*
4115 : * force symmetricity
4116 : */
4117 0 : rmatrixenforcesymmetricity(c, m, ae_true, _state);
4118 0 : ae_frame_leave(_state);
4119 : }
4120 :
4121 :
4122 : /*************************************************************************
4123 : Cross-covariance matrix
4124 :
4125 : ! COMMERCIAL EDITION OF ALGLIB:
4126 : !
4127 : ! Commercial Edition of ALGLIB includes following important improvements
4128 : ! of this function:
4129 : ! * high-performance native backend with same C# interface (C# version)
4130 : ! * multithreading support (C++ and C# versions)
4131 : ! * hardware vendor (Intel) implementations of linear algebra primitives
4132 : ! (C++ and C# versions, x86/x64 platform)
4133 : !
4134 : ! We recommend you to read 'Working with commercial version' section of
4135 : ! ALGLIB Reference Manual in order to find out how to use performance-
4136 : ! related features provided by commercial edition of ALGLIB.
4137 :
4138 : INPUT PARAMETERS:
4139 : X - array[N,M1], sample matrix:
4140 : * J-th column corresponds to J-th variable
4141 : * I-th row corresponds to I-th observation
4142 : Y - array[N,M2], sample matrix:
4143 : * J-th column corresponds to J-th variable
4144 : * I-th row corresponds to I-th observation
4145 : N - N>=0, number of observations:
4146 : * if given, only leading N rows of X/Y are used
4147 : * if not given, automatically determined from input sizes
4148 : M1 - M1>0, number of variables in X:
4149 : * if given, only leading M1 columns of X are used
4150 : * if not given, automatically determined from input size
4151 : M2 - M2>0, number of variables in Y:
4152 : * if given, only leading M1 columns of X are used
4153 : * if not given, automatically determined from input size
4154 :
4155 : OUTPUT PARAMETERS:
4156 : C - array[M1,M2], cross-covariance matrix (zero if N=0 or N=1)
4157 :
4158 : -- ALGLIB --
4159 : Copyright 28.10.2010 by Bochkanov Sergey
4160 : *************************************************************************/
4161 0 : void covm2(/* Real */ ae_matrix* x,
4162 : /* Real */ ae_matrix* y,
4163 : ae_int_t n,
4164 : ae_int_t m1,
4165 : ae_int_t m2,
4166 : /* Real */ ae_matrix* c,
4167 : ae_state *_state)
4168 : {
4169 : ae_frame _frame_block;
4170 : ae_matrix _x;
4171 : ae_matrix _y;
4172 : ae_int_t i;
4173 : ae_int_t j;
4174 : double v;
4175 : ae_vector t;
4176 : ae_vector x0;
4177 : ae_vector y0;
4178 : ae_vector samex;
4179 : ae_vector samey;
4180 :
4181 0 : ae_frame_make(_state, &_frame_block);
4182 0 : memset(&_x, 0, sizeof(_x));
4183 0 : memset(&_y, 0, sizeof(_y));
4184 0 : memset(&t, 0, sizeof(t));
4185 0 : memset(&x0, 0, sizeof(x0));
4186 0 : memset(&y0, 0, sizeof(y0));
4187 0 : memset(&samex, 0, sizeof(samex));
4188 0 : memset(&samey, 0, sizeof(samey));
4189 0 : ae_matrix_init_copy(&_x, x, _state, ae_true);
4190 0 : x = &_x;
4191 0 : ae_matrix_init_copy(&_y, y, _state, ae_true);
4192 0 : y = &_y;
4193 0 : ae_matrix_clear(c);
4194 0 : ae_vector_init(&t, 0, DT_REAL, _state, ae_true);
4195 0 : ae_vector_init(&x0, 0, DT_REAL, _state, ae_true);
4196 0 : ae_vector_init(&y0, 0, DT_REAL, _state, ae_true);
4197 0 : ae_vector_init(&samex, 0, DT_BOOL, _state, ae_true);
4198 0 : ae_vector_init(&samey, 0, DT_BOOL, _state, ae_true);
4199 :
4200 0 : ae_assert(n>=0, "CovM2: N<0", _state);
4201 0 : ae_assert(m1>=1, "CovM2: M1<1", _state);
4202 0 : ae_assert(m2>=1, "CovM2: M2<1", _state);
4203 0 : ae_assert(x->rows>=n, "CovM2: Rows(X)<N!", _state);
4204 0 : ae_assert(x->cols>=m1||n==0, "CovM2: Cols(X)<M1!", _state);
4205 0 : ae_assert(apservisfinitematrix(x, n, m1, _state), "CovM2: X contains infinite/NAN elements", _state);
4206 0 : ae_assert(y->rows>=n, "CovM2: Rows(Y)<N!", _state);
4207 0 : ae_assert(y->cols>=m2||n==0, "CovM2: Cols(Y)<M2!", _state);
4208 0 : ae_assert(apservisfinitematrix(y, n, m2, _state), "CovM2: X contains infinite/NAN elements", _state);
4209 :
4210 : /*
4211 : * N<=1, return zero
4212 : */
4213 0 : if( n<=1 )
4214 : {
4215 0 : ae_matrix_set_length(c, m1, m2, _state);
4216 0 : for(i=0; i<=m1-1; i++)
4217 : {
4218 0 : for(j=0; j<=m2-1; j++)
4219 : {
4220 0 : c->ptr.pp_double[i][j] = (double)(0);
4221 : }
4222 : }
4223 0 : ae_frame_leave(_state);
4224 0 : return;
4225 : }
4226 :
4227 : /*
4228 : * Allocate
4229 : */
4230 0 : ae_vector_set_length(&t, ae_maxint(m1, m2, _state), _state);
4231 0 : ae_vector_set_length(&x0, m1, _state);
4232 0 : ae_vector_set_length(&y0, m2, _state);
4233 0 : ae_vector_set_length(&samex, m1, _state);
4234 0 : ae_vector_set_length(&samey, m2, _state);
4235 0 : ae_matrix_set_length(c, m1, m2, _state);
4236 :
4237 : /*
4238 : * * calculate means of X
4239 : * * center X
4240 : * * if we have constant columns, these columns are
4241 : * artificially zeroed (they must be zero in exact arithmetics,
4242 : * but unfortunately floating point ops are not exact).
4243 : */
4244 0 : for(i=0; i<=m1-1; i++)
4245 : {
4246 0 : t.ptr.p_double[i] = (double)(0);
4247 0 : samex.ptr.p_bool[i] = ae_true;
4248 : }
4249 0 : ae_v_move(&x0.ptr.p_double[0], 1, &x->ptr.pp_double[0][0], 1, ae_v_len(0,m1-1));
4250 0 : v = (double)1/(double)n;
4251 0 : for(i=0; i<=n-1; i++)
4252 : {
4253 0 : ae_v_addd(&t.ptr.p_double[0], 1, &x->ptr.pp_double[i][0], 1, ae_v_len(0,m1-1), v);
4254 0 : for(j=0; j<=m1-1; j++)
4255 : {
4256 0 : samex.ptr.p_bool[j] = samex.ptr.p_bool[j]&&ae_fp_eq(x->ptr.pp_double[i][j],x0.ptr.p_double[j]);
4257 : }
4258 : }
4259 0 : for(i=0; i<=n-1; i++)
4260 : {
4261 0 : ae_v_sub(&x->ptr.pp_double[i][0], 1, &t.ptr.p_double[0], 1, ae_v_len(0,m1-1));
4262 0 : for(j=0; j<=m1-1; j++)
4263 : {
4264 0 : if( samex.ptr.p_bool[j] )
4265 : {
4266 0 : x->ptr.pp_double[i][j] = (double)(0);
4267 : }
4268 : }
4269 : }
4270 :
4271 : /*
4272 : * Repeat same steps for Y
4273 : */
4274 0 : for(i=0; i<=m2-1; i++)
4275 : {
4276 0 : t.ptr.p_double[i] = (double)(0);
4277 0 : samey.ptr.p_bool[i] = ae_true;
4278 : }
4279 0 : ae_v_move(&y0.ptr.p_double[0], 1, &y->ptr.pp_double[0][0], 1, ae_v_len(0,m2-1));
4280 0 : v = (double)1/(double)n;
4281 0 : for(i=0; i<=n-1; i++)
4282 : {
4283 0 : ae_v_addd(&t.ptr.p_double[0], 1, &y->ptr.pp_double[i][0], 1, ae_v_len(0,m2-1), v);
4284 0 : for(j=0; j<=m2-1; j++)
4285 : {
4286 0 : samey.ptr.p_bool[j] = samey.ptr.p_bool[j]&&ae_fp_eq(y->ptr.pp_double[i][j],y0.ptr.p_double[j]);
4287 : }
4288 : }
4289 0 : for(i=0; i<=n-1; i++)
4290 : {
4291 0 : ae_v_sub(&y->ptr.pp_double[i][0], 1, &t.ptr.p_double[0], 1, ae_v_len(0,m2-1));
4292 0 : for(j=0; j<=m2-1; j++)
4293 : {
4294 0 : if( samey.ptr.p_bool[j] )
4295 : {
4296 0 : y->ptr.pp_double[i][j] = (double)(0);
4297 : }
4298 : }
4299 : }
4300 :
4301 : /*
4302 : * calculate cross-covariance matrix
4303 : */
4304 0 : rmatrixgemm(m1, m2, n, (double)1/(double)(n-1), x, 0, 0, 1, y, 0, 0, 0, 0.0, c, 0, 0, _state);
4305 0 : ae_frame_leave(_state);
4306 : }
4307 :
4308 :
4309 : /*************************************************************************
4310 : Pearson product-moment cross-correlation matrix
4311 :
4312 : ! COMMERCIAL EDITION OF ALGLIB:
4313 : !
4314 : ! Commercial Edition of ALGLIB includes following important improvements
4315 : ! of this function:
4316 : ! * high-performance native backend with same C# interface (C# version)
4317 : ! * multithreading support (C++ and C# versions)
4318 : ! * hardware vendor (Intel) implementations of linear algebra primitives
4319 : ! (C++ and C# versions, x86/x64 platform)
4320 : !
4321 : ! We recommend you to read 'Working with commercial version' section of
4322 : ! ALGLIB Reference Manual in order to find out how to use performance-
4323 : ! related features provided by commercial edition of ALGLIB.
4324 :
4325 : INPUT PARAMETERS:
4326 : X - array[N,M1], sample matrix:
4327 : * J-th column corresponds to J-th variable
4328 : * I-th row corresponds to I-th observation
4329 : Y - array[N,M2], sample matrix:
4330 : * J-th column corresponds to J-th variable
4331 : * I-th row corresponds to I-th observation
4332 : N - N>=0, number of observations:
4333 : * if given, only leading N rows of X/Y are used
4334 : * if not given, automatically determined from input sizes
4335 : M1 - M1>0, number of variables in X:
4336 : * if given, only leading M1 columns of X are used
4337 : * if not given, automatically determined from input size
4338 : M2 - M2>0, number of variables in Y:
4339 : * if given, only leading M1 columns of X are used
4340 : * if not given, automatically determined from input size
4341 :
4342 : OUTPUT PARAMETERS:
4343 : C - array[M1,M2], cross-correlation matrix (zero if N=0 or N=1)
4344 :
4345 : -- ALGLIB --
4346 : Copyright 28.10.2010 by Bochkanov Sergey
4347 : *************************************************************************/
4348 0 : void pearsoncorrm2(/* Real */ ae_matrix* x,
4349 : /* Real */ ae_matrix* y,
4350 : ae_int_t n,
4351 : ae_int_t m1,
4352 : ae_int_t m2,
4353 : /* Real */ ae_matrix* c,
4354 : ae_state *_state)
4355 : {
4356 : ae_frame _frame_block;
4357 : ae_matrix _x;
4358 : ae_matrix _y;
4359 : ae_int_t i;
4360 : ae_int_t j;
4361 : double v;
4362 : ae_vector t;
4363 : ae_vector x0;
4364 : ae_vector y0;
4365 : ae_vector sx;
4366 : ae_vector sy;
4367 : ae_vector samex;
4368 : ae_vector samey;
4369 :
4370 0 : ae_frame_make(_state, &_frame_block);
4371 0 : memset(&_x, 0, sizeof(_x));
4372 0 : memset(&_y, 0, sizeof(_y));
4373 0 : memset(&t, 0, sizeof(t));
4374 0 : memset(&x0, 0, sizeof(x0));
4375 0 : memset(&y0, 0, sizeof(y0));
4376 0 : memset(&sx, 0, sizeof(sx));
4377 0 : memset(&sy, 0, sizeof(sy));
4378 0 : memset(&samex, 0, sizeof(samex));
4379 0 : memset(&samey, 0, sizeof(samey));
4380 0 : ae_matrix_init_copy(&_x, x, _state, ae_true);
4381 0 : x = &_x;
4382 0 : ae_matrix_init_copy(&_y, y, _state, ae_true);
4383 0 : y = &_y;
4384 0 : ae_matrix_clear(c);
4385 0 : ae_vector_init(&t, 0, DT_REAL, _state, ae_true);
4386 0 : ae_vector_init(&x0, 0, DT_REAL, _state, ae_true);
4387 0 : ae_vector_init(&y0, 0, DT_REAL, _state, ae_true);
4388 0 : ae_vector_init(&sx, 0, DT_REAL, _state, ae_true);
4389 0 : ae_vector_init(&sy, 0, DT_REAL, _state, ae_true);
4390 0 : ae_vector_init(&samex, 0, DT_BOOL, _state, ae_true);
4391 0 : ae_vector_init(&samey, 0, DT_BOOL, _state, ae_true);
4392 :
4393 0 : ae_assert(n>=0, "PearsonCorrM2: N<0", _state);
4394 0 : ae_assert(m1>=1, "PearsonCorrM2: M1<1", _state);
4395 0 : ae_assert(m2>=1, "PearsonCorrM2: M2<1", _state);
4396 0 : ae_assert(x->rows>=n, "PearsonCorrM2: Rows(X)<N!", _state);
4397 0 : ae_assert(x->cols>=m1||n==0, "PearsonCorrM2: Cols(X)<M1!", _state);
4398 0 : ae_assert(apservisfinitematrix(x, n, m1, _state), "PearsonCorrM2: X contains infinite/NAN elements", _state);
4399 0 : ae_assert(y->rows>=n, "PearsonCorrM2: Rows(Y)<N!", _state);
4400 0 : ae_assert(y->cols>=m2||n==0, "PearsonCorrM2: Cols(Y)<M2!", _state);
4401 0 : ae_assert(apservisfinitematrix(y, n, m2, _state), "PearsonCorrM2: X contains infinite/NAN elements", _state);
4402 :
4403 : /*
4404 : * N<=1, return zero
4405 : */
4406 0 : if( n<=1 )
4407 : {
4408 0 : ae_matrix_set_length(c, m1, m2, _state);
4409 0 : for(i=0; i<=m1-1; i++)
4410 : {
4411 0 : for(j=0; j<=m2-1; j++)
4412 : {
4413 0 : c->ptr.pp_double[i][j] = (double)(0);
4414 : }
4415 : }
4416 0 : ae_frame_leave(_state);
4417 0 : return;
4418 : }
4419 :
4420 : /*
4421 : * Allocate
4422 : */
4423 0 : ae_vector_set_length(&t, ae_maxint(m1, m2, _state), _state);
4424 0 : ae_vector_set_length(&x0, m1, _state);
4425 0 : ae_vector_set_length(&y0, m2, _state);
4426 0 : ae_vector_set_length(&sx, m1, _state);
4427 0 : ae_vector_set_length(&sy, m2, _state);
4428 0 : ae_vector_set_length(&samex, m1, _state);
4429 0 : ae_vector_set_length(&samey, m2, _state);
4430 0 : ae_matrix_set_length(c, m1, m2, _state);
4431 :
4432 : /*
4433 : * * calculate means of X
4434 : * * center X
4435 : * * if we have constant columns, these columns are
4436 : * artificially zeroed (they must be zero in exact arithmetics,
4437 : * but unfortunately floating point ops are not exact).
4438 : * * calculate column variances
4439 : */
4440 0 : for(i=0; i<=m1-1; i++)
4441 : {
4442 0 : t.ptr.p_double[i] = (double)(0);
4443 0 : samex.ptr.p_bool[i] = ae_true;
4444 0 : sx.ptr.p_double[i] = (double)(0);
4445 : }
4446 0 : ae_v_move(&x0.ptr.p_double[0], 1, &x->ptr.pp_double[0][0], 1, ae_v_len(0,m1-1));
4447 0 : v = (double)1/(double)n;
4448 0 : for(i=0; i<=n-1; i++)
4449 : {
4450 0 : ae_v_addd(&t.ptr.p_double[0], 1, &x->ptr.pp_double[i][0], 1, ae_v_len(0,m1-1), v);
4451 0 : for(j=0; j<=m1-1; j++)
4452 : {
4453 0 : samex.ptr.p_bool[j] = samex.ptr.p_bool[j]&&ae_fp_eq(x->ptr.pp_double[i][j],x0.ptr.p_double[j]);
4454 : }
4455 : }
4456 0 : for(i=0; i<=n-1; i++)
4457 : {
4458 0 : ae_v_sub(&x->ptr.pp_double[i][0], 1, &t.ptr.p_double[0], 1, ae_v_len(0,m1-1));
4459 0 : for(j=0; j<=m1-1; j++)
4460 : {
4461 0 : if( samex.ptr.p_bool[j] )
4462 : {
4463 0 : x->ptr.pp_double[i][j] = (double)(0);
4464 : }
4465 0 : sx.ptr.p_double[j] = sx.ptr.p_double[j]+x->ptr.pp_double[i][j]*x->ptr.pp_double[i][j];
4466 : }
4467 : }
4468 0 : for(j=0; j<=m1-1; j++)
4469 : {
4470 0 : sx.ptr.p_double[j] = ae_sqrt(sx.ptr.p_double[j]/(n-1), _state);
4471 : }
4472 :
4473 : /*
4474 : * Repeat same steps for Y
4475 : */
4476 0 : for(i=0; i<=m2-1; i++)
4477 : {
4478 0 : t.ptr.p_double[i] = (double)(0);
4479 0 : samey.ptr.p_bool[i] = ae_true;
4480 0 : sy.ptr.p_double[i] = (double)(0);
4481 : }
4482 0 : ae_v_move(&y0.ptr.p_double[0], 1, &y->ptr.pp_double[0][0], 1, ae_v_len(0,m2-1));
4483 0 : v = (double)1/(double)n;
4484 0 : for(i=0; i<=n-1; i++)
4485 : {
4486 0 : ae_v_addd(&t.ptr.p_double[0], 1, &y->ptr.pp_double[i][0], 1, ae_v_len(0,m2-1), v);
4487 0 : for(j=0; j<=m2-1; j++)
4488 : {
4489 0 : samey.ptr.p_bool[j] = samey.ptr.p_bool[j]&&ae_fp_eq(y->ptr.pp_double[i][j],y0.ptr.p_double[j]);
4490 : }
4491 : }
4492 0 : for(i=0; i<=n-1; i++)
4493 : {
4494 0 : ae_v_sub(&y->ptr.pp_double[i][0], 1, &t.ptr.p_double[0], 1, ae_v_len(0,m2-1));
4495 0 : for(j=0; j<=m2-1; j++)
4496 : {
4497 0 : if( samey.ptr.p_bool[j] )
4498 : {
4499 0 : y->ptr.pp_double[i][j] = (double)(0);
4500 : }
4501 0 : sy.ptr.p_double[j] = sy.ptr.p_double[j]+y->ptr.pp_double[i][j]*y->ptr.pp_double[i][j];
4502 : }
4503 : }
4504 0 : for(j=0; j<=m2-1; j++)
4505 : {
4506 0 : sy.ptr.p_double[j] = ae_sqrt(sy.ptr.p_double[j]/(n-1), _state);
4507 : }
4508 :
4509 : /*
4510 : * calculate cross-covariance matrix
4511 : */
4512 0 : rmatrixgemm(m1, m2, n, (double)1/(double)(n-1), x, 0, 0, 1, y, 0, 0, 0, 0.0, c, 0, 0, _state);
4513 :
4514 : /*
4515 : * Divide by standard deviations
4516 : */
4517 0 : for(i=0; i<=m1-1; i++)
4518 : {
4519 0 : if( ae_fp_neq(sx.ptr.p_double[i],(double)(0)) )
4520 : {
4521 0 : sx.ptr.p_double[i] = 1/sx.ptr.p_double[i];
4522 : }
4523 : else
4524 : {
4525 0 : sx.ptr.p_double[i] = 0.0;
4526 : }
4527 : }
4528 0 : for(i=0; i<=m2-1; i++)
4529 : {
4530 0 : if( ae_fp_neq(sy.ptr.p_double[i],(double)(0)) )
4531 : {
4532 0 : sy.ptr.p_double[i] = 1/sy.ptr.p_double[i];
4533 : }
4534 : else
4535 : {
4536 0 : sy.ptr.p_double[i] = 0.0;
4537 : }
4538 : }
4539 0 : for(i=0; i<=m1-1; i++)
4540 : {
4541 0 : v = sx.ptr.p_double[i];
4542 0 : for(j=0; j<=m2-1; j++)
4543 : {
4544 0 : c->ptr.pp_double[i][j] = c->ptr.pp_double[i][j]*v*sy.ptr.p_double[j];
4545 : }
4546 : }
4547 0 : ae_frame_leave(_state);
4548 : }
4549 :
4550 :
4551 : /*************************************************************************
4552 : Spearman's rank cross-correlation matrix
4553 :
4554 : ! COMMERCIAL EDITION OF ALGLIB:
4555 : !
4556 : ! Commercial Edition of ALGLIB includes following important improvements
4557 : ! of this function:
4558 : ! * high-performance native backend with same C# interface (C# version)
4559 : ! * multithreading support (C++ and C# versions)
4560 : ! * hardware vendor (Intel) implementations of linear algebra primitives
4561 : ! (C++ and C# versions, x86/x64 platform)
4562 : !
4563 : ! We recommend you to read 'Working with commercial version' section of
4564 : ! ALGLIB Reference Manual in order to find out how to use performance-
4565 : ! related features provided by commercial edition of ALGLIB.
4566 :
4567 : INPUT PARAMETERS:
4568 : X - array[N,M1], sample matrix:
4569 : * J-th column corresponds to J-th variable
4570 : * I-th row corresponds to I-th observation
4571 : Y - array[N,M2], sample matrix:
4572 : * J-th column corresponds to J-th variable
4573 : * I-th row corresponds to I-th observation
4574 : N - N>=0, number of observations:
4575 : * if given, only leading N rows of X/Y are used
4576 : * if not given, automatically determined from input sizes
4577 : M1 - M1>0, number of variables in X:
4578 : * if given, only leading M1 columns of X are used
4579 : * if not given, automatically determined from input size
4580 : M2 - M2>0, number of variables in Y:
4581 : * if given, only leading M1 columns of X are used
4582 : * if not given, automatically determined from input size
4583 :
4584 : OUTPUT PARAMETERS:
4585 : C - array[M1,M2], cross-correlation matrix (zero if N=0 or N=1)
4586 :
4587 : -- ALGLIB --
4588 : Copyright 28.10.2010 by Bochkanov Sergey
4589 : *************************************************************************/
4590 0 : void spearmancorrm2(/* Real */ ae_matrix* x,
4591 : /* Real */ ae_matrix* y,
4592 : ae_int_t n,
4593 : ae_int_t m1,
4594 : ae_int_t m2,
4595 : /* Real */ ae_matrix* c,
4596 : ae_state *_state)
4597 : {
4598 : ae_frame _frame_block;
4599 : ae_int_t i;
4600 : ae_int_t j;
4601 : double v;
4602 : double v2;
4603 : double vv;
4604 : ae_bool b;
4605 : ae_vector t;
4606 : double x0;
4607 : double y0;
4608 : ae_vector sx;
4609 : ae_vector sy;
4610 : ae_matrix xc;
4611 : ae_matrix yc;
4612 : apbuffers buf;
4613 :
4614 0 : ae_frame_make(_state, &_frame_block);
4615 0 : memset(&t, 0, sizeof(t));
4616 0 : memset(&sx, 0, sizeof(sx));
4617 0 : memset(&sy, 0, sizeof(sy));
4618 0 : memset(&xc, 0, sizeof(xc));
4619 0 : memset(&yc, 0, sizeof(yc));
4620 0 : memset(&buf, 0, sizeof(buf));
4621 0 : ae_matrix_clear(c);
4622 0 : ae_vector_init(&t, 0, DT_REAL, _state, ae_true);
4623 0 : ae_vector_init(&sx, 0, DT_REAL, _state, ae_true);
4624 0 : ae_vector_init(&sy, 0, DT_REAL, _state, ae_true);
4625 0 : ae_matrix_init(&xc, 0, 0, DT_REAL, _state, ae_true);
4626 0 : ae_matrix_init(&yc, 0, 0, DT_REAL, _state, ae_true);
4627 0 : _apbuffers_init(&buf, _state, ae_true);
4628 :
4629 0 : ae_assert(n>=0, "SpearmanCorrM2: N<0", _state);
4630 0 : ae_assert(m1>=1, "SpearmanCorrM2: M1<1", _state);
4631 0 : ae_assert(m2>=1, "SpearmanCorrM2: M2<1", _state);
4632 0 : ae_assert(x->rows>=n, "SpearmanCorrM2: Rows(X)<N!", _state);
4633 0 : ae_assert(x->cols>=m1||n==0, "SpearmanCorrM2: Cols(X)<M1!", _state);
4634 0 : ae_assert(apservisfinitematrix(x, n, m1, _state), "SpearmanCorrM2: X contains infinite/NAN elements", _state);
4635 0 : ae_assert(y->rows>=n, "SpearmanCorrM2: Rows(Y)<N!", _state);
4636 0 : ae_assert(y->cols>=m2||n==0, "SpearmanCorrM2: Cols(Y)<M2!", _state);
4637 0 : ae_assert(apservisfinitematrix(y, n, m2, _state), "SpearmanCorrM2: X contains infinite/NAN elements", _state);
4638 :
4639 : /*
4640 : * N<=1, return zero
4641 : */
4642 0 : if( n<=1 )
4643 : {
4644 0 : ae_matrix_set_length(c, m1, m2, _state);
4645 0 : for(i=0; i<=m1-1; i++)
4646 : {
4647 0 : for(j=0; j<=m2-1; j++)
4648 : {
4649 0 : c->ptr.pp_double[i][j] = (double)(0);
4650 : }
4651 : }
4652 0 : ae_frame_leave(_state);
4653 0 : return;
4654 : }
4655 :
4656 : /*
4657 : * Allocate
4658 : */
4659 0 : ae_vector_set_length(&t, ae_maxint(ae_maxint(m1, m2, _state), n, _state), _state);
4660 0 : ae_vector_set_length(&sx, m1, _state);
4661 0 : ae_vector_set_length(&sy, m2, _state);
4662 0 : ae_matrix_set_length(c, m1, m2, _state);
4663 :
4664 : /*
4665 : * Replace data with ranks
4666 : */
4667 0 : ae_matrix_set_length(&xc, m1, n, _state);
4668 0 : ae_matrix_set_length(&yc, m2, n, _state);
4669 0 : rmatrixtranspose(n, m1, x, 0, 0, &xc, 0, 0, _state);
4670 0 : rmatrixtranspose(n, m2, y, 0, 0, &yc, 0, 0, _state);
4671 0 : rankdata(&xc, m1, n, _state);
4672 0 : rankdata(&yc, m2, n, _state);
4673 :
4674 : /*
4675 : * 1. Calculate means, variances, check for constant columns
4676 : * 2. Center variables, constant columns are
4677 : * artificialy zeroed (they must be zero in exact arithmetics,
4678 : * but unfortunately floating point is not exact).
4679 : *
4680 : * Description of variables:
4681 : * * V - mean value of I-th variable
4682 : * * V2- variance
4683 : * * VV-temporary
4684 : * * B - True in case all variable values are same
4685 : */
4686 0 : for(i=0; i<=m1-1; i++)
4687 : {
4688 0 : v = (double)(0);
4689 0 : v2 = 0.0;
4690 0 : b = ae_true;
4691 0 : x0 = xc.ptr.pp_double[i][0];
4692 0 : for(j=0; j<=n-1; j++)
4693 : {
4694 0 : vv = xc.ptr.pp_double[i][j];
4695 0 : v = v+vv;
4696 0 : b = b&&ae_fp_eq(vv,x0);
4697 : }
4698 0 : v = v/n;
4699 0 : if( b )
4700 : {
4701 0 : for(j=0; j<=n-1; j++)
4702 : {
4703 0 : xc.ptr.pp_double[i][j] = 0.0;
4704 : }
4705 : }
4706 : else
4707 : {
4708 0 : for(j=0; j<=n-1; j++)
4709 : {
4710 0 : vv = xc.ptr.pp_double[i][j];
4711 0 : xc.ptr.pp_double[i][j] = vv-v;
4712 0 : v2 = v2+(vv-v)*(vv-v);
4713 : }
4714 : }
4715 0 : sx.ptr.p_double[i] = ae_sqrt(v2/(n-1), _state);
4716 : }
4717 0 : for(i=0; i<=m2-1; i++)
4718 : {
4719 0 : v = (double)(0);
4720 0 : v2 = 0.0;
4721 0 : b = ae_true;
4722 0 : y0 = yc.ptr.pp_double[i][0];
4723 0 : for(j=0; j<=n-1; j++)
4724 : {
4725 0 : vv = yc.ptr.pp_double[i][j];
4726 0 : v = v+vv;
4727 0 : b = b&&ae_fp_eq(vv,y0);
4728 : }
4729 0 : v = v/n;
4730 0 : if( b )
4731 : {
4732 0 : for(j=0; j<=n-1; j++)
4733 : {
4734 0 : yc.ptr.pp_double[i][j] = 0.0;
4735 : }
4736 : }
4737 : else
4738 : {
4739 0 : for(j=0; j<=n-1; j++)
4740 : {
4741 0 : vv = yc.ptr.pp_double[i][j];
4742 0 : yc.ptr.pp_double[i][j] = vv-v;
4743 0 : v2 = v2+(vv-v)*(vv-v);
4744 : }
4745 : }
4746 0 : sy.ptr.p_double[i] = ae_sqrt(v2/(n-1), _state);
4747 : }
4748 :
4749 : /*
4750 : * calculate cross-covariance matrix
4751 : */
4752 0 : rmatrixgemm(m1, m2, n, (double)1/(double)(n-1), &xc, 0, 0, 0, &yc, 0, 0, 1, 0.0, c, 0, 0, _state);
4753 :
4754 : /*
4755 : * Divide by standard deviations
4756 : */
4757 0 : for(i=0; i<=m1-1; i++)
4758 : {
4759 0 : if( ae_fp_neq(sx.ptr.p_double[i],(double)(0)) )
4760 : {
4761 0 : sx.ptr.p_double[i] = 1/sx.ptr.p_double[i];
4762 : }
4763 : else
4764 : {
4765 0 : sx.ptr.p_double[i] = 0.0;
4766 : }
4767 : }
4768 0 : for(i=0; i<=m2-1; i++)
4769 : {
4770 0 : if( ae_fp_neq(sy.ptr.p_double[i],(double)(0)) )
4771 : {
4772 0 : sy.ptr.p_double[i] = 1/sy.ptr.p_double[i];
4773 : }
4774 : else
4775 : {
4776 0 : sy.ptr.p_double[i] = 0.0;
4777 : }
4778 : }
4779 0 : for(i=0; i<=m1-1; i++)
4780 : {
4781 0 : v = sx.ptr.p_double[i];
4782 0 : for(j=0; j<=m2-1; j++)
4783 : {
4784 0 : c->ptr.pp_double[i][j] = c->ptr.pp_double[i][j]*v*sy.ptr.p_double[j];
4785 : }
4786 : }
4787 0 : ae_frame_leave(_state);
4788 : }
4789 :
4790 :
4791 : /*************************************************************************
4792 : This function replaces data in XY by their ranks:
4793 : * XY is processed row-by-row
4794 : * rows are processed separately
4795 : * tied data are correctly handled (tied ranks are calculated)
4796 : * ranking starts from 0, ends at NFeatures-1
4797 : * sum of within-row values is equal to (NFeatures-1)*NFeatures/2
4798 :
4799 : ! COMMERCIAL EDITION OF ALGLIB:
4800 : !
4801 : ! Commercial Edition of ALGLIB includes following important improvements
4802 : ! of this function:
4803 : ! * high-performance native backend with same C# interface (C# version)
4804 : ! * multithreading support (C++ and C# versions)
4805 : !
4806 : ! We recommend you to read 'Working with commercial version' section of
4807 : ! ALGLIB Reference Manual in order to find out how to use performance-
4808 : ! related features provided by commercial edition of ALGLIB.
4809 :
4810 : INPUT PARAMETERS:
4811 : XY - array[NPoints,NFeatures], dataset
4812 : NPoints - number of points
4813 : NFeatures- number of features
4814 :
4815 : OUTPUT PARAMETERS:
4816 : XY - data are replaced by their within-row ranks;
4817 : ranking starts from 0, ends at NFeatures-1
4818 :
4819 : -- ALGLIB --
4820 : Copyright 18.04.2013 by Bochkanov Sergey
4821 : *************************************************************************/
4822 0 : void rankdata(/* Real */ ae_matrix* xy,
4823 : ae_int_t npoints,
4824 : ae_int_t nfeatures,
4825 : ae_state *_state)
4826 : {
4827 : ae_frame _frame_block;
4828 : apbuffers buf0;
4829 : apbuffers buf1;
4830 : ae_int_t basecasecost;
4831 : ae_shared_pool pool;
4832 :
4833 0 : ae_frame_make(_state, &_frame_block);
4834 0 : memset(&buf0, 0, sizeof(buf0));
4835 0 : memset(&buf1, 0, sizeof(buf1));
4836 0 : memset(&pool, 0, sizeof(pool));
4837 0 : _apbuffers_init(&buf0, _state, ae_true);
4838 0 : _apbuffers_init(&buf1, _state, ae_true);
4839 0 : ae_shared_pool_init(&pool, _state, ae_true);
4840 :
4841 0 : ae_assert(npoints>=0, "RankData: NPoints<0", _state);
4842 0 : ae_assert(nfeatures>=1, "RankData: NFeatures<1", _state);
4843 0 : ae_assert(xy->rows>=npoints, "RankData: Rows(XY)<NPoints", _state);
4844 0 : ae_assert(xy->cols>=nfeatures||npoints==0, "RankData: Cols(XY)<NFeatures", _state);
4845 0 : ae_assert(apservisfinitematrix(xy, npoints, nfeatures, _state), "RankData: XY contains infinite/NAN elements", _state);
4846 :
4847 : /*
4848 : * Basecase cost is a maximum cost of basecase problems.
4849 : * Problems harded than that cost will be split.
4850 : *
4851 : * Problem cost is assumed to be NPoints*NFeatures*log2(NFeatures),
4852 : * which is proportional, but NOT equal to number of FLOPs required
4853 : * to solve problem.
4854 : *
4855 : * Try to use serial code for basecase problems, no SMP functionality, no shared pools.
4856 : */
4857 0 : basecasecost = 10000;
4858 0 : if( ae_fp_less(rmul3((double)(npoints), (double)(nfeatures), logbase2((double)(nfeatures), _state), _state),(double)(basecasecost)) )
4859 : {
4860 0 : basestat_rankdatabasecase(xy, 0, npoints, nfeatures, ae_false, &buf0, &buf1, _state);
4861 0 : ae_frame_leave(_state);
4862 0 : return;
4863 : }
4864 :
4865 : /*
4866 : * Parallel code
4867 : */
4868 0 : ae_shared_pool_set_seed(&pool, &buf0, sizeof(buf0), _apbuffers_init, _apbuffers_init_copy, _apbuffers_destroy, _state);
4869 0 : basestat_rankdatarec(xy, 0, npoints, nfeatures, ae_false, &pool, basecasecost, _state);
4870 0 : ae_frame_leave(_state);
4871 : }
4872 :
4873 :
4874 : /*************************************************************************
4875 : Serial stub for GPL edition.
4876 : *************************************************************************/
4877 0 : ae_bool _trypexec_rankdata(/* Real */ ae_matrix* xy,
4878 : ae_int_t npoints,
4879 : ae_int_t nfeatures,
4880 : ae_state *_state)
4881 : {
4882 0 : return ae_false;
4883 : }
4884 :
4885 :
4886 : /*************************************************************************
4887 : This function replaces data in XY by their CENTERED ranks:
4888 : * XY is processed row-by-row
4889 : * rows are processed separately
4890 : * tied data are correctly handled (tied ranks are calculated)
4891 : * centered ranks are just usual ranks, but centered in such way that sum
4892 : of within-row values is equal to 0.0.
4893 : * centering is performed by subtracting mean from each row, i.e it changes
4894 : mean value, but does NOT change higher moments
4895 :
4896 : ! COMMERCIAL EDITION OF ALGLIB:
4897 : !
4898 : ! Commercial Edition of ALGLIB includes following important improvements
4899 : ! of this function:
4900 : ! * high-performance native backend with same C# interface (C# version)
4901 : ! * multithreading support (C++ and C# versions)
4902 : !
4903 : ! We recommend you to read 'Working with commercial version' section of
4904 : ! ALGLIB Reference Manual in order to find out how to use performance-
4905 : ! related features provided by commercial edition of ALGLIB.
4906 :
4907 : INPUT PARAMETERS:
4908 : XY - array[NPoints,NFeatures], dataset
4909 : NPoints - number of points
4910 : NFeatures- number of features
4911 :
4912 : OUTPUT PARAMETERS:
4913 : XY - data are replaced by their within-row ranks;
4914 : ranking starts from 0, ends at NFeatures-1
4915 :
4916 : -- ALGLIB --
4917 : Copyright 18.04.2013 by Bochkanov Sergey
4918 : *************************************************************************/
4919 0 : void rankdatacentered(/* Real */ ae_matrix* xy,
4920 : ae_int_t npoints,
4921 : ae_int_t nfeatures,
4922 : ae_state *_state)
4923 : {
4924 : ae_frame _frame_block;
4925 : apbuffers buf0;
4926 : apbuffers buf1;
4927 : ae_int_t basecasecost;
4928 : ae_shared_pool pool;
4929 :
4930 0 : ae_frame_make(_state, &_frame_block);
4931 0 : memset(&buf0, 0, sizeof(buf0));
4932 0 : memset(&buf1, 0, sizeof(buf1));
4933 0 : memset(&pool, 0, sizeof(pool));
4934 0 : _apbuffers_init(&buf0, _state, ae_true);
4935 0 : _apbuffers_init(&buf1, _state, ae_true);
4936 0 : ae_shared_pool_init(&pool, _state, ae_true);
4937 :
4938 0 : ae_assert(npoints>=0, "RankData: NPoints<0", _state);
4939 0 : ae_assert(nfeatures>=1, "RankData: NFeatures<1", _state);
4940 0 : ae_assert(xy->rows>=npoints, "RankData: Rows(XY)<NPoints", _state);
4941 0 : ae_assert(xy->cols>=nfeatures||npoints==0, "RankData: Cols(XY)<NFeatures", _state);
4942 0 : ae_assert(apservisfinitematrix(xy, npoints, nfeatures, _state), "RankData: XY contains infinite/NAN elements", _state);
4943 :
4944 : /*
4945 : * Basecase cost is a maximum cost of basecase problems.
4946 : * Problems harded than that cost will be split.
4947 : *
4948 : * Problem cost is assumed to be NPoints*NFeatures*log2(NFeatures),
4949 : * which is proportional, but NOT equal to number of FLOPs required
4950 : * to solve problem.
4951 : *
4952 : * Try to use serial code, no SMP functionality, no shared pools.
4953 : */
4954 0 : basecasecost = 10000;
4955 0 : if( ae_fp_less(rmul3((double)(npoints), (double)(nfeatures), logbase2((double)(nfeatures), _state), _state),(double)(basecasecost)) )
4956 : {
4957 0 : basestat_rankdatabasecase(xy, 0, npoints, nfeatures, ae_true, &buf0, &buf1, _state);
4958 0 : ae_frame_leave(_state);
4959 0 : return;
4960 : }
4961 :
4962 : /*
4963 : * Parallel code
4964 : */
4965 0 : ae_shared_pool_set_seed(&pool, &buf0, sizeof(buf0), _apbuffers_init, _apbuffers_init_copy, _apbuffers_destroy, _state);
4966 0 : basestat_rankdatarec(xy, 0, npoints, nfeatures, ae_true, &pool, basecasecost, _state);
4967 0 : ae_frame_leave(_state);
4968 : }
4969 :
4970 :
4971 : /*************************************************************************
4972 : Serial stub for GPL edition.
4973 : *************************************************************************/
4974 0 : ae_bool _trypexec_rankdatacentered(/* Real */ ae_matrix* xy,
4975 : ae_int_t npoints,
4976 : ae_int_t nfeatures,
4977 : ae_state *_state)
4978 : {
4979 0 : return ae_false;
4980 : }
4981 :
4982 :
4983 : /*************************************************************************
4984 : Obsolete function, we recommend to use PearsonCorr2().
4985 :
4986 : -- ALGLIB --
4987 : Copyright 09.04.2007 by Bochkanov Sergey
4988 : *************************************************************************/
4989 0 : double pearsoncorrelation(/* Real */ ae_vector* x,
4990 : /* Real */ ae_vector* y,
4991 : ae_int_t n,
4992 : ae_state *_state)
4993 : {
4994 : double result;
4995 :
4996 :
4997 0 : result = pearsoncorr2(x, y, n, _state);
4998 0 : return result;
4999 : }
5000 :
5001 :
5002 : /*************************************************************************
5003 : Obsolete function, we recommend to use SpearmanCorr2().
5004 :
5005 : -- ALGLIB --
5006 : Copyright 09.04.2007 by Bochkanov Sergey
5007 : *************************************************************************/
5008 0 : double spearmanrankcorrelation(/* Real */ ae_vector* x,
5009 : /* Real */ ae_vector* y,
5010 : ae_int_t n,
5011 : ae_state *_state)
5012 : {
5013 : double result;
5014 :
5015 :
5016 0 : result = spearmancorr2(x, y, n, _state);
5017 0 : return result;
5018 : }
5019 :
5020 :
5021 : /*************************************************************************
5022 : Recurrent code for RankData(), splits problem into subproblems or calls
5023 : basecase code (depending on problem complexity).
5024 :
5025 : INPUT PARAMETERS:
5026 : XY - array[NPoints,NFeatures], dataset
5027 : I0 - index of first row to process
5028 : I1 - index of past-the-last row to process;
5029 : this function processes half-interval [I0,I1).
5030 : NFeatures- number of features
5031 : IsCentered- whether ranks are centered or not:
5032 : * True - ranks are centered in such way that their
5033 : within-row sum is zero
5034 : * False - ranks are not centered
5035 : Pool - shared pool which holds temporary buffers
5036 : (APBuffers structure)
5037 : BasecaseCost-minimum cost of the problem which will be split
5038 :
5039 : OUTPUT PARAMETERS:
5040 : XY - data in [I0,I1) are replaced by their within-row ranks;
5041 : ranking starts from 0, ends at NFeatures-1
5042 :
5043 : -- ALGLIB --
5044 : Copyright 18.04.2013 by Bochkanov Sergey
5045 : *************************************************************************/
5046 0 : static void basestat_rankdatarec(/* Real */ ae_matrix* xy,
5047 : ae_int_t i0,
5048 : ae_int_t i1,
5049 : ae_int_t nfeatures,
5050 : ae_bool iscentered,
5051 : ae_shared_pool* pool,
5052 : ae_int_t basecasecost,
5053 : ae_state *_state)
5054 : {
5055 : ae_frame _frame_block;
5056 : apbuffers *buf0;
5057 : ae_smart_ptr _buf0;
5058 : apbuffers *buf1;
5059 : ae_smart_ptr _buf1;
5060 : double problemcost;
5061 : ae_int_t im;
5062 :
5063 0 : ae_frame_make(_state, &_frame_block);
5064 0 : memset(&_buf0, 0, sizeof(_buf0));
5065 0 : memset(&_buf1, 0, sizeof(_buf1));
5066 0 : ae_smart_ptr_init(&_buf0, (void**)&buf0, _state, ae_true);
5067 0 : ae_smart_ptr_init(&_buf1, (void**)&buf1, _state, ae_true);
5068 :
5069 0 : ae_assert(i1>=i0, "RankDataRec: internal error", _state);
5070 :
5071 : /*
5072 : * Try to activate parallelism
5073 : */
5074 0 : if( i1-i0>=4&&ae_fp_greater_eq(rmul3((double)(i1-i0), (double)(nfeatures), logbase2((double)(nfeatures), _state), _state),smpactivationlevel(_state)) )
5075 : {
5076 0 : if( _trypexec_basestat_rankdatarec(xy,i0,i1,nfeatures,iscentered,pool,basecasecost, _state) )
5077 : {
5078 0 : ae_frame_leave(_state);
5079 0 : return;
5080 : }
5081 : }
5082 :
5083 : /*
5084 : * Recursively split problem, if it is too large
5085 : */
5086 0 : problemcost = rmul3((double)(i1-i0), (double)(nfeatures), logbase2((double)(nfeatures), _state), _state);
5087 0 : if( i1-i0>=2&&ae_fp_greater(problemcost,spawnlevel(_state)) )
5088 : {
5089 0 : im = (i1+i0)/2;
5090 0 : basestat_rankdatarec(xy, i0, im, nfeatures, iscentered, pool, basecasecost, _state);
5091 0 : basestat_rankdatarec(xy, im, i1, nfeatures, iscentered, pool, basecasecost, _state);
5092 0 : ae_frame_leave(_state);
5093 0 : return;
5094 : }
5095 :
5096 : /*
5097 : * Retrieve buffers from pool, call serial code, return buffers to pool
5098 : */
5099 0 : ae_shared_pool_retrieve(pool, &_buf0, _state);
5100 0 : ae_shared_pool_retrieve(pool, &_buf1, _state);
5101 0 : basestat_rankdatabasecase(xy, i0, i1, nfeatures, iscentered, buf0, buf1, _state);
5102 0 : ae_shared_pool_recycle(pool, &_buf0, _state);
5103 0 : ae_shared_pool_recycle(pool, &_buf1, _state);
5104 0 : ae_frame_leave(_state);
5105 : }
5106 :
5107 :
5108 : /*************************************************************************
5109 : Serial stub for GPL edition.
5110 : *************************************************************************/
5111 0 : ae_bool _trypexec_basestat_rankdatarec(/* Real */ ae_matrix* xy,
5112 : ae_int_t i0,
5113 : ae_int_t i1,
5114 : ae_int_t nfeatures,
5115 : ae_bool iscentered,
5116 : ae_shared_pool* pool,
5117 : ae_int_t basecasecost,
5118 : ae_state *_state)
5119 : {
5120 0 : return ae_false;
5121 : }
5122 :
5123 :
5124 : /*************************************************************************
5125 : Basecase code for RankData(), performs actual work on subset of data using
5126 : temporary buffer passed as parameter.
5127 :
5128 : INPUT PARAMETERS:
5129 : XY - array[NPoints,NFeatures], dataset
5130 : I0 - index of first row to process
5131 : I1 - index of past-the-last row to process;
5132 : this function processes half-interval [I0,I1).
5133 : NFeatures- number of features
5134 : IsCentered- whether ranks are centered or not:
5135 : * True - ranks are centered in such way that their
5136 : within-row sum is zero
5137 : * False - ranks are not centered
5138 : Buf0 - temporary buffers, may be empty (this function automatically
5139 : allocates/reuses buffers).
5140 : Buf1 - temporary buffers, may be empty (this function automatically
5141 : allocates/reuses buffers).
5142 :
5143 : OUTPUT PARAMETERS:
5144 : XY - data in [I0,I1) are replaced by their within-row ranks;
5145 : ranking starts from 0, ends at NFeatures-1
5146 :
5147 : -- ALGLIB --
5148 : Copyright 18.04.2013 by Bochkanov Sergey
5149 : *************************************************************************/
5150 0 : static void basestat_rankdatabasecase(/* Real */ ae_matrix* xy,
5151 : ae_int_t i0,
5152 : ae_int_t i1,
5153 : ae_int_t nfeatures,
5154 : ae_bool iscentered,
5155 : apbuffers* buf0,
5156 : apbuffers* buf1,
5157 : ae_state *_state)
5158 : {
5159 : ae_int_t i;
5160 :
5161 :
5162 0 : ae_assert(i1>=i0, "RankDataBasecase: internal error", _state);
5163 0 : if( buf1->ra0.cnt<nfeatures )
5164 : {
5165 0 : ae_vector_set_length(&buf1->ra0, nfeatures, _state);
5166 : }
5167 0 : for(i=i0; i<=i1-1; i++)
5168 : {
5169 0 : ae_v_move(&buf1->ra0.ptr.p_double[0], 1, &xy->ptr.pp_double[i][0], 1, ae_v_len(0,nfeatures-1));
5170 0 : rankx(&buf1->ra0, nfeatures, iscentered, buf0, _state);
5171 0 : ae_v_move(&xy->ptr.pp_double[i][0], 1, &buf1->ra0.ptr.p_double[0], 1, ae_v_len(0,nfeatures-1));
5172 : }
5173 0 : }
5174 :
5175 :
5176 : /*************************************************************************
5177 : Serial stub for GPL edition.
5178 : *************************************************************************/
5179 0 : ae_bool _trypexec_basestat_rankdatabasecase(/* Real */ ae_matrix* xy,
5180 : ae_int_t i0,
5181 : ae_int_t i1,
5182 : ae_int_t nfeatures,
5183 : ae_bool iscentered,
5184 : apbuffers* buf0,
5185 : apbuffers* buf1,
5186 : ae_state *_state)
5187 : {
5188 0 : return ae_false;
5189 : }
5190 :
5191 :
5192 : #endif
5193 : #if defined(AE_COMPILE_WSR) || !defined(AE_PARTIAL_BUILD)
5194 :
5195 :
5196 : /*************************************************************************
5197 : Wilcoxon signed-rank test
5198 :
5199 : This test checks three hypotheses about the median of the given sample.
5200 : The following tests are performed:
5201 : * two-tailed test (null hypothesis - the median is equal to the given
5202 : value)
5203 : * left-tailed test (null hypothesis - the median is greater than or
5204 : equal to the given value)
5205 : * right-tailed test (null hypothesis - the median is less than or
5206 : equal to the given value)
5207 :
5208 : Requirements:
5209 : * the scale of measurement should be ordinal, interval or ratio (i.e.
5210 : the test could not be applied to nominal variables).
5211 : * the distribution should be continuous and symmetric relative to its
5212 : median.
5213 : * number of distinct values in the X array should be greater than 4
5214 :
5215 : The test is non-parametric and doesn't require distribution X to be normal
5216 :
5217 : Input parameters:
5218 : X - sample. Array whose index goes from 0 to N-1.
5219 : N - size of the sample.
5220 : Median - assumed median value.
5221 :
5222 : Output parameters:
5223 : BothTails - p-value for two-tailed test.
5224 : If BothTails is less than the given significance level
5225 : the null hypothesis is rejected.
5226 : LeftTail - p-value for left-tailed test.
5227 : If LeftTail is less than the given significance level,
5228 : the null hypothesis is rejected.
5229 : RightTail - p-value for right-tailed test.
5230 : If RightTail is less than the given significance level
5231 : the null hypothesis is rejected.
5232 :
5233 : To calculate p-values, special approximation is used. This method lets us
5234 : calculate p-values with two decimal places in interval [0.0001, 1].
5235 :
5236 : "Two decimal places" does not sound very impressive, but in practice the
5237 : relative error of less than 1% is enough to make a decision.
5238 :
5239 : There is no approximation outside the [0.0001, 1] interval. Therefore, if
5240 : the significance level outlies this interval, the test returns 0.0001.
5241 :
5242 : -- ALGLIB --
5243 : Copyright 08.09.2006 by Bochkanov Sergey
5244 : *************************************************************************/
5245 0 : void wilcoxonsignedranktest(/* Real */ ae_vector* x,
5246 : ae_int_t n,
5247 : double e,
5248 : double* bothtails,
5249 : double* lefttail,
5250 : double* righttail,
5251 : ae_state *_state)
5252 : {
5253 : ae_frame _frame_block;
5254 : ae_vector _x;
5255 : ae_int_t i;
5256 : ae_int_t j;
5257 : ae_int_t k;
5258 : ae_int_t t;
5259 : double tmp;
5260 : ae_int_t tmpi;
5261 : ae_int_t ns;
5262 : ae_vector r;
5263 : ae_vector c;
5264 : double w;
5265 : double p;
5266 : double mp;
5267 : double s;
5268 : double sigma;
5269 : double mu;
5270 :
5271 0 : ae_frame_make(_state, &_frame_block);
5272 0 : memset(&_x, 0, sizeof(_x));
5273 0 : memset(&r, 0, sizeof(r));
5274 0 : memset(&c, 0, sizeof(c));
5275 0 : ae_vector_init_copy(&_x, x, _state, ae_true);
5276 0 : x = &_x;
5277 0 : *bothtails = 0;
5278 0 : *lefttail = 0;
5279 0 : *righttail = 0;
5280 0 : ae_vector_init(&r, 0, DT_REAL, _state, ae_true);
5281 0 : ae_vector_init(&c, 0, DT_INT, _state, ae_true);
5282 :
5283 :
5284 : /*
5285 : * Prepare
5286 : */
5287 0 : if( n<5 )
5288 : {
5289 0 : *bothtails = 1.0;
5290 0 : *lefttail = 1.0;
5291 0 : *righttail = 1.0;
5292 0 : ae_frame_leave(_state);
5293 0 : return;
5294 : }
5295 0 : ns = 0;
5296 0 : for(i=0; i<=n-1; i++)
5297 : {
5298 0 : if( ae_fp_eq(x->ptr.p_double[i],e) )
5299 : {
5300 0 : continue;
5301 : }
5302 0 : x->ptr.p_double[ns] = x->ptr.p_double[i];
5303 0 : ns = ns+1;
5304 : }
5305 0 : if( ns<5 )
5306 : {
5307 0 : *bothtails = 1.0;
5308 0 : *lefttail = 1.0;
5309 0 : *righttail = 1.0;
5310 0 : ae_frame_leave(_state);
5311 0 : return;
5312 : }
5313 0 : ae_vector_set_length(&r, ns-1+1, _state);
5314 0 : ae_vector_set_length(&c, ns-1+1, _state);
5315 0 : for(i=0; i<=ns-1; i++)
5316 : {
5317 0 : r.ptr.p_double[i] = ae_fabs(x->ptr.p_double[i]-e, _state);
5318 0 : c.ptr.p_int[i] = i;
5319 : }
5320 :
5321 : /*
5322 : * sort {R, C}
5323 : */
5324 0 : if( ns!=1 )
5325 : {
5326 0 : i = 2;
5327 : do
5328 : {
5329 0 : t = i;
5330 0 : while(t!=1)
5331 : {
5332 0 : k = t/2;
5333 0 : if( ae_fp_greater_eq(r.ptr.p_double[k-1],r.ptr.p_double[t-1]) )
5334 : {
5335 0 : t = 1;
5336 : }
5337 : else
5338 : {
5339 0 : tmp = r.ptr.p_double[k-1];
5340 0 : r.ptr.p_double[k-1] = r.ptr.p_double[t-1];
5341 0 : r.ptr.p_double[t-1] = tmp;
5342 0 : tmpi = c.ptr.p_int[k-1];
5343 0 : c.ptr.p_int[k-1] = c.ptr.p_int[t-1];
5344 0 : c.ptr.p_int[t-1] = tmpi;
5345 0 : t = k;
5346 : }
5347 : }
5348 0 : i = i+1;
5349 : }
5350 0 : while(i<=ns);
5351 0 : i = ns-1;
5352 : do
5353 : {
5354 0 : tmp = r.ptr.p_double[i];
5355 0 : r.ptr.p_double[i] = r.ptr.p_double[0];
5356 0 : r.ptr.p_double[0] = tmp;
5357 0 : tmpi = c.ptr.p_int[i];
5358 0 : c.ptr.p_int[i] = c.ptr.p_int[0];
5359 0 : c.ptr.p_int[0] = tmpi;
5360 0 : t = 1;
5361 0 : while(t!=0)
5362 : {
5363 0 : k = 2*t;
5364 0 : if( k>i )
5365 : {
5366 0 : t = 0;
5367 : }
5368 : else
5369 : {
5370 0 : if( k<i )
5371 : {
5372 0 : if( ae_fp_greater(r.ptr.p_double[k],r.ptr.p_double[k-1]) )
5373 : {
5374 0 : k = k+1;
5375 : }
5376 : }
5377 0 : if( ae_fp_greater_eq(r.ptr.p_double[t-1],r.ptr.p_double[k-1]) )
5378 : {
5379 0 : t = 0;
5380 : }
5381 : else
5382 : {
5383 0 : tmp = r.ptr.p_double[k-1];
5384 0 : r.ptr.p_double[k-1] = r.ptr.p_double[t-1];
5385 0 : r.ptr.p_double[t-1] = tmp;
5386 0 : tmpi = c.ptr.p_int[k-1];
5387 0 : c.ptr.p_int[k-1] = c.ptr.p_int[t-1];
5388 0 : c.ptr.p_int[t-1] = tmpi;
5389 0 : t = k;
5390 : }
5391 : }
5392 : }
5393 0 : i = i-1;
5394 : }
5395 0 : while(i>=1);
5396 : }
5397 :
5398 : /*
5399 : * compute tied ranks
5400 : */
5401 0 : i = 0;
5402 0 : while(i<=ns-1)
5403 : {
5404 0 : j = i+1;
5405 0 : while(j<=ns-1)
5406 : {
5407 0 : if( ae_fp_neq(r.ptr.p_double[j],r.ptr.p_double[i]) )
5408 : {
5409 0 : break;
5410 : }
5411 0 : j = j+1;
5412 : }
5413 0 : for(k=i; k<=j-1; k++)
5414 : {
5415 0 : r.ptr.p_double[k] = 1+(double)(i+j-1)/(double)2;
5416 : }
5417 0 : i = j;
5418 : }
5419 :
5420 : /*
5421 : * Compute W+
5422 : */
5423 0 : w = (double)(0);
5424 0 : for(i=0; i<=ns-1; i++)
5425 : {
5426 0 : if( ae_fp_greater(x->ptr.p_double[c.ptr.p_int[i]],e) )
5427 : {
5428 0 : w = w+r.ptr.p_double[i];
5429 : }
5430 : }
5431 :
5432 : /*
5433 : * Result
5434 : */
5435 0 : mu = rmul2((double)(ns), (double)(ns+1), _state)/4;
5436 0 : sigma = ae_sqrt(mu*(2*ns+1)/6, _state);
5437 0 : s = (w-mu)/sigma;
5438 0 : if( ae_fp_less_eq(s,(double)(0)) )
5439 : {
5440 0 : p = ae_exp(wsr_wsigma(-(w-mu)/sigma, ns, _state), _state);
5441 0 : mp = 1-ae_exp(wsr_wsigma(-(w-1-mu)/sigma, ns, _state), _state);
5442 : }
5443 : else
5444 : {
5445 0 : mp = ae_exp(wsr_wsigma((w-mu)/sigma, ns, _state), _state);
5446 0 : p = 1-ae_exp(wsr_wsigma((w+1-mu)/sigma, ns, _state), _state);
5447 : }
5448 0 : *lefttail = ae_maxreal(p, 1.0E-4, _state);
5449 0 : *righttail = ae_maxreal(mp, 1.0E-4, _state);
5450 0 : *bothtails = 2*ae_minreal(*lefttail, *righttail, _state);
5451 0 : ae_frame_leave(_state);
5452 : }
5453 :
5454 :
5455 : /*************************************************************************
5456 : Sequential Chebyshev interpolation.
5457 : *************************************************************************/
5458 0 : static void wsr_wcheb(double x,
5459 : double c,
5460 : double* tj,
5461 : double* tj1,
5462 : double* r,
5463 : ae_state *_state)
5464 : {
5465 : double t;
5466 :
5467 :
5468 0 : *r = *r+c*(*tj);
5469 0 : t = 2*x*(*tj1)-(*tj);
5470 0 : *tj = *tj1;
5471 0 : *tj1 = t;
5472 0 : }
5473 :
5474 :
5475 : /*************************************************************************
5476 : Tail(S, 5)
5477 : *************************************************************************/
5478 0 : static double wsr_w5(double s, ae_state *_state)
5479 : {
5480 : ae_int_t w;
5481 : double r;
5482 : double result;
5483 :
5484 :
5485 0 : r = (double)(0);
5486 0 : w = ae_round(-3.708099e+00*s+7.500000e+00, _state);
5487 0 : if( w>=7 )
5488 : {
5489 0 : r = -6.931e-01;
5490 : }
5491 0 : if( w==6 )
5492 : {
5493 0 : r = -9.008e-01;
5494 : }
5495 0 : if( w==5 )
5496 : {
5497 0 : r = -1.163e+00;
5498 : }
5499 0 : if( w==4 )
5500 : {
5501 0 : r = -1.520e+00;
5502 : }
5503 0 : if( w==3 )
5504 : {
5505 0 : r = -1.856e+00;
5506 : }
5507 0 : if( w==2 )
5508 : {
5509 0 : r = -2.367e+00;
5510 : }
5511 0 : if( w==1 )
5512 : {
5513 0 : r = -2.773e+00;
5514 : }
5515 0 : if( w<=0 )
5516 : {
5517 0 : r = -3.466e+00;
5518 : }
5519 0 : result = r;
5520 0 : return result;
5521 : }
5522 :
5523 :
5524 : /*************************************************************************
5525 : Tail(S, 6)
5526 : *************************************************************************/
5527 0 : static double wsr_w6(double s, ae_state *_state)
5528 : {
5529 : ae_int_t w;
5530 : double r;
5531 : double result;
5532 :
5533 :
5534 0 : r = (double)(0);
5535 0 : w = ae_round(-4.769696e+00*s+1.050000e+01, _state);
5536 0 : if( w>=10 )
5537 : {
5538 0 : r = -6.931e-01;
5539 : }
5540 0 : if( w==9 )
5541 : {
5542 0 : r = -8.630e-01;
5543 : }
5544 0 : if( w==8 )
5545 : {
5546 0 : r = -1.068e+00;
5547 : }
5548 0 : if( w==7 )
5549 : {
5550 0 : r = -1.269e+00;
5551 : }
5552 0 : if( w==6 )
5553 : {
5554 0 : r = -1.520e+00;
5555 : }
5556 0 : if( w==5 )
5557 : {
5558 0 : r = -1.856e+00;
5559 : }
5560 0 : if( w==4 )
5561 : {
5562 0 : r = -2.213e+00;
5563 : }
5564 0 : if( w==3 )
5565 : {
5566 0 : r = -2.549e+00;
5567 : }
5568 0 : if( w==2 )
5569 : {
5570 0 : r = -3.060e+00;
5571 : }
5572 0 : if( w==1 )
5573 : {
5574 0 : r = -3.466e+00;
5575 : }
5576 0 : if( w<=0 )
5577 : {
5578 0 : r = -4.159e+00;
5579 : }
5580 0 : result = r;
5581 0 : return result;
5582 : }
5583 :
5584 :
5585 : /*************************************************************************
5586 : Tail(S, 7)
5587 : *************************************************************************/
5588 0 : static double wsr_w7(double s, ae_state *_state)
5589 : {
5590 : ae_int_t w;
5591 : double r;
5592 : double result;
5593 :
5594 :
5595 0 : r = (double)(0);
5596 0 : w = ae_round(-5.916080e+00*s+1.400000e+01, _state);
5597 0 : if( w>=14 )
5598 : {
5599 0 : r = -6.325e-01;
5600 : }
5601 0 : if( w==13 )
5602 : {
5603 0 : r = -7.577e-01;
5604 : }
5605 0 : if( w==12 )
5606 : {
5607 0 : r = -9.008e-01;
5608 : }
5609 0 : if( w==11 )
5610 : {
5611 0 : r = -1.068e+00;
5612 : }
5613 0 : if( w==10 )
5614 : {
5615 0 : r = -1.241e+00;
5616 : }
5617 0 : if( w==9 )
5618 : {
5619 0 : r = -1.451e+00;
5620 : }
5621 0 : if( w==8 )
5622 : {
5623 0 : r = -1.674e+00;
5624 : }
5625 0 : if( w==7 )
5626 : {
5627 0 : r = -1.908e+00;
5628 : }
5629 0 : if( w==6 )
5630 : {
5631 0 : r = -2.213e+00;
5632 : }
5633 0 : if( w==5 )
5634 : {
5635 0 : r = -2.549e+00;
5636 : }
5637 0 : if( w==4 )
5638 : {
5639 0 : r = -2.906e+00;
5640 : }
5641 0 : if( w==3 )
5642 : {
5643 0 : r = -3.243e+00;
5644 : }
5645 0 : if( w==2 )
5646 : {
5647 0 : r = -3.753e+00;
5648 : }
5649 0 : if( w==1 )
5650 : {
5651 0 : r = -4.159e+00;
5652 : }
5653 0 : if( w<=0 )
5654 : {
5655 0 : r = -4.852e+00;
5656 : }
5657 0 : result = r;
5658 0 : return result;
5659 : }
5660 :
5661 :
5662 : /*************************************************************************
5663 : Tail(S, 8)
5664 : *************************************************************************/
5665 0 : static double wsr_w8(double s, ae_state *_state)
5666 : {
5667 : ae_int_t w;
5668 : double r;
5669 : double result;
5670 :
5671 :
5672 0 : r = (double)(0);
5673 0 : w = ae_round(-7.141428e+00*s+1.800000e+01, _state);
5674 0 : if( w>=18 )
5675 : {
5676 0 : r = -6.399e-01;
5677 : }
5678 0 : if( w==17 )
5679 : {
5680 0 : r = -7.494e-01;
5681 : }
5682 0 : if( w==16 )
5683 : {
5684 0 : r = -8.630e-01;
5685 : }
5686 0 : if( w==15 )
5687 : {
5688 0 : r = -9.913e-01;
5689 : }
5690 0 : if( w==14 )
5691 : {
5692 0 : r = -1.138e+00;
5693 : }
5694 0 : if( w==13 )
5695 : {
5696 0 : r = -1.297e+00;
5697 : }
5698 0 : if( w==12 )
5699 : {
5700 0 : r = -1.468e+00;
5701 : }
5702 0 : if( w==11 )
5703 : {
5704 0 : r = -1.653e+00;
5705 : }
5706 0 : if( w==10 )
5707 : {
5708 0 : r = -1.856e+00;
5709 : }
5710 0 : if( w==9 )
5711 : {
5712 0 : r = -2.079e+00;
5713 : }
5714 0 : if( w==8 )
5715 : {
5716 0 : r = -2.326e+00;
5717 : }
5718 0 : if( w==7 )
5719 : {
5720 0 : r = -2.601e+00;
5721 : }
5722 0 : if( w==6 )
5723 : {
5724 0 : r = -2.906e+00;
5725 : }
5726 0 : if( w==5 )
5727 : {
5728 0 : r = -3.243e+00;
5729 : }
5730 0 : if( w==4 )
5731 : {
5732 0 : r = -3.599e+00;
5733 : }
5734 0 : if( w==3 )
5735 : {
5736 0 : r = -3.936e+00;
5737 : }
5738 0 : if( w==2 )
5739 : {
5740 0 : r = -4.447e+00;
5741 : }
5742 0 : if( w==1 )
5743 : {
5744 0 : r = -4.852e+00;
5745 : }
5746 0 : if( w<=0 )
5747 : {
5748 0 : r = -5.545e+00;
5749 : }
5750 0 : result = r;
5751 0 : return result;
5752 : }
5753 :
5754 :
5755 : /*************************************************************************
5756 : Tail(S, 9)
5757 : *************************************************************************/
5758 0 : static double wsr_w9(double s, ae_state *_state)
5759 : {
5760 : ae_int_t w;
5761 : double r;
5762 : double result;
5763 :
5764 :
5765 0 : r = (double)(0);
5766 0 : w = ae_round(-8.440972e+00*s+2.250000e+01, _state);
5767 0 : if( w>=22 )
5768 : {
5769 0 : r = -6.931e-01;
5770 : }
5771 0 : if( w==21 )
5772 : {
5773 0 : r = -7.873e-01;
5774 : }
5775 0 : if( w==20 )
5776 : {
5777 0 : r = -8.912e-01;
5778 : }
5779 0 : if( w==19 )
5780 : {
5781 0 : r = -1.002e+00;
5782 : }
5783 0 : if( w==18 )
5784 : {
5785 0 : r = -1.120e+00;
5786 : }
5787 0 : if( w==17 )
5788 : {
5789 0 : r = -1.255e+00;
5790 : }
5791 0 : if( w==16 )
5792 : {
5793 0 : r = -1.394e+00;
5794 : }
5795 0 : if( w==15 )
5796 : {
5797 0 : r = -1.547e+00;
5798 : }
5799 0 : if( w==14 )
5800 : {
5801 0 : r = -1.717e+00;
5802 : }
5803 0 : if( w==13 )
5804 : {
5805 0 : r = -1.895e+00;
5806 : }
5807 0 : if( w==12 )
5808 : {
5809 0 : r = -2.079e+00;
5810 : }
5811 0 : if( w==11 )
5812 : {
5813 0 : r = -2.287e+00;
5814 : }
5815 0 : if( w==10 )
5816 : {
5817 0 : r = -2.501e+00;
5818 : }
5819 0 : if( w==9 )
5820 : {
5821 0 : r = -2.742e+00;
5822 : }
5823 0 : if( w==8 )
5824 : {
5825 0 : r = -3.019e+00;
5826 : }
5827 0 : if( w==7 )
5828 : {
5829 0 : r = -3.294e+00;
5830 : }
5831 0 : if( w==6 )
5832 : {
5833 0 : r = -3.599e+00;
5834 : }
5835 0 : if( w==5 )
5836 : {
5837 0 : r = -3.936e+00;
5838 : }
5839 0 : if( w==4 )
5840 : {
5841 0 : r = -4.292e+00;
5842 : }
5843 0 : if( w==3 )
5844 : {
5845 0 : r = -4.629e+00;
5846 : }
5847 0 : if( w==2 )
5848 : {
5849 0 : r = -5.140e+00;
5850 : }
5851 0 : if( w==1 )
5852 : {
5853 0 : r = -5.545e+00;
5854 : }
5855 0 : if( w<=0 )
5856 : {
5857 0 : r = -6.238e+00;
5858 : }
5859 0 : result = r;
5860 0 : return result;
5861 : }
5862 :
5863 :
5864 : /*************************************************************************
5865 : Tail(S, 10)
5866 : *************************************************************************/
5867 0 : static double wsr_w10(double s, ae_state *_state)
5868 : {
5869 : ae_int_t w;
5870 : double r;
5871 : double result;
5872 :
5873 :
5874 0 : r = (double)(0);
5875 0 : w = ae_round(-9.810708e+00*s+2.750000e+01, _state);
5876 0 : if( w>=27 )
5877 : {
5878 0 : r = -6.931e-01;
5879 : }
5880 0 : if( w==26 )
5881 : {
5882 0 : r = -7.745e-01;
5883 : }
5884 0 : if( w==25 )
5885 : {
5886 0 : r = -8.607e-01;
5887 : }
5888 0 : if( w==24 )
5889 : {
5890 0 : r = -9.551e-01;
5891 : }
5892 0 : if( w==23 )
5893 : {
5894 0 : r = -1.057e+00;
5895 : }
5896 0 : if( w==22 )
5897 : {
5898 0 : r = -1.163e+00;
5899 : }
5900 0 : if( w==21 )
5901 : {
5902 0 : r = -1.279e+00;
5903 : }
5904 0 : if( w==20 )
5905 : {
5906 0 : r = -1.402e+00;
5907 : }
5908 0 : if( w==19 )
5909 : {
5910 0 : r = -1.533e+00;
5911 : }
5912 0 : if( w==18 )
5913 : {
5914 0 : r = -1.674e+00;
5915 : }
5916 0 : if( w==17 )
5917 : {
5918 0 : r = -1.826e+00;
5919 : }
5920 0 : if( w==16 )
5921 : {
5922 0 : r = -1.983e+00;
5923 : }
5924 0 : if( w==15 )
5925 : {
5926 0 : r = -2.152e+00;
5927 : }
5928 0 : if( w==14 )
5929 : {
5930 0 : r = -2.336e+00;
5931 : }
5932 0 : if( w==13 )
5933 : {
5934 0 : r = -2.525e+00;
5935 : }
5936 0 : if( w==12 )
5937 : {
5938 0 : r = -2.727e+00;
5939 : }
5940 0 : if( w==11 )
5941 : {
5942 0 : r = -2.942e+00;
5943 : }
5944 0 : if( w==10 )
5945 : {
5946 0 : r = -3.170e+00;
5947 : }
5948 0 : if( w==9 )
5949 : {
5950 0 : r = -3.435e+00;
5951 : }
5952 0 : if( w==8 )
5953 : {
5954 0 : r = -3.713e+00;
5955 : }
5956 0 : if( w==7 )
5957 : {
5958 0 : r = -3.987e+00;
5959 : }
5960 0 : if( w==6 )
5961 : {
5962 0 : r = -4.292e+00;
5963 : }
5964 0 : if( w==5 )
5965 : {
5966 0 : r = -4.629e+00;
5967 : }
5968 0 : if( w==4 )
5969 : {
5970 0 : r = -4.986e+00;
5971 : }
5972 0 : if( w==3 )
5973 : {
5974 0 : r = -5.322e+00;
5975 : }
5976 0 : if( w==2 )
5977 : {
5978 0 : r = -5.833e+00;
5979 : }
5980 0 : if( w==1 )
5981 : {
5982 0 : r = -6.238e+00;
5983 : }
5984 0 : if( w<=0 )
5985 : {
5986 0 : r = -6.931e+00;
5987 : }
5988 0 : result = r;
5989 0 : return result;
5990 : }
5991 :
5992 :
5993 : /*************************************************************************
5994 : Tail(S, 11)
5995 : *************************************************************************/
5996 0 : static double wsr_w11(double s, ae_state *_state)
5997 : {
5998 : ae_int_t w;
5999 : double r;
6000 : double result;
6001 :
6002 :
6003 0 : r = (double)(0);
6004 0 : w = ae_round(-1.124722e+01*s+3.300000e+01, _state);
6005 0 : if( w>=33 )
6006 : {
6007 0 : r = -6.595e-01;
6008 : }
6009 0 : if( w==32 )
6010 : {
6011 0 : r = -7.279e-01;
6012 : }
6013 0 : if( w==31 )
6014 : {
6015 0 : r = -8.002e-01;
6016 : }
6017 0 : if( w==30 )
6018 : {
6019 0 : r = -8.782e-01;
6020 : }
6021 0 : if( w==29 )
6022 : {
6023 0 : r = -9.615e-01;
6024 : }
6025 0 : if( w==28 )
6026 : {
6027 0 : r = -1.050e+00;
6028 : }
6029 0 : if( w==27 )
6030 : {
6031 0 : r = -1.143e+00;
6032 : }
6033 0 : if( w==26 )
6034 : {
6035 0 : r = -1.243e+00;
6036 : }
6037 0 : if( w==25 )
6038 : {
6039 0 : r = -1.348e+00;
6040 : }
6041 0 : if( w==24 )
6042 : {
6043 0 : r = -1.459e+00;
6044 : }
6045 0 : if( w==23 )
6046 : {
6047 0 : r = -1.577e+00;
6048 : }
6049 0 : if( w==22 )
6050 : {
6051 0 : r = -1.700e+00;
6052 : }
6053 0 : if( w==21 )
6054 : {
6055 0 : r = -1.832e+00;
6056 : }
6057 0 : if( w==20 )
6058 : {
6059 0 : r = -1.972e+00;
6060 : }
6061 0 : if( w==19 )
6062 : {
6063 0 : r = -2.119e+00;
6064 : }
6065 0 : if( w==18 )
6066 : {
6067 0 : r = -2.273e+00;
6068 : }
6069 0 : if( w==17 )
6070 : {
6071 0 : r = -2.437e+00;
6072 : }
6073 0 : if( w==16 )
6074 : {
6075 0 : r = -2.607e+00;
6076 : }
6077 0 : if( w==15 )
6078 : {
6079 0 : r = -2.788e+00;
6080 : }
6081 0 : if( w==14 )
6082 : {
6083 0 : r = -2.980e+00;
6084 : }
6085 0 : if( w==13 )
6086 : {
6087 0 : r = -3.182e+00;
6088 : }
6089 0 : if( w==12 )
6090 : {
6091 0 : r = -3.391e+00;
6092 : }
6093 0 : if( w==11 )
6094 : {
6095 0 : r = -3.617e+00;
6096 : }
6097 0 : if( w==10 )
6098 : {
6099 0 : r = -3.863e+00;
6100 : }
6101 0 : if( w==9 )
6102 : {
6103 0 : r = -4.128e+00;
6104 : }
6105 0 : if( w==8 )
6106 : {
6107 0 : r = -4.406e+00;
6108 : }
6109 0 : if( w==7 )
6110 : {
6111 0 : r = -4.680e+00;
6112 : }
6113 0 : if( w==6 )
6114 : {
6115 0 : r = -4.986e+00;
6116 : }
6117 0 : if( w==5 )
6118 : {
6119 0 : r = -5.322e+00;
6120 : }
6121 0 : if( w==4 )
6122 : {
6123 0 : r = -5.679e+00;
6124 : }
6125 0 : if( w==3 )
6126 : {
6127 0 : r = -6.015e+00;
6128 : }
6129 0 : if( w==2 )
6130 : {
6131 0 : r = -6.526e+00;
6132 : }
6133 0 : if( w==1 )
6134 : {
6135 0 : r = -6.931e+00;
6136 : }
6137 0 : if( w<=0 )
6138 : {
6139 0 : r = -7.625e+00;
6140 : }
6141 0 : result = r;
6142 0 : return result;
6143 : }
6144 :
6145 :
6146 : /*************************************************************************
6147 : Tail(S, 12)
6148 : *************************************************************************/
6149 0 : static double wsr_w12(double s, ae_state *_state)
6150 : {
6151 : ae_int_t w;
6152 : double r;
6153 : double result;
6154 :
6155 :
6156 0 : r = (double)(0);
6157 0 : w = ae_round(-1.274755e+01*s+3.900000e+01, _state);
6158 0 : if( w>=39 )
6159 : {
6160 0 : r = -6.633e-01;
6161 : }
6162 0 : if( w==38 )
6163 : {
6164 0 : r = -7.239e-01;
6165 : }
6166 0 : if( w==37 )
6167 : {
6168 0 : r = -7.878e-01;
6169 : }
6170 0 : if( w==36 )
6171 : {
6172 0 : r = -8.556e-01;
6173 : }
6174 0 : if( w==35 )
6175 : {
6176 0 : r = -9.276e-01;
6177 : }
6178 0 : if( w==34 )
6179 : {
6180 0 : r = -1.003e+00;
6181 : }
6182 0 : if( w==33 )
6183 : {
6184 0 : r = -1.083e+00;
6185 : }
6186 0 : if( w==32 )
6187 : {
6188 0 : r = -1.168e+00;
6189 : }
6190 0 : if( w==31 )
6191 : {
6192 0 : r = -1.256e+00;
6193 : }
6194 0 : if( w==30 )
6195 : {
6196 0 : r = -1.350e+00;
6197 : }
6198 0 : if( w==29 )
6199 : {
6200 0 : r = -1.449e+00;
6201 : }
6202 0 : if( w==28 )
6203 : {
6204 0 : r = -1.552e+00;
6205 : }
6206 0 : if( w==27 )
6207 : {
6208 0 : r = -1.660e+00;
6209 : }
6210 0 : if( w==26 )
6211 : {
6212 0 : r = -1.774e+00;
6213 : }
6214 0 : if( w==25 )
6215 : {
6216 0 : r = -1.893e+00;
6217 : }
6218 0 : if( w==24 )
6219 : {
6220 0 : r = -2.017e+00;
6221 : }
6222 0 : if( w==23 )
6223 : {
6224 0 : r = -2.148e+00;
6225 : }
6226 0 : if( w==22 )
6227 : {
6228 0 : r = -2.285e+00;
6229 : }
6230 0 : if( w==21 )
6231 : {
6232 0 : r = -2.429e+00;
6233 : }
6234 0 : if( w==20 )
6235 : {
6236 0 : r = -2.581e+00;
6237 : }
6238 0 : if( w==19 )
6239 : {
6240 0 : r = -2.738e+00;
6241 : }
6242 0 : if( w==18 )
6243 : {
6244 0 : r = -2.902e+00;
6245 : }
6246 0 : if( w==17 )
6247 : {
6248 0 : r = -3.076e+00;
6249 : }
6250 0 : if( w==16 )
6251 : {
6252 0 : r = -3.255e+00;
6253 : }
6254 0 : if( w==15 )
6255 : {
6256 0 : r = -3.443e+00;
6257 : }
6258 0 : if( w==14 )
6259 : {
6260 0 : r = -3.645e+00;
6261 : }
6262 0 : if( w==13 )
6263 : {
6264 0 : r = -3.852e+00;
6265 : }
6266 0 : if( w==12 )
6267 : {
6268 0 : r = -4.069e+00;
6269 : }
6270 0 : if( w==11 )
6271 : {
6272 0 : r = -4.310e+00;
6273 : }
6274 0 : if( w==10 )
6275 : {
6276 0 : r = -4.557e+00;
6277 : }
6278 0 : if( w==9 )
6279 : {
6280 0 : r = -4.821e+00;
6281 : }
6282 0 : if( w==8 )
6283 : {
6284 0 : r = -5.099e+00;
6285 : }
6286 0 : if( w==7 )
6287 : {
6288 0 : r = -5.373e+00;
6289 : }
6290 0 : if( w==6 )
6291 : {
6292 0 : r = -5.679e+00;
6293 : }
6294 0 : if( w==5 )
6295 : {
6296 0 : r = -6.015e+00;
6297 : }
6298 0 : if( w==4 )
6299 : {
6300 0 : r = -6.372e+00;
6301 : }
6302 0 : if( w==3 )
6303 : {
6304 0 : r = -6.708e+00;
6305 : }
6306 0 : if( w==2 )
6307 : {
6308 0 : r = -7.219e+00;
6309 : }
6310 0 : if( w==1 )
6311 : {
6312 0 : r = -7.625e+00;
6313 : }
6314 0 : if( w<=0 )
6315 : {
6316 0 : r = -8.318e+00;
6317 : }
6318 0 : result = r;
6319 0 : return result;
6320 : }
6321 :
6322 :
6323 : /*************************************************************************
6324 : Tail(S, 13)
6325 : *************************************************************************/
6326 0 : static double wsr_w13(double s, ae_state *_state)
6327 : {
6328 : ae_int_t w;
6329 : double r;
6330 : double result;
6331 :
6332 :
6333 0 : r = (double)(0);
6334 0 : w = ae_round(-1.430909e+01*s+4.550000e+01, _state);
6335 0 : if( w>=45 )
6336 : {
6337 0 : r = -6.931e-01;
6338 : }
6339 0 : if( w==44 )
6340 : {
6341 0 : r = -7.486e-01;
6342 : }
6343 0 : if( w==43 )
6344 : {
6345 0 : r = -8.068e-01;
6346 : }
6347 0 : if( w==42 )
6348 : {
6349 0 : r = -8.683e-01;
6350 : }
6351 0 : if( w==41 )
6352 : {
6353 0 : r = -9.328e-01;
6354 : }
6355 0 : if( w==40 )
6356 : {
6357 0 : r = -1.001e+00;
6358 : }
6359 0 : if( w==39 )
6360 : {
6361 0 : r = -1.072e+00;
6362 : }
6363 0 : if( w==38 )
6364 : {
6365 0 : r = -1.146e+00;
6366 : }
6367 0 : if( w==37 )
6368 : {
6369 0 : r = -1.224e+00;
6370 : }
6371 0 : if( w==36 )
6372 : {
6373 0 : r = -1.306e+00;
6374 : }
6375 0 : if( w==35 )
6376 : {
6377 0 : r = -1.392e+00;
6378 : }
6379 0 : if( w==34 )
6380 : {
6381 0 : r = -1.481e+00;
6382 : }
6383 0 : if( w==33 )
6384 : {
6385 0 : r = -1.574e+00;
6386 : }
6387 0 : if( w==32 )
6388 : {
6389 0 : r = -1.672e+00;
6390 : }
6391 0 : if( w==31 )
6392 : {
6393 0 : r = -1.773e+00;
6394 : }
6395 0 : if( w==30 )
6396 : {
6397 0 : r = -1.879e+00;
6398 : }
6399 0 : if( w==29 )
6400 : {
6401 0 : r = -1.990e+00;
6402 : }
6403 0 : if( w==28 )
6404 : {
6405 0 : r = -2.104e+00;
6406 : }
6407 0 : if( w==27 )
6408 : {
6409 0 : r = -2.224e+00;
6410 : }
6411 0 : if( w==26 )
6412 : {
6413 0 : r = -2.349e+00;
6414 : }
6415 0 : if( w==25 )
6416 : {
6417 0 : r = -2.479e+00;
6418 : }
6419 0 : if( w==24 )
6420 : {
6421 0 : r = -2.614e+00;
6422 : }
6423 0 : if( w==23 )
6424 : {
6425 0 : r = -2.755e+00;
6426 : }
6427 0 : if( w==22 )
6428 : {
6429 0 : r = -2.902e+00;
6430 : }
6431 0 : if( w==21 )
6432 : {
6433 0 : r = -3.055e+00;
6434 : }
6435 0 : if( w==20 )
6436 : {
6437 0 : r = -3.215e+00;
6438 : }
6439 0 : if( w==19 )
6440 : {
6441 0 : r = -3.380e+00;
6442 : }
6443 0 : if( w==18 )
6444 : {
6445 0 : r = -3.551e+00;
6446 : }
6447 0 : if( w==17 )
6448 : {
6449 0 : r = -3.733e+00;
6450 : }
6451 0 : if( w==16 )
6452 : {
6453 0 : r = -3.917e+00;
6454 : }
6455 0 : if( w==15 )
6456 : {
6457 0 : r = -4.113e+00;
6458 : }
6459 0 : if( w==14 )
6460 : {
6461 0 : r = -4.320e+00;
6462 : }
6463 0 : if( w==13 )
6464 : {
6465 0 : r = -4.534e+00;
6466 : }
6467 0 : if( w==12 )
6468 : {
6469 0 : r = -4.762e+00;
6470 : }
6471 0 : if( w==11 )
6472 : {
6473 0 : r = -5.004e+00;
6474 : }
6475 0 : if( w==10 )
6476 : {
6477 0 : r = -5.250e+00;
6478 : }
6479 0 : if( w==9 )
6480 : {
6481 0 : r = -5.514e+00;
6482 : }
6483 0 : if( w==8 )
6484 : {
6485 0 : r = -5.792e+00;
6486 : }
6487 0 : if( w==7 )
6488 : {
6489 0 : r = -6.066e+00;
6490 : }
6491 0 : if( w==6 )
6492 : {
6493 0 : r = -6.372e+00;
6494 : }
6495 0 : if( w==5 )
6496 : {
6497 0 : r = -6.708e+00;
6498 : }
6499 0 : if( w==4 )
6500 : {
6501 0 : r = -7.065e+00;
6502 : }
6503 0 : if( w==3 )
6504 : {
6505 0 : r = -7.401e+00;
6506 : }
6507 0 : if( w==2 )
6508 : {
6509 0 : r = -7.912e+00;
6510 : }
6511 0 : if( w==1 )
6512 : {
6513 0 : r = -8.318e+00;
6514 : }
6515 0 : if( w<=0 )
6516 : {
6517 0 : r = -9.011e+00;
6518 : }
6519 0 : result = r;
6520 0 : return result;
6521 : }
6522 :
6523 :
6524 : /*************************************************************************
6525 : Tail(S, 14)
6526 : *************************************************************************/
6527 0 : static double wsr_w14(double s, ae_state *_state)
6528 : {
6529 : ae_int_t w;
6530 : double r;
6531 : double result;
6532 :
6533 :
6534 0 : r = (double)(0);
6535 0 : w = ae_round(-1.592953e+01*s+5.250000e+01, _state);
6536 0 : if( w>=52 )
6537 : {
6538 0 : r = -6.931e-01;
6539 : }
6540 0 : if( w==51 )
6541 : {
6542 0 : r = -7.428e-01;
6543 : }
6544 0 : if( w==50 )
6545 : {
6546 0 : r = -7.950e-01;
6547 : }
6548 0 : if( w==49 )
6549 : {
6550 0 : r = -8.495e-01;
6551 : }
6552 0 : if( w==48 )
6553 : {
6554 0 : r = -9.067e-01;
6555 : }
6556 0 : if( w==47 )
6557 : {
6558 0 : r = -9.664e-01;
6559 : }
6560 0 : if( w==46 )
6561 : {
6562 0 : r = -1.029e+00;
6563 : }
6564 0 : if( w==45 )
6565 : {
6566 0 : r = -1.094e+00;
6567 : }
6568 0 : if( w==44 )
6569 : {
6570 0 : r = -1.162e+00;
6571 : }
6572 0 : if( w==43 )
6573 : {
6574 0 : r = -1.233e+00;
6575 : }
6576 0 : if( w==42 )
6577 : {
6578 0 : r = -1.306e+00;
6579 : }
6580 0 : if( w==41 )
6581 : {
6582 0 : r = -1.383e+00;
6583 : }
6584 0 : if( w==40 )
6585 : {
6586 0 : r = -1.463e+00;
6587 : }
6588 0 : if( w==39 )
6589 : {
6590 0 : r = -1.546e+00;
6591 : }
6592 0 : if( w==38 )
6593 : {
6594 0 : r = -1.632e+00;
6595 : }
6596 0 : if( w==37 )
6597 : {
6598 0 : r = -1.722e+00;
6599 : }
6600 0 : if( w==36 )
6601 : {
6602 0 : r = -1.815e+00;
6603 : }
6604 0 : if( w==35 )
6605 : {
6606 0 : r = -1.911e+00;
6607 : }
6608 0 : if( w==34 )
6609 : {
6610 0 : r = -2.011e+00;
6611 : }
6612 0 : if( w==33 )
6613 : {
6614 0 : r = -2.115e+00;
6615 : }
6616 0 : if( w==32 )
6617 : {
6618 0 : r = -2.223e+00;
6619 : }
6620 0 : if( w==31 )
6621 : {
6622 0 : r = -2.334e+00;
6623 : }
6624 0 : if( w==30 )
6625 : {
6626 0 : r = -2.450e+00;
6627 : }
6628 0 : if( w==29 )
6629 : {
6630 0 : r = -2.570e+00;
6631 : }
6632 0 : if( w==28 )
6633 : {
6634 0 : r = -2.694e+00;
6635 : }
6636 0 : if( w==27 )
6637 : {
6638 0 : r = -2.823e+00;
6639 : }
6640 0 : if( w==26 )
6641 : {
6642 0 : r = -2.956e+00;
6643 : }
6644 0 : if( w==25 )
6645 : {
6646 0 : r = -3.095e+00;
6647 : }
6648 0 : if( w==24 )
6649 : {
6650 0 : r = -3.238e+00;
6651 : }
6652 0 : if( w==23 )
6653 : {
6654 0 : r = -3.387e+00;
6655 : }
6656 0 : if( w==22 )
6657 : {
6658 0 : r = -3.541e+00;
6659 : }
6660 0 : if( w==21 )
6661 : {
6662 0 : r = -3.700e+00;
6663 : }
6664 0 : if( w==20 )
6665 : {
6666 0 : r = -3.866e+00;
6667 : }
6668 0 : if( w==19 )
6669 : {
6670 0 : r = -4.038e+00;
6671 : }
6672 0 : if( w==18 )
6673 : {
6674 0 : r = -4.215e+00;
6675 : }
6676 0 : if( w==17 )
6677 : {
6678 0 : r = -4.401e+00;
6679 : }
6680 0 : if( w==16 )
6681 : {
6682 0 : r = -4.592e+00;
6683 : }
6684 0 : if( w==15 )
6685 : {
6686 0 : r = -4.791e+00;
6687 : }
6688 0 : if( w==14 )
6689 : {
6690 0 : r = -5.004e+00;
6691 : }
6692 0 : if( w==13 )
6693 : {
6694 0 : r = -5.227e+00;
6695 : }
6696 0 : if( w==12 )
6697 : {
6698 0 : r = -5.456e+00;
6699 : }
6700 0 : if( w==11 )
6701 : {
6702 0 : r = -5.697e+00;
6703 : }
6704 0 : if( w==10 )
6705 : {
6706 0 : r = -5.943e+00;
6707 : }
6708 0 : if( w==9 )
6709 : {
6710 0 : r = -6.208e+00;
6711 : }
6712 0 : if( w==8 )
6713 : {
6714 0 : r = -6.485e+00;
6715 : }
6716 0 : if( w==7 )
6717 : {
6718 0 : r = -6.760e+00;
6719 : }
6720 0 : if( w==6 )
6721 : {
6722 0 : r = -7.065e+00;
6723 : }
6724 0 : if( w==5 )
6725 : {
6726 0 : r = -7.401e+00;
6727 : }
6728 0 : if( w==4 )
6729 : {
6730 0 : r = -7.758e+00;
6731 : }
6732 0 : if( w==3 )
6733 : {
6734 0 : r = -8.095e+00;
6735 : }
6736 0 : if( w==2 )
6737 : {
6738 0 : r = -8.605e+00;
6739 : }
6740 0 : if( w==1 )
6741 : {
6742 0 : r = -9.011e+00;
6743 : }
6744 0 : if( w<=0 )
6745 : {
6746 0 : r = -9.704e+00;
6747 : }
6748 0 : result = r;
6749 0 : return result;
6750 : }
6751 :
6752 :
6753 : /*************************************************************************
6754 : Tail(S, 15)
6755 : *************************************************************************/
6756 0 : static double wsr_w15(double s, ae_state *_state)
6757 : {
6758 : ae_int_t w;
6759 : double r;
6760 : double result;
6761 :
6762 :
6763 0 : r = (double)(0);
6764 0 : w = ae_round(-1.760682e+01*s+6.000000e+01, _state);
6765 0 : if( w>=60 )
6766 : {
6767 0 : r = -6.714e-01;
6768 : }
6769 0 : if( w==59 )
6770 : {
6771 0 : r = -7.154e-01;
6772 : }
6773 0 : if( w==58 )
6774 : {
6775 0 : r = -7.613e-01;
6776 : }
6777 0 : if( w==57 )
6778 : {
6779 0 : r = -8.093e-01;
6780 : }
6781 0 : if( w==56 )
6782 : {
6783 0 : r = -8.593e-01;
6784 : }
6785 0 : if( w==55 )
6786 : {
6787 0 : r = -9.114e-01;
6788 : }
6789 0 : if( w==54 )
6790 : {
6791 0 : r = -9.656e-01;
6792 : }
6793 0 : if( w==53 )
6794 : {
6795 0 : r = -1.022e+00;
6796 : }
6797 0 : if( w==52 )
6798 : {
6799 0 : r = -1.081e+00;
6800 : }
6801 0 : if( w==51 )
6802 : {
6803 0 : r = -1.142e+00;
6804 : }
6805 0 : if( w==50 )
6806 : {
6807 0 : r = -1.205e+00;
6808 : }
6809 0 : if( w==49 )
6810 : {
6811 0 : r = -1.270e+00;
6812 : }
6813 0 : if( w==48 )
6814 : {
6815 0 : r = -1.339e+00;
6816 : }
6817 0 : if( w==47 )
6818 : {
6819 0 : r = -1.409e+00;
6820 : }
6821 0 : if( w==46 )
6822 : {
6823 0 : r = -1.482e+00;
6824 : }
6825 0 : if( w==45 )
6826 : {
6827 0 : r = -1.558e+00;
6828 : }
6829 0 : if( w==44 )
6830 : {
6831 0 : r = -1.636e+00;
6832 : }
6833 0 : if( w==43 )
6834 : {
6835 0 : r = -1.717e+00;
6836 : }
6837 0 : if( w==42 )
6838 : {
6839 0 : r = -1.801e+00;
6840 : }
6841 0 : if( w==41 )
6842 : {
6843 0 : r = -1.888e+00;
6844 : }
6845 0 : if( w==40 )
6846 : {
6847 0 : r = -1.977e+00;
6848 : }
6849 0 : if( w==39 )
6850 : {
6851 0 : r = -2.070e+00;
6852 : }
6853 0 : if( w==38 )
6854 : {
6855 0 : r = -2.166e+00;
6856 : }
6857 0 : if( w==37 )
6858 : {
6859 0 : r = -2.265e+00;
6860 : }
6861 0 : if( w==36 )
6862 : {
6863 0 : r = -2.366e+00;
6864 : }
6865 0 : if( w==35 )
6866 : {
6867 0 : r = -2.472e+00;
6868 : }
6869 0 : if( w==34 )
6870 : {
6871 0 : r = -2.581e+00;
6872 : }
6873 0 : if( w==33 )
6874 : {
6875 0 : r = -2.693e+00;
6876 : }
6877 0 : if( w==32 )
6878 : {
6879 0 : r = -2.809e+00;
6880 : }
6881 0 : if( w==31 )
6882 : {
6883 0 : r = -2.928e+00;
6884 : }
6885 0 : if( w==30 )
6886 : {
6887 0 : r = -3.051e+00;
6888 : }
6889 0 : if( w==29 )
6890 : {
6891 0 : r = -3.179e+00;
6892 : }
6893 0 : if( w==28 )
6894 : {
6895 0 : r = -3.310e+00;
6896 : }
6897 0 : if( w==27 )
6898 : {
6899 0 : r = -3.446e+00;
6900 : }
6901 0 : if( w==26 )
6902 : {
6903 0 : r = -3.587e+00;
6904 : }
6905 0 : if( w==25 )
6906 : {
6907 0 : r = -3.732e+00;
6908 : }
6909 0 : if( w==24 )
6910 : {
6911 0 : r = -3.881e+00;
6912 : }
6913 0 : if( w==23 )
6914 : {
6915 0 : r = -4.036e+00;
6916 : }
6917 0 : if( w==22 )
6918 : {
6919 0 : r = -4.195e+00;
6920 : }
6921 0 : if( w==21 )
6922 : {
6923 0 : r = -4.359e+00;
6924 : }
6925 0 : if( w==20 )
6926 : {
6927 0 : r = -4.531e+00;
6928 : }
6929 0 : if( w==19 )
6930 : {
6931 0 : r = -4.707e+00;
6932 : }
6933 0 : if( w==18 )
6934 : {
6935 0 : r = -4.888e+00;
6936 : }
6937 0 : if( w==17 )
6938 : {
6939 0 : r = -5.079e+00;
6940 : }
6941 0 : if( w==16 )
6942 : {
6943 0 : r = -5.273e+00;
6944 : }
6945 0 : if( w==15 )
6946 : {
6947 0 : r = -5.477e+00;
6948 : }
6949 0 : if( w==14 )
6950 : {
6951 0 : r = -5.697e+00;
6952 : }
6953 0 : if( w==13 )
6954 : {
6955 0 : r = -5.920e+00;
6956 : }
6957 0 : if( w==12 )
6958 : {
6959 0 : r = -6.149e+00;
6960 : }
6961 0 : if( w==11 )
6962 : {
6963 0 : r = -6.390e+00;
6964 : }
6965 0 : if( w==10 )
6966 : {
6967 0 : r = -6.636e+00;
6968 : }
6969 0 : if( w==9 )
6970 : {
6971 0 : r = -6.901e+00;
6972 : }
6973 0 : if( w==8 )
6974 : {
6975 0 : r = -7.178e+00;
6976 : }
6977 0 : if( w==7 )
6978 : {
6979 0 : r = -7.453e+00;
6980 : }
6981 0 : if( w==6 )
6982 : {
6983 0 : r = -7.758e+00;
6984 : }
6985 0 : if( w==5 )
6986 : {
6987 0 : r = -8.095e+00;
6988 : }
6989 0 : if( w==4 )
6990 : {
6991 0 : r = -8.451e+00;
6992 : }
6993 0 : if( w==3 )
6994 : {
6995 0 : r = -8.788e+00;
6996 : }
6997 0 : if( w==2 )
6998 : {
6999 0 : r = -9.299e+00;
7000 : }
7001 0 : if( w==1 )
7002 : {
7003 0 : r = -9.704e+00;
7004 : }
7005 0 : if( w<=0 )
7006 : {
7007 0 : r = -1.040e+01;
7008 : }
7009 0 : result = r;
7010 0 : return result;
7011 : }
7012 :
7013 :
7014 : /*************************************************************************
7015 : Tail(S, 16)
7016 : *************************************************************************/
7017 0 : static double wsr_w16(double s, ae_state *_state)
7018 : {
7019 : ae_int_t w;
7020 : double r;
7021 : double result;
7022 :
7023 :
7024 0 : r = (double)(0);
7025 0 : w = ae_round(-1.933908e+01*s+6.800000e+01, _state);
7026 0 : if( w>=68 )
7027 : {
7028 0 : r = -6.733e-01;
7029 : }
7030 0 : if( w==67 )
7031 : {
7032 0 : r = -7.134e-01;
7033 : }
7034 0 : if( w==66 )
7035 : {
7036 0 : r = -7.551e-01;
7037 : }
7038 0 : if( w==65 )
7039 : {
7040 0 : r = -7.986e-01;
7041 : }
7042 0 : if( w==64 )
7043 : {
7044 0 : r = -8.437e-01;
7045 : }
7046 0 : if( w==63 )
7047 : {
7048 0 : r = -8.905e-01;
7049 : }
7050 0 : if( w==62 )
7051 : {
7052 0 : r = -9.391e-01;
7053 : }
7054 0 : if( w==61 )
7055 : {
7056 0 : r = -9.895e-01;
7057 : }
7058 0 : if( w==60 )
7059 : {
7060 0 : r = -1.042e+00;
7061 : }
7062 0 : if( w==59 )
7063 : {
7064 0 : r = -1.096e+00;
7065 : }
7066 0 : if( w==58 )
7067 : {
7068 0 : r = -1.152e+00;
7069 : }
7070 0 : if( w==57 )
7071 : {
7072 0 : r = -1.210e+00;
7073 : }
7074 0 : if( w==56 )
7075 : {
7076 0 : r = -1.270e+00;
7077 : }
7078 0 : if( w==55 )
7079 : {
7080 0 : r = -1.331e+00;
7081 : }
7082 0 : if( w==54 )
7083 : {
7084 0 : r = -1.395e+00;
7085 : }
7086 0 : if( w==53 )
7087 : {
7088 0 : r = -1.462e+00;
7089 : }
7090 0 : if( w==52 )
7091 : {
7092 0 : r = -1.530e+00;
7093 : }
7094 0 : if( w==51 )
7095 : {
7096 0 : r = -1.600e+00;
7097 : }
7098 0 : if( w==50 )
7099 : {
7100 0 : r = -1.673e+00;
7101 : }
7102 0 : if( w==49 )
7103 : {
7104 0 : r = -1.748e+00;
7105 : }
7106 0 : if( w==48 )
7107 : {
7108 0 : r = -1.825e+00;
7109 : }
7110 0 : if( w==47 )
7111 : {
7112 0 : r = -1.904e+00;
7113 : }
7114 0 : if( w==46 )
7115 : {
7116 0 : r = -1.986e+00;
7117 : }
7118 0 : if( w==45 )
7119 : {
7120 0 : r = -2.071e+00;
7121 : }
7122 0 : if( w==44 )
7123 : {
7124 0 : r = -2.158e+00;
7125 : }
7126 0 : if( w==43 )
7127 : {
7128 0 : r = -2.247e+00;
7129 : }
7130 0 : if( w==42 )
7131 : {
7132 0 : r = -2.339e+00;
7133 : }
7134 0 : if( w==41 )
7135 : {
7136 0 : r = -2.434e+00;
7137 : }
7138 0 : if( w==40 )
7139 : {
7140 0 : r = -2.532e+00;
7141 : }
7142 0 : if( w==39 )
7143 : {
7144 0 : r = -2.632e+00;
7145 : }
7146 0 : if( w==38 )
7147 : {
7148 0 : r = -2.735e+00;
7149 : }
7150 0 : if( w==37 )
7151 : {
7152 0 : r = -2.842e+00;
7153 : }
7154 0 : if( w==36 )
7155 : {
7156 0 : r = -2.951e+00;
7157 : }
7158 0 : if( w==35 )
7159 : {
7160 0 : r = -3.064e+00;
7161 : }
7162 0 : if( w==34 )
7163 : {
7164 0 : r = -3.179e+00;
7165 : }
7166 0 : if( w==33 )
7167 : {
7168 0 : r = -3.298e+00;
7169 : }
7170 0 : if( w==32 )
7171 : {
7172 0 : r = -3.420e+00;
7173 : }
7174 0 : if( w==31 )
7175 : {
7176 0 : r = -3.546e+00;
7177 : }
7178 0 : if( w==30 )
7179 : {
7180 0 : r = -3.676e+00;
7181 : }
7182 0 : if( w==29 )
7183 : {
7184 0 : r = -3.810e+00;
7185 : }
7186 0 : if( w==28 )
7187 : {
7188 0 : r = -3.947e+00;
7189 : }
7190 0 : if( w==27 )
7191 : {
7192 0 : r = -4.088e+00;
7193 : }
7194 0 : if( w==26 )
7195 : {
7196 0 : r = -4.234e+00;
7197 : }
7198 0 : if( w==25 )
7199 : {
7200 0 : r = -4.383e+00;
7201 : }
7202 0 : if( w==24 )
7203 : {
7204 0 : r = -4.538e+00;
7205 : }
7206 0 : if( w==23 )
7207 : {
7208 0 : r = -4.697e+00;
7209 : }
7210 0 : if( w==22 )
7211 : {
7212 0 : r = -4.860e+00;
7213 : }
7214 0 : if( w==21 )
7215 : {
7216 0 : r = -5.029e+00;
7217 : }
7218 0 : if( w==20 )
7219 : {
7220 0 : r = -5.204e+00;
7221 : }
7222 0 : if( w==19 )
7223 : {
7224 0 : r = -5.383e+00;
7225 : }
7226 0 : if( w==18 )
7227 : {
7228 0 : r = -5.569e+00;
7229 : }
7230 0 : if( w==17 )
7231 : {
7232 0 : r = -5.762e+00;
7233 : }
7234 0 : if( w==16 )
7235 : {
7236 0 : r = -5.960e+00;
7237 : }
7238 0 : if( w==15 )
7239 : {
7240 0 : r = -6.170e+00;
7241 : }
7242 0 : if( w==14 )
7243 : {
7244 0 : r = -6.390e+00;
7245 : }
7246 0 : if( w==13 )
7247 : {
7248 0 : r = -6.613e+00;
7249 : }
7250 0 : if( w==12 )
7251 : {
7252 0 : r = -6.842e+00;
7253 : }
7254 0 : if( w==11 )
7255 : {
7256 0 : r = -7.083e+00;
7257 : }
7258 0 : if( w==10 )
7259 : {
7260 0 : r = -7.329e+00;
7261 : }
7262 0 : if( w==9 )
7263 : {
7264 0 : r = -7.594e+00;
7265 : }
7266 0 : if( w==8 )
7267 : {
7268 0 : r = -7.871e+00;
7269 : }
7270 0 : if( w==7 )
7271 : {
7272 0 : r = -8.146e+00;
7273 : }
7274 0 : if( w==6 )
7275 : {
7276 0 : r = -8.451e+00;
7277 : }
7278 0 : if( w==5 )
7279 : {
7280 0 : r = -8.788e+00;
7281 : }
7282 0 : if( w==4 )
7283 : {
7284 0 : r = -9.144e+00;
7285 : }
7286 0 : if( w==3 )
7287 : {
7288 0 : r = -9.481e+00;
7289 : }
7290 0 : if( w==2 )
7291 : {
7292 0 : r = -9.992e+00;
7293 : }
7294 0 : if( w==1 )
7295 : {
7296 0 : r = -1.040e+01;
7297 : }
7298 0 : if( w<=0 )
7299 : {
7300 0 : r = -1.109e+01;
7301 : }
7302 0 : result = r;
7303 0 : return result;
7304 : }
7305 :
7306 :
7307 : /*************************************************************************
7308 : Tail(S, 17)
7309 : *************************************************************************/
7310 0 : static double wsr_w17(double s, ae_state *_state)
7311 : {
7312 : ae_int_t w;
7313 : double r;
7314 : double result;
7315 :
7316 :
7317 0 : r = (double)(0);
7318 0 : w = ae_round(-2.112463e+01*s+7.650000e+01, _state);
7319 0 : if( w>=76 )
7320 : {
7321 0 : r = -6.931e-01;
7322 : }
7323 0 : if( w==75 )
7324 : {
7325 0 : r = -7.306e-01;
7326 : }
7327 0 : if( w==74 )
7328 : {
7329 0 : r = -7.695e-01;
7330 : }
7331 0 : if( w==73 )
7332 : {
7333 0 : r = -8.097e-01;
7334 : }
7335 0 : if( w==72 )
7336 : {
7337 0 : r = -8.514e-01;
7338 : }
7339 0 : if( w==71 )
7340 : {
7341 0 : r = -8.946e-01;
7342 : }
7343 0 : if( w==70 )
7344 : {
7345 0 : r = -9.392e-01;
7346 : }
7347 0 : if( w==69 )
7348 : {
7349 0 : r = -9.853e-01;
7350 : }
7351 0 : if( w==68 )
7352 : {
7353 0 : r = -1.033e+00;
7354 : }
7355 0 : if( w==67 )
7356 : {
7357 0 : r = -1.082e+00;
7358 : }
7359 0 : if( w==66 )
7360 : {
7361 0 : r = -1.133e+00;
7362 : }
7363 0 : if( w==65 )
7364 : {
7365 0 : r = -1.185e+00;
7366 : }
7367 0 : if( w==64 )
7368 : {
7369 0 : r = -1.240e+00;
7370 : }
7371 0 : if( w==63 )
7372 : {
7373 0 : r = -1.295e+00;
7374 : }
7375 0 : if( w==62 )
7376 : {
7377 0 : r = -1.353e+00;
7378 : }
7379 0 : if( w==61 )
7380 : {
7381 0 : r = -1.412e+00;
7382 : }
7383 0 : if( w==60 )
7384 : {
7385 0 : r = -1.473e+00;
7386 : }
7387 0 : if( w==59 )
7388 : {
7389 0 : r = -1.536e+00;
7390 : }
7391 0 : if( w==58 )
7392 : {
7393 0 : r = -1.600e+00;
7394 : }
7395 0 : if( w==57 )
7396 : {
7397 0 : r = -1.666e+00;
7398 : }
7399 0 : if( w==56 )
7400 : {
7401 0 : r = -1.735e+00;
7402 : }
7403 0 : if( w==55 )
7404 : {
7405 0 : r = -1.805e+00;
7406 : }
7407 0 : if( w==54 )
7408 : {
7409 0 : r = -1.877e+00;
7410 : }
7411 0 : if( w==53 )
7412 : {
7413 0 : r = -1.951e+00;
7414 : }
7415 0 : if( w==52 )
7416 : {
7417 0 : r = -2.028e+00;
7418 : }
7419 0 : if( w==51 )
7420 : {
7421 0 : r = -2.106e+00;
7422 : }
7423 0 : if( w==50 )
7424 : {
7425 0 : r = -2.186e+00;
7426 : }
7427 0 : if( w==49 )
7428 : {
7429 0 : r = -2.269e+00;
7430 : }
7431 0 : if( w==48 )
7432 : {
7433 0 : r = -2.353e+00;
7434 : }
7435 0 : if( w==47 )
7436 : {
7437 0 : r = -2.440e+00;
7438 : }
7439 0 : if( w==46 )
7440 : {
7441 0 : r = -2.530e+00;
7442 : }
7443 0 : if( w==45 )
7444 : {
7445 0 : r = -2.621e+00;
7446 : }
7447 0 : if( w==44 )
7448 : {
7449 0 : r = -2.715e+00;
7450 : }
7451 0 : if( w==43 )
7452 : {
7453 0 : r = -2.812e+00;
7454 : }
7455 0 : if( w==42 )
7456 : {
7457 0 : r = -2.911e+00;
7458 : }
7459 0 : if( w==41 )
7460 : {
7461 0 : r = -3.012e+00;
7462 : }
7463 0 : if( w==40 )
7464 : {
7465 0 : r = -3.116e+00;
7466 : }
7467 0 : if( w==39 )
7468 : {
7469 0 : r = -3.223e+00;
7470 : }
7471 0 : if( w==38 )
7472 : {
7473 0 : r = -3.332e+00;
7474 : }
7475 0 : if( w==37 )
7476 : {
7477 0 : r = -3.445e+00;
7478 : }
7479 0 : if( w==36 )
7480 : {
7481 0 : r = -3.560e+00;
7482 : }
7483 0 : if( w==35 )
7484 : {
7485 0 : r = -3.678e+00;
7486 : }
7487 0 : if( w==34 )
7488 : {
7489 0 : r = -3.799e+00;
7490 : }
7491 0 : if( w==33 )
7492 : {
7493 0 : r = -3.924e+00;
7494 : }
7495 0 : if( w==32 )
7496 : {
7497 0 : r = -4.052e+00;
7498 : }
7499 0 : if( w==31 )
7500 : {
7501 0 : r = -4.183e+00;
7502 : }
7503 0 : if( w==30 )
7504 : {
7505 0 : r = -4.317e+00;
7506 : }
7507 0 : if( w==29 )
7508 : {
7509 0 : r = -4.456e+00;
7510 : }
7511 0 : if( w==28 )
7512 : {
7513 0 : r = -4.597e+00;
7514 : }
7515 0 : if( w==27 )
7516 : {
7517 0 : r = -4.743e+00;
7518 : }
7519 0 : if( w==26 )
7520 : {
7521 0 : r = -4.893e+00;
7522 : }
7523 0 : if( w==25 )
7524 : {
7525 0 : r = -5.047e+00;
7526 : }
7527 0 : if( w==24 )
7528 : {
7529 0 : r = -5.204e+00;
7530 : }
7531 0 : if( w==23 )
7532 : {
7533 0 : r = -5.367e+00;
7534 : }
7535 0 : if( w==22 )
7536 : {
7537 0 : r = -5.534e+00;
7538 : }
7539 0 : if( w==21 )
7540 : {
7541 0 : r = -5.706e+00;
7542 : }
7543 0 : if( w==20 )
7544 : {
7545 0 : r = -5.884e+00;
7546 : }
7547 0 : if( w==19 )
7548 : {
7549 0 : r = -6.066e+00;
7550 : }
7551 0 : if( w==18 )
7552 : {
7553 0 : r = -6.254e+00;
7554 : }
7555 0 : if( w==17 )
7556 : {
7557 0 : r = -6.451e+00;
7558 : }
7559 0 : if( w==16 )
7560 : {
7561 0 : r = -6.654e+00;
7562 : }
7563 0 : if( w==15 )
7564 : {
7565 0 : r = -6.864e+00;
7566 : }
7567 0 : if( w==14 )
7568 : {
7569 0 : r = -7.083e+00;
7570 : }
7571 0 : if( w==13 )
7572 : {
7573 0 : r = -7.306e+00;
7574 : }
7575 0 : if( w==12 )
7576 : {
7577 0 : r = -7.535e+00;
7578 : }
7579 0 : if( w==11 )
7580 : {
7581 0 : r = -7.776e+00;
7582 : }
7583 0 : if( w==10 )
7584 : {
7585 0 : r = -8.022e+00;
7586 : }
7587 0 : if( w==9 )
7588 : {
7589 0 : r = -8.287e+00;
7590 : }
7591 0 : if( w==8 )
7592 : {
7593 0 : r = -8.565e+00;
7594 : }
7595 0 : if( w==7 )
7596 : {
7597 0 : r = -8.839e+00;
7598 : }
7599 0 : if( w==6 )
7600 : {
7601 0 : r = -9.144e+00;
7602 : }
7603 0 : if( w==5 )
7604 : {
7605 0 : r = -9.481e+00;
7606 : }
7607 0 : if( w==4 )
7608 : {
7609 0 : r = -9.838e+00;
7610 : }
7611 0 : if( w==3 )
7612 : {
7613 0 : r = -1.017e+01;
7614 : }
7615 0 : if( w==2 )
7616 : {
7617 0 : r = -1.068e+01;
7618 : }
7619 0 : if( w==1 )
7620 : {
7621 0 : r = -1.109e+01;
7622 : }
7623 0 : if( w<=0 )
7624 : {
7625 0 : r = -1.178e+01;
7626 : }
7627 0 : result = r;
7628 0 : return result;
7629 : }
7630 :
7631 :
7632 : /*************************************************************************
7633 : Tail(S, 18)
7634 : *************************************************************************/
7635 0 : static double wsr_w18(double s, ae_state *_state)
7636 : {
7637 : ae_int_t w;
7638 : double r;
7639 : double result;
7640 :
7641 :
7642 0 : r = (double)(0);
7643 0 : w = ae_round(-2.296193e+01*s+8.550000e+01, _state);
7644 0 : if( w>=85 )
7645 : {
7646 0 : r = -6.931e-01;
7647 : }
7648 0 : if( w==84 )
7649 : {
7650 0 : r = -7.276e-01;
7651 : }
7652 0 : if( w==83 )
7653 : {
7654 0 : r = -7.633e-01;
7655 : }
7656 0 : if( w==82 )
7657 : {
7658 0 : r = -8.001e-01;
7659 : }
7660 0 : if( w==81 )
7661 : {
7662 0 : r = -8.381e-01;
7663 : }
7664 0 : if( w==80 )
7665 : {
7666 0 : r = -8.774e-01;
7667 : }
7668 0 : if( w==79 )
7669 : {
7670 0 : r = -9.179e-01;
7671 : }
7672 0 : if( w==78 )
7673 : {
7674 0 : r = -9.597e-01;
7675 : }
7676 0 : if( w==77 )
7677 : {
7678 0 : r = -1.003e+00;
7679 : }
7680 0 : if( w==76 )
7681 : {
7682 0 : r = -1.047e+00;
7683 : }
7684 0 : if( w==75 )
7685 : {
7686 0 : r = -1.093e+00;
7687 : }
7688 0 : if( w==74 )
7689 : {
7690 0 : r = -1.140e+00;
7691 : }
7692 0 : if( w==73 )
7693 : {
7694 0 : r = -1.188e+00;
7695 : }
7696 0 : if( w==72 )
7697 : {
7698 0 : r = -1.238e+00;
7699 : }
7700 0 : if( w==71 )
7701 : {
7702 0 : r = -1.289e+00;
7703 : }
7704 0 : if( w==70 )
7705 : {
7706 0 : r = -1.342e+00;
7707 : }
7708 0 : if( w==69 )
7709 : {
7710 0 : r = -1.396e+00;
7711 : }
7712 0 : if( w==68 )
7713 : {
7714 0 : r = -1.452e+00;
7715 : }
7716 0 : if( w==67 )
7717 : {
7718 0 : r = -1.509e+00;
7719 : }
7720 0 : if( w==66 )
7721 : {
7722 0 : r = -1.568e+00;
7723 : }
7724 0 : if( w==65 )
7725 : {
7726 0 : r = -1.628e+00;
7727 : }
7728 0 : if( w==64 )
7729 : {
7730 0 : r = -1.690e+00;
7731 : }
7732 0 : if( w==63 )
7733 : {
7734 0 : r = -1.753e+00;
7735 : }
7736 0 : if( w==62 )
7737 : {
7738 0 : r = -1.818e+00;
7739 : }
7740 0 : if( w==61 )
7741 : {
7742 0 : r = -1.885e+00;
7743 : }
7744 0 : if( w==60 )
7745 : {
7746 0 : r = -1.953e+00;
7747 : }
7748 0 : if( w==59 )
7749 : {
7750 0 : r = -2.023e+00;
7751 : }
7752 0 : if( w==58 )
7753 : {
7754 0 : r = -2.095e+00;
7755 : }
7756 0 : if( w==57 )
7757 : {
7758 0 : r = -2.168e+00;
7759 : }
7760 0 : if( w==56 )
7761 : {
7762 0 : r = -2.244e+00;
7763 : }
7764 0 : if( w==55 )
7765 : {
7766 0 : r = -2.321e+00;
7767 : }
7768 0 : if( w==54 )
7769 : {
7770 0 : r = -2.400e+00;
7771 : }
7772 0 : if( w==53 )
7773 : {
7774 0 : r = -2.481e+00;
7775 : }
7776 0 : if( w==52 )
7777 : {
7778 0 : r = -2.564e+00;
7779 : }
7780 0 : if( w==51 )
7781 : {
7782 0 : r = -2.648e+00;
7783 : }
7784 0 : if( w==50 )
7785 : {
7786 0 : r = -2.735e+00;
7787 : }
7788 0 : if( w==49 )
7789 : {
7790 0 : r = -2.824e+00;
7791 : }
7792 0 : if( w==48 )
7793 : {
7794 0 : r = -2.915e+00;
7795 : }
7796 0 : if( w==47 )
7797 : {
7798 0 : r = -3.008e+00;
7799 : }
7800 0 : if( w==46 )
7801 : {
7802 0 : r = -3.104e+00;
7803 : }
7804 0 : if( w==45 )
7805 : {
7806 0 : r = -3.201e+00;
7807 : }
7808 0 : if( w==44 )
7809 : {
7810 0 : r = -3.301e+00;
7811 : }
7812 0 : if( w==43 )
7813 : {
7814 0 : r = -3.403e+00;
7815 : }
7816 0 : if( w==42 )
7817 : {
7818 0 : r = -3.508e+00;
7819 : }
7820 0 : if( w==41 )
7821 : {
7822 0 : r = -3.615e+00;
7823 : }
7824 0 : if( w==40 )
7825 : {
7826 0 : r = -3.724e+00;
7827 : }
7828 0 : if( w==39 )
7829 : {
7830 0 : r = -3.836e+00;
7831 : }
7832 0 : if( w==38 )
7833 : {
7834 0 : r = -3.950e+00;
7835 : }
7836 0 : if( w==37 )
7837 : {
7838 0 : r = -4.068e+00;
7839 : }
7840 0 : if( w==36 )
7841 : {
7842 0 : r = -4.188e+00;
7843 : }
7844 0 : if( w==35 )
7845 : {
7846 0 : r = -4.311e+00;
7847 : }
7848 0 : if( w==34 )
7849 : {
7850 0 : r = -4.437e+00;
7851 : }
7852 0 : if( w==33 )
7853 : {
7854 0 : r = -4.565e+00;
7855 : }
7856 0 : if( w==32 )
7857 : {
7858 0 : r = -4.698e+00;
7859 : }
7860 0 : if( w==31 )
7861 : {
7862 0 : r = -4.833e+00;
7863 : }
7864 0 : if( w==30 )
7865 : {
7866 0 : r = -4.971e+00;
7867 : }
7868 0 : if( w==29 )
7869 : {
7870 0 : r = -5.113e+00;
7871 : }
7872 0 : if( w==28 )
7873 : {
7874 0 : r = -5.258e+00;
7875 : }
7876 0 : if( w==27 )
7877 : {
7878 0 : r = -5.408e+00;
7879 : }
7880 0 : if( w==26 )
7881 : {
7882 0 : r = -5.561e+00;
7883 : }
7884 0 : if( w==25 )
7885 : {
7886 0 : r = -5.717e+00;
7887 : }
7888 0 : if( w==24 )
7889 : {
7890 0 : r = -5.878e+00;
7891 : }
7892 0 : if( w==23 )
7893 : {
7894 0 : r = -6.044e+00;
7895 : }
7896 0 : if( w==22 )
7897 : {
7898 0 : r = -6.213e+00;
7899 : }
7900 0 : if( w==21 )
7901 : {
7902 0 : r = -6.388e+00;
7903 : }
7904 0 : if( w==20 )
7905 : {
7906 0 : r = -6.569e+00;
7907 : }
7908 0 : if( w==19 )
7909 : {
7910 0 : r = -6.753e+00;
7911 : }
7912 0 : if( w==18 )
7913 : {
7914 0 : r = -6.943e+00;
7915 : }
7916 0 : if( w==17 )
7917 : {
7918 0 : r = -7.144e+00;
7919 : }
7920 0 : if( w==16 )
7921 : {
7922 0 : r = -7.347e+00;
7923 : }
7924 0 : if( w==15 )
7925 : {
7926 0 : r = -7.557e+00;
7927 : }
7928 0 : if( w==14 )
7929 : {
7930 0 : r = -7.776e+00;
7931 : }
7932 0 : if( w==13 )
7933 : {
7934 0 : r = -7.999e+00;
7935 : }
7936 0 : if( w==12 )
7937 : {
7938 0 : r = -8.228e+00;
7939 : }
7940 0 : if( w==11 )
7941 : {
7942 0 : r = -8.469e+00;
7943 : }
7944 0 : if( w==10 )
7945 : {
7946 0 : r = -8.715e+00;
7947 : }
7948 0 : if( w==9 )
7949 : {
7950 0 : r = -8.980e+00;
7951 : }
7952 0 : if( w==8 )
7953 : {
7954 0 : r = -9.258e+00;
7955 : }
7956 0 : if( w==7 )
7957 : {
7958 0 : r = -9.532e+00;
7959 : }
7960 0 : if( w==6 )
7961 : {
7962 0 : r = -9.838e+00;
7963 : }
7964 0 : if( w==5 )
7965 : {
7966 0 : r = -1.017e+01;
7967 : }
7968 0 : if( w==4 )
7969 : {
7970 0 : r = -1.053e+01;
7971 : }
7972 0 : if( w==3 )
7973 : {
7974 0 : r = -1.087e+01;
7975 : }
7976 0 : if( w==2 )
7977 : {
7978 0 : r = -1.138e+01;
7979 : }
7980 0 : if( w==1 )
7981 : {
7982 0 : r = -1.178e+01;
7983 : }
7984 0 : if( w<=0 )
7985 : {
7986 0 : r = -1.248e+01;
7987 : }
7988 0 : result = r;
7989 0 : return result;
7990 : }
7991 :
7992 :
7993 : /*************************************************************************
7994 : Tail(S, 19)
7995 : *************************************************************************/
7996 0 : static double wsr_w19(double s, ae_state *_state)
7997 : {
7998 : ae_int_t w;
7999 : double r;
8000 : double result;
8001 :
8002 :
8003 0 : r = (double)(0);
8004 0 : w = ae_round(-2.484955e+01*s+9.500000e+01, _state);
8005 0 : if( w>=95 )
8006 : {
8007 0 : r = -6.776e-01;
8008 : }
8009 0 : if( w==94 )
8010 : {
8011 0 : r = -7.089e-01;
8012 : }
8013 0 : if( w==93 )
8014 : {
8015 0 : r = -7.413e-01;
8016 : }
8017 0 : if( w==92 )
8018 : {
8019 0 : r = -7.747e-01;
8020 : }
8021 0 : if( w==91 )
8022 : {
8023 0 : r = -8.090e-01;
8024 : }
8025 0 : if( w==90 )
8026 : {
8027 0 : r = -8.445e-01;
8028 : }
8029 0 : if( w==89 )
8030 : {
8031 0 : r = -8.809e-01;
8032 : }
8033 0 : if( w==88 )
8034 : {
8035 0 : r = -9.185e-01;
8036 : }
8037 0 : if( w==87 )
8038 : {
8039 0 : r = -9.571e-01;
8040 : }
8041 0 : if( w==86 )
8042 : {
8043 0 : r = -9.968e-01;
8044 : }
8045 0 : if( w==85 )
8046 : {
8047 0 : r = -1.038e+00;
8048 : }
8049 0 : if( w==84 )
8050 : {
8051 0 : r = -1.080e+00;
8052 : }
8053 0 : if( w==83 )
8054 : {
8055 0 : r = -1.123e+00;
8056 : }
8057 0 : if( w==82 )
8058 : {
8059 0 : r = -1.167e+00;
8060 : }
8061 0 : if( w==81 )
8062 : {
8063 0 : r = -1.213e+00;
8064 : }
8065 0 : if( w==80 )
8066 : {
8067 0 : r = -1.259e+00;
8068 : }
8069 0 : if( w==79 )
8070 : {
8071 0 : r = -1.307e+00;
8072 : }
8073 0 : if( w==78 )
8074 : {
8075 0 : r = -1.356e+00;
8076 : }
8077 0 : if( w==77 )
8078 : {
8079 0 : r = -1.407e+00;
8080 : }
8081 0 : if( w==76 )
8082 : {
8083 0 : r = -1.458e+00;
8084 : }
8085 0 : if( w==75 )
8086 : {
8087 0 : r = -1.511e+00;
8088 : }
8089 0 : if( w==74 )
8090 : {
8091 0 : r = -1.565e+00;
8092 : }
8093 0 : if( w==73 )
8094 : {
8095 0 : r = -1.621e+00;
8096 : }
8097 0 : if( w==72 )
8098 : {
8099 0 : r = -1.678e+00;
8100 : }
8101 0 : if( w==71 )
8102 : {
8103 0 : r = -1.736e+00;
8104 : }
8105 0 : if( w==70 )
8106 : {
8107 0 : r = -1.796e+00;
8108 : }
8109 0 : if( w==69 )
8110 : {
8111 0 : r = -1.857e+00;
8112 : }
8113 0 : if( w==68 )
8114 : {
8115 0 : r = -1.919e+00;
8116 : }
8117 0 : if( w==67 )
8118 : {
8119 0 : r = -1.983e+00;
8120 : }
8121 0 : if( w==66 )
8122 : {
8123 0 : r = -2.048e+00;
8124 : }
8125 0 : if( w==65 )
8126 : {
8127 0 : r = -2.115e+00;
8128 : }
8129 0 : if( w==64 )
8130 : {
8131 0 : r = -2.183e+00;
8132 : }
8133 0 : if( w==63 )
8134 : {
8135 0 : r = -2.253e+00;
8136 : }
8137 0 : if( w==62 )
8138 : {
8139 0 : r = -2.325e+00;
8140 : }
8141 0 : if( w==61 )
8142 : {
8143 0 : r = -2.398e+00;
8144 : }
8145 0 : if( w==60 )
8146 : {
8147 0 : r = -2.472e+00;
8148 : }
8149 0 : if( w==59 )
8150 : {
8151 0 : r = -2.548e+00;
8152 : }
8153 0 : if( w==58 )
8154 : {
8155 0 : r = -2.626e+00;
8156 : }
8157 0 : if( w==57 )
8158 : {
8159 0 : r = -2.706e+00;
8160 : }
8161 0 : if( w==56 )
8162 : {
8163 0 : r = -2.787e+00;
8164 : }
8165 0 : if( w==55 )
8166 : {
8167 0 : r = -2.870e+00;
8168 : }
8169 0 : if( w==54 )
8170 : {
8171 0 : r = -2.955e+00;
8172 : }
8173 0 : if( w==53 )
8174 : {
8175 0 : r = -3.042e+00;
8176 : }
8177 0 : if( w==52 )
8178 : {
8179 0 : r = -3.130e+00;
8180 : }
8181 0 : if( w==51 )
8182 : {
8183 0 : r = -3.220e+00;
8184 : }
8185 0 : if( w==50 )
8186 : {
8187 0 : r = -3.313e+00;
8188 : }
8189 0 : if( w==49 )
8190 : {
8191 0 : r = -3.407e+00;
8192 : }
8193 0 : if( w==48 )
8194 : {
8195 0 : r = -3.503e+00;
8196 : }
8197 0 : if( w==47 )
8198 : {
8199 0 : r = -3.601e+00;
8200 : }
8201 0 : if( w==46 )
8202 : {
8203 0 : r = -3.702e+00;
8204 : }
8205 0 : if( w==45 )
8206 : {
8207 0 : r = -3.804e+00;
8208 : }
8209 0 : if( w==44 )
8210 : {
8211 0 : r = -3.909e+00;
8212 : }
8213 0 : if( w==43 )
8214 : {
8215 0 : r = -4.015e+00;
8216 : }
8217 0 : if( w==42 )
8218 : {
8219 0 : r = -4.125e+00;
8220 : }
8221 0 : if( w==41 )
8222 : {
8223 0 : r = -4.236e+00;
8224 : }
8225 0 : if( w==40 )
8226 : {
8227 0 : r = -4.350e+00;
8228 : }
8229 0 : if( w==39 )
8230 : {
8231 0 : r = -4.466e+00;
8232 : }
8233 0 : if( w==38 )
8234 : {
8235 0 : r = -4.585e+00;
8236 : }
8237 0 : if( w==37 )
8238 : {
8239 0 : r = -4.706e+00;
8240 : }
8241 0 : if( w==36 )
8242 : {
8243 0 : r = -4.830e+00;
8244 : }
8245 0 : if( w==35 )
8246 : {
8247 0 : r = -4.957e+00;
8248 : }
8249 0 : if( w==34 )
8250 : {
8251 0 : r = -5.086e+00;
8252 : }
8253 0 : if( w==33 )
8254 : {
8255 0 : r = -5.219e+00;
8256 : }
8257 0 : if( w==32 )
8258 : {
8259 0 : r = -5.355e+00;
8260 : }
8261 0 : if( w==31 )
8262 : {
8263 0 : r = -5.493e+00;
8264 : }
8265 0 : if( w==30 )
8266 : {
8267 0 : r = -5.634e+00;
8268 : }
8269 0 : if( w==29 )
8270 : {
8271 0 : r = -5.780e+00;
8272 : }
8273 0 : if( w==28 )
8274 : {
8275 0 : r = -5.928e+00;
8276 : }
8277 0 : if( w==27 )
8278 : {
8279 0 : r = -6.080e+00;
8280 : }
8281 0 : if( w==26 )
8282 : {
8283 0 : r = -6.235e+00;
8284 : }
8285 0 : if( w==25 )
8286 : {
8287 0 : r = -6.394e+00;
8288 : }
8289 0 : if( w==24 )
8290 : {
8291 0 : r = -6.558e+00;
8292 : }
8293 0 : if( w==23 )
8294 : {
8295 0 : r = -6.726e+00;
8296 : }
8297 0 : if( w==22 )
8298 : {
8299 0 : r = -6.897e+00;
8300 : }
8301 0 : if( w==21 )
8302 : {
8303 0 : r = -7.074e+00;
8304 : }
8305 0 : if( w==20 )
8306 : {
8307 0 : r = -7.256e+00;
8308 : }
8309 0 : if( w==19 )
8310 : {
8311 0 : r = -7.443e+00;
8312 : }
8313 0 : if( w==18 )
8314 : {
8315 0 : r = -7.636e+00;
8316 : }
8317 0 : if( w==17 )
8318 : {
8319 0 : r = -7.837e+00;
8320 : }
8321 0 : if( w==16 )
8322 : {
8323 0 : r = -8.040e+00;
8324 : }
8325 0 : if( w==15 )
8326 : {
8327 0 : r = -8.250e+00;
8328 : }
8329 0 : if( w==14 )
8330 : {
8331 0 : r = -8.469e+00;
8332 : }
8333 0 : if( w==13 )
8334 : {
8335 0 : r = -8.692e+00;
8336 : }
8337 0 : if( w==12 )
8338 : {
8339 0 : r = -8.921e+00;
8340 : }
8341 0 : if( w==11 )
8342 : {
8343 0 : r = -9.162e+00;
8344 : }
8345 0 : if( w==10 )
8346 : {
8347 0 : r = -9.409e+00;
8348 : }
8349 0 : if( w==9 )
8350 : {
8351 0 : r = -9.673e+00;
8352 : }
8353 0 : if( w==8 )
8354 : {
8355 0 : r = -9.951e+00;
8356 : }
8357 0 : if( w==7 )
8358 : {
8359 0 : r = -1.023e+01;
8360 : }
8361 0 : if( w==6 )
8362 : {
8363 0 : r = -1.053e+01;
8364 : }
8365 0 : if( w==5 )
8366 : {
8367 0 : r = -1.087e+01;
8368 : }
8369 0 : if( w==4 )
8370 : {
8371 0 : r = -1.122e+01;
8372 : }
8373 0 : if( w==3 )
8374 : {
8375 0 : r = -1.156e+01;
8376 : }
8377 0 : if( w==2 )
8378 : {
8379 0 : r = -1.207e+01;
8380 : }
8381 0 : if( w==1 )
8382 : {
8383 0 : r = -1.248e+01;
8384 : }
8385 0 : if( w<=0 )
8386 : {
8387 0 : r = -1.317e+01;
8388 : }
8389 0 : result = r;
8390 0 : return result;
8391 : }
8392 :
8393 :
8394 : /*************************************************************************
8395 : Tail(S, 20)
8396 : *************************************************************************/
8397 0 : static double wsr_w20(double s, ae_state *_state)
8398 : {
8399 : ae_int_t w;
8400 : double r;
8401 : double result;
8402 :
8403 :
8404 0 : r = (double)(0);
8405 0 : w = ae_round(-2.678619e+01*s+1.050000e+02, _state);
8406 0 : if( w>=105 )
8407 : {
8408 0 : r = -6.787e-01;
8409 : }
8410 0 : if( w==104 )
8411 : {
8412 0 : r = -7.078e-01;
8413 : }
8414 0 : if( w==103 )
8415 : {
8416 0 : r = -7.378e-01;
8417 : }
8418 0 : if( w==102 )
8419 : {
8420 0 : r = -7.686e-01;
8421 : }
8422 0 : if( w==101 )
8423 : {
8424 0 : r = -8.004e-01;
8425 : }
8426 0 : if( w==100 )
8427 : {
8428 0 : r = -8.330e-01;
8429 : }
8430 0 : if( w==99 )
8431 : {
8432 0 : r = -8.665e-01;
8433 : }
8434 0 : if( w==98 )
8435 : {
8436 0 : r = -9.010e-01;
8437 : }
8438 0 : if( w==97 )
8439 : {
8440 0 : r = -9.363e-01;
8441 : }
8442 0 : if( w==96 )
8443 : {
8444 0 : r = -9.726e-01;
8445 : }
8446 0 : if( w==95 )
8447 : {
8448 0 : r = -1.010e+00;
8449 : }
8450 0 : if( w==94 )
8451 : {
8452 0 : r = -1.048e+00;
8453 : }
8454 0 : if( w==93 )
8455 : {
8456 0 : r = -1.087e+00;
8457 : }
8458 0 : if( w==92 )
8459 : {
8460 0 : r = -1.128e+00;
8461 : }
8462 0 : if( w==91 )
8463 : {
8464 0 : r = -1.169e+00;
8465 : }
8466 0 : if( w==90 )
8467 : {
8468 0 : r = -1.211e+00;
8469 : }
8470 0 : if( w==89 )
8471 : {
8472 0 : r = -1.254e+00;
8473 : }
8474 0 : if( w==88 )
8475 : {
8476 0 : r = -1.299e+00;
8477 : }
8478 0 : if( w==87 )
8479 : {
8480 0 : r = -1.344e+00;
8481 : }
8482 0 : if( w==86 )
8483 : {
8484 0 : r = -1.390e+00;
8485 : }
8486 0 : if( w==85 )
8487 : {
8488 0 : r = -1.438e+00;
8489 : }
8490 0 : if( w==84 )
8491 : {
8492 0 : r = -1.486e+00;
8493 : }
8494 0 : if( w==83 )
8495 : {
8496 0 : r = -1.536e+00;
8497 : }
8498 0 : if( w==82 )
8499 : {
8500 0 : r = -1.587e+00;
8501 : }
8502 0 : if( w==81 )
8503 : {
8504 0 : r = -1.639e+00;
8505 : }
8506 0 : if( w==80 )
8507 : {
8508 0 : r = -1.692e+00;
8509 : }
8510 0 : if( w==79 )
8511 : {
8512 0 : r = -1.746e+00;
8513 : }
8514 0 : if( w==78 )
8515 : {
8516 0 : r = -1.802e+00;
8517 : }
8518 0 : if( w==77 )
8519 : {
8520 0 : r = -1.859e+00;
8521 : }
8522 0 : if( w==76 )
8523 : {
8524 0 : r = -1.916e+00;
8525 : }
8526 0 : if( w==75 )
8527 : {
8528 0 : r = -1.976e+00;
8529 : }
8530 0 : if( w==74 )
8531 : {
8532 0 : r = -2.036e+00;
8533 : }
8534 0 : if( w==73 )
8535 : {
8536 0 : r = -2.098e+00;
8537 : }
8538 0 : if( w==72 )
8539 : {
8540 0 : r = -2.161e+00;
8541 : }
8542 0 : if( w==71 )
8543 : {
8544 0 : r = -2.225e+00;
8545 : }
8546 0 : if( w==70 )
8547 : {
8548 0 : r = -2.290e+00;
8549 : }
8550 0 : if( w==69 )
8551 : {
8552 0 : r = -2.357e+00;
8553 : }
8554 0 : if( w==68 )
8555 : {
8556 0 : r = -2.426e+00;
8557 : }
8558 0 : if( w==67 )
8559 : {
8560 0 : r = -2.495e+00;
8561 : }
8562 0 : if( w==66 )
8563 : {
8564 0 : r = -2.566e+00;
8565 : }
8566 0 : if( w==65 )
8567 : {
8568 0 : r = -2.639e+00;
8569 : }
8570 0 : if( w==64 )
8571 : {
8572 0 : r = -2.713e+00;
8573 : }
8574 0 : if( w==63 )
8575 : {
8576 0 : r = -2.788e+00;
8577 : }
8578 0 : if( w==62 )
8579 : {
8580 0 : r = -2.865e+00;
8581 : }
8582 0 : if( w==61 )
8583 : {
8584 0 : r = -2.943e+00;
8585 : }
8586 0 : if( w==60 )
8587 : {
8588 0 : r = -3.023e+00;
8589 : }
8590 0 : if( w==59 )
8591 : {
8592 0 : r = -3.104e+00;
8593 : }
8594 0 : if( w==58 )
8595 : {
8596 0 : r = -3.187e+00;
8597 : }
8598 0 : if( w==57 )
8599 : {
8600 0 : r = -3.272e+00;
8601 : }
8602 0 : if( w==56 )
8603 : {
8604 0 : r = -3.358e+00;
8605 : }
8606 0 : if( w==55 )
8607 : {
8608 0 : r = -3.446e+00;
8609 : }
8610 0 : if( w==54 )
8611 : {
8612 0 : r = -3.536e+00;
8613 : }
8614 0 : if( w==53 )
8615 : {
8616 0 : r = -3.627e+00;
8617 : }
8618 0 : if( w==52 )
8619 : {
8620 0 : r = -3.721e+00;
8621 : }
8622 0 : if( w==51 )
8623 : {
8624 0 : r = -3.815e+00;
8625 : }
8626 0 : if( w==50 )
8627 : {
8628 0 : r = -3.912e+00;
8629 : }
8630 0 : if( w==49 )
8631 : {
8632 0 : r = -4.011e+00;
8633 : }
8634 0 : if( w==48 )
8635 : {
8636 0 : r = -4.111e+00;
8637 : }
8638 0 : if( w==47 )
8639 : {
8640 0 : r = -4.214e+00;
8641 : }
8642 0 : if( w==46 )
8643 : {
8644 0 : r = -4.318e+00;
8645 : }
8646 0 : if( w==45 )
8647 : {
8648 0 : r = -4.425e+00;
8649 : }
8650 0 : if( w==44 )
8651 : {
8652 0 : r = -4.534e+00;
8653 : }
8654 0 : if( w==43 )
8655 : {
8656 0 : r = -4.644e+00;
8657 : }
8658 0 : if( w==42 )
8659 : {
8660 0 : r = -4.757e+00;
8661 : }
8662 0 : if( w==41 )
8663 : {
8664 0 : r = -4.872e+00;
8665 : }
8666 0 : if( w==40 )
8667 : {
8668 0 : r = -4.990e+00;
8669 : }
8670 0 : if( w==39 )
8671 : {
8672 0 : r = -5.109e+00;
8673 : }
8674 0 : if( w==38 )
8675 : {
8676 0 : r = -5.232e+00;
8677 : }
8678 0 : if( w==37 )
8679 : {
8680 0 : r = -5.356e+00;
8681 : }
8682 0 : if( w==36 )
8683 : {
8684 0 : r = -5.484e+00;
8685 : }
8686 0 : if( w==35 )
8687 : {
8688 0 : r = -5.614e+00;
8689 : }
8690 0 : if( w==34 )
8691 : {
8692 0 : r = -5.746e+00;
8693 : }
8694 0 : if( w==33 )
8695 : {
8696 0 : r = -5.882e+00;
8697 : }
8698 0 : if( w==32 )
8699 : {
8700 0 : r = -6.020e+00;
8701 : }
8702 0 : if( w==31 )
8703 : {
8704 0 : r = -6.161e+00;
8705 : }
8706 0 : if( w==30 )
8707 : {
8708 0 : r = -6.305e+00;
8709 : }
8710 0 : if( w==29 )
8711 : {
8712 0 : r = -6.453e+00;
8713 : }
8714 0 : if( w==28 )
8715 : {
8716 0 : r = -6.603e+00;
8717 : }
8718 0 : if( w==27 )
8719 : {
8720 0 : r = -6.757e+00;
8721 : }
8722 0 : if( w==26 )
8723 : {
8724 0 : r = -6.915e+00;
8725 : }
8726 0 : if( w==25 )
8727 : {
8728 0 : r = -7.076e+00;
8729 : }
8730 0 : if( w==24 )
8731 : {
8732 0 : r = -7.242e+00;
8733 : }
8734 0 : if( w==23 )
8735 : {
8736 0 : r = -7.411e+00;
8737 : }
8738 0 : if( w==22 )
8739 : {
8740 0 : r = -7.584e+00;
8741 : }
8742 0 : if( w==21 )
8743 : {
8744 0 : r = -7.763e+00;
8745 : }
8746 0 : if( w==20 )
8747 : {
8748 0 : r = -7.947e+00;
8749 : }
8750 0 : if( w==19 )
8751 : {
8752 0 : r = -8.136e+00;
8753 : }
8754 0 : if( w==18 )
8755 : {
8756 0 : r = -8.330e+00;
8757 : }
8758 0 : if( w==17 )
8759 : {
8760 0 : r = -8.530e+00;
8761 : }
8762 0 : if( w==16 )
8763 : {
8764 0 : r = -8.733e+00;
8765 : }
8766 0 : if( w==15 )
8767 : {
8768 0 : r = -8.943e+00;
8769 : }
8770 0 : if( w==14 )
8771 : {
8772 0 : r = -9.162e+00;
8773 : }
8774 0 : if( w==13 )
8775 : {
8776 0 : r = -9.386e+00;
8777 : }
8778 0 : if( w==12 )
8779 : {
8780 0 : r = -9.614e+00;
8781 : }
8782 0 : if( w==11 )
8783 : {
8784 0 : r = -9.856e+00;
8785 : }
8786 0 : if( w==10 )
8787 : {
8788 0 : r = -1.010e+01;
8789 : }
8790 0 : if( w==9 )
8791 : {
8792 0 : r = -1.037e+01;
8793 : }
8794 0 : if( w==8 )
8795 : {
8796 0 : r = -1.064e+01;
8797 : }
8798 0 : if( w==7 )
8799 : {
8800 0 : r = -1.092e+01;
8801 : }
8802 0 : if( w==6 )
8803 : {
8804 0 : r = -1.122e+01;
8805 : }
8806 0 : if( w==5 )
8807 : {
8808 0 : r = -1.156e+01;
8809 : }
8810 0 : if( w==4 )
8811 : {
8812 0 : r = -1.192e+01;
8813 : }
8814 0 : if( w==3 )
8815 : {
8816 0 : r = -1.225e+01;
8817 : }
8818 0 : if( w==2 )
8819 : {
8820 0 : r = -1.276e+01;
8821 : }
8822 0 : if( w==1 )
8823 : {
8824 0 : r = -1.317e+01;
8825 : }
8826 0 : if( w<=0 )
8827 : {
8828 0 : r = -1.386e+01;
8829 : }
8830 0 : result = r;
8831 0 : return result;
8832 : }
8833 :
8834 :
8835 : /*************************************************************************
8836 : Tail(S, 21)
8837 : *************************************************************************/
8838 0 : static double wsr_w21(double s, ae_state *_state)
8839 : {
8840 : ae_int_t w;
8841 : double r;
8842 : double result;
8843 :
8844 :
8845 0 : r = (double)(0);
8846 0 : w = ae_round(-2.877064e+01*s+1.155000e+02, _state);
8847 0 : if( w>=115 )
8848 : {
8849 0 : r = -6.931e-01;
8850 : }
8851 0 : if( w==114 )
8852 : {
8853 0 : r = -7.207e-01;
8854 : }
8855 0 : if( w==113 )
8856 : {
8857 0 : r = -7.489e-01;
8858 : }
8859 0 : if( w==112 )
8860 : {
8861 0 : r = -7.779e-01;
8862 : }
8863 0 : if( w==111 )
8864 : {
8865 0 : r = -8.077e-01;
8866 : }
8867 0 : if( w==110 )
8868 : {
8869 0 : r = -8.383e-01;
8870 : }
8871 0 : if( w==109 )
8872 : {
8873 0 : r = -8.697e-01;
8874 : }
8875 0 : if( w==108 )
8876 : {
8877 0 : r = -9.018e-01;
8878 : }
8879 0 : if( w==107 )
8880 : {
8881 0 : r = -9.348e-01;
8882 : }
8883 0 : if( w==106 )
8884 : {
8885 0 : r = -9.685e-01;
8886 : }
8887 0 : if( w==105 )
8888 : {
8889 0 : r = -1.003e+00;
8890 : }
8891 0 : if( w==104 )
8892 : {
8893 0 : r = -1.039e+00;
8894 : }
8895 0 : if( w==103 )
8896 : {
8897 0 : r = -1.075e+00;
8898 : }
8899 0 : if( w==102 )
8900 : {
8901 0 : r = -1.112e+00;
8902 : }
8903 0 : if( w==101 )
8904 : {
8905 0 : r = -1.150e+00;
8906 : }
8907 0 : if( w==100 )
8908 : {
8909 0 : r = -1.189e+00;
8910 : }
8911 0 : if( w==99 )
8912 : {
8913 0 : r = -1.229e+00;
8914 : }
8915 0 : if( w==98 )
8916 : {
8917 0 : r = -1.269e+00;
8918 : }
8919 0 : if( w==97 )
8920 : {
8921 0 : r = -1.311e+00;
8922 : }
8923 0 : if( w==96 )
8924 : {
8925 0 : r = -1.353e+00;
8926 : }
8927 0 : if( w==95 )
8928 : {
8929 0 : r = -1.397e+00;
8930 : }
8931 0 : if( w==94 )
8932 : {
8933 0 : r = -1.441e+00;
8934 : }
8935 0 : if( w==93 )
8936 : {
8937 0 : r = -1.486e+00;
8938 : }
8939 0 : if( w==92 )
8940 : {
8941 0 : r = -1.533e+00;
8942 : }
8943 0 : if( w==91 )
8944 : {
8945 0 : r = -1.580e+00;
8946 : }
8947 0 : if( w==90 )
8948 : {
8949 0 : r = -1.628e+00;
8950 : }
8951 0 : if( w==89 )
8952 : {
8953 0 : r = -1.677e+00;
8954 : }
8955 0 : if( w==88 )
8956 : {
8957 0 : r = -1.728e+00;
8958 : }
8959 0 : if( w==87 )
8960 : {
8961 0 : r = -1.779e+00;
8962 : }
8963 0 : if( w==86 )
8964 : {
8965 0 : r = -1.831e+00;
8966 : }
8967 0 : if( w==85 )
8968 : {
8969 0 : r = -1.884e+00;
8970 : }
8971 0 : if( w==84 )
8972 : {
8973 0 : r = -1.939e+00;
8974 : }
8975 0 : if( w==83 )
8976 : {
8977 0 : r = -1.994e+00;
8978 : }
8979 0 : if( w==82 )
8980 : {
8981 0 : r = -2.051e+00;
8982 : }
8983 0 : if( w==81 )
8984 : {
8985 0 : r = -2.108e+00;
8986 : }
8987 0 : if( w==80 )
8988 : {
8989 0 : r = -2.167e+00;
8990 : }
8991 0 : if( w==79 )
8992 : {
8993 0 : r = -2.227e+00;
8994 : }
8995 0 : if( w==78 )
8996 : {
8997 0 : r = -2.288e+00;
8998 : }
8999 0 : if( w==77 )
9000 : {
9001 0 : r = -2.350e+00;
9002 : }
9003 0 : if( w==76 )
9004 : {
9005 0 : r = -2.414e+00;
9006 : }
9007 0 : if( w==75 )
9008 : {
9009 0 : r = -2.478e+00;
9010 : }
9011 0 : if( w==74 )
9012 : {
9013 0 : r = -2.544e+00;
9014 : }
9015 0 : if( w==73 )
9016 : {
9017 0 : r = -2.611e+00;
9018 : }
9019 0 : if( w==72 )
9020 : {
9021 0 : r = -2.679e+00;
9022 : }
9023 0 : if( w==71 )
9024 : {
9025 0 : r = -2.748e+00;
9026 : }
9027 0 : if( w==70 )
9028 : {
9029 0 : r = -2.819e+00;
9030 : }
9031 0 : if( w==69 )
9032 : {
9033 0 : r = -2.891e+00;
9034 : }
9035 0 : if( w==68 )
9036 : {
9037 0 : r = -2.964e+00;
9038 : }
9039 0 : if( w==67 )
9040 : {
9041 0 : r = -3.039e+00;
9042 : }
9043 0 : if( w==66 )
9044 : {
9045 0 : r = -3.115e+00;
9046 : }
9047 0 : if( w==65 )
9048 : {
9049 0 : r = -3.192e+00;
9050 : }
9051 0 : if( w==64 )
9052 : {
9053 0 : r = -3.270e+00;
9054 : }
9055 0 : if( w==63 )
9056 : {
9057 0 : r = -3.350e+00;
9058 : }
9059 0 : if( w==62 )
9060 : {
9061 0 : r = -3.432e+00;
9062 : }
9063 0 : if( w==61 )
9064 : {
9065 0 : r = -3.515e+00;
9066 : }
9067 0 : if( w==60 )
9068 : {
9069 0 : r = -3.599e+00;
9070 : }
9071 0 : if( w==59 )
9072 : {
9073 0 : r = -3.685e+00;
9074 : }
9075 0 : if( w==58 )
9076 : {
9077 0 : r = -3.772e+00;
9078 : }
9079 0 : if( w==57 )
9080 : {
9081 0 : r = -3.861e+00;
9082 : }
9083 0 : if( w==56 )
9084 : {
9085 0 : r = -3.952e+00;
9086 : }
9087 0 : if( w==55 )
9088 : {
9089 0 : r = -4.044e+00;
9090 : }
9091 0 : if( w==54 )
9092 : {
9093 0 : r = -4.138e+00;
9094 : }
9095 0 : if( w==53 )
9096 : {
9097 0 : r = -4.233e+00;
9098 : }
9099 0 : if( w==52 )
9100 : {
9101 0 : r = -4.330e+00;
9102 : }
9103 0 : if( w==51 )
9104 : {
9105 0 : r = -4.429e+00;
9106 : }
9107 0 : if( w==50 )
9108 : {
9109 0 : r = -4.530e+00;
9110 : }
9111 0 : if( w==49 )
9112 : {
9113 0 : r = -4.632e+00;
9114 : }
9115 0 : if( w==48 )
9116 : {
9117 0 : r = -4.736e+00;
9118 : }
9119 0 : if( w==47 )
9120 : {
9121 0 : r = -4.842e+00;
9122 : }
9123 0 : if( w==46 )
9124 : {
9125 0 : r = -4.950e+00;
9126 : }
9127 0 : if( w==45 )
9128 : {
9129 0 : r = -5.060e+00;
9130 : }
9131 0 : if( w==44 )
9132 : {
9133 0 : r = -5.172e+00;
9134 : }
9135 0 : if( w==43 )
9136 : {
9137 0 : r = -5.286e+00;
9138 : }
9139 0 : if( w==42 )
9140 : {
9141 0 : r = -5.402e+00;
9142 : }
9143 0 : if( w==41 )
9144 : {
9145 0 : r = -5.520e+00;
9146 : }
9147 0 : if( w==40 )
9148 : {
9149 0 : r = -5.641e+00;
9150 : }
9151 0 : if( w==39 )
9152 : {
9153 0 : r = -5.763e+00;
9154 : }
9155 0 : if( w==38 )
9156 : {
9157 0 : r = -5.889e+00;
9158 : }
9159 0 : if( w==37 )
9160 : {
9161 0 : r = -6.016e+00;
9162 : }
9163 0 : if( w==36 )
9164 : {
9165 0 : r = -6.146e+00;
9166 : }
9167 0 : if( w==35 )
9168 : {
9169 0 : r = -6.278e+00;
9170 : }
9171 0 : if( w==34 )
9172 : {
9173 0 : r = -6.413e+00;
9174 : }
9175 0 : if( w==33 )
9176 : {
9177 0 : r = -6.551e+00;
9178 : }
9179 0 : if( w==32 )
9180 : {
9181 0 : r = -6.692e+00;
9182 : }
9183 0 : if( w==31 )
9184 : {
9185 0 : r = -6.835e+00;
9186 : }
9187 0 : if( w==30 )
9188 : {
9189 0 : r = -6.981e+00;
9190 : }
9191 0 : if( w==29 )
9192 : {
9193 0 : r = -7.131e+00;
9194 : }
9195 0 : if( w==28 )
9196 : {
9197 0 : r = -7.283e+00;
9198 : }
9199 0 : if( w==27 )
9200 : {
9201 0 : r = -7.439e+00;
9202 : }
9203 0 : if( w==26 )
9204 : {
9205 0 : r = -7.599e+00;
9206 : }
9207 0 : if( w==25 )
9208 : {
9209 0 : r = -7.762e+00;
9210 : }
9211 0 : if( w==24 )
9212 : {
9213 0 : r = -7.928e+00;
9214 : }
9215 0 : if( w==23 )
9216 : {
9217 0 : r = -8.099e+00;
9218 : }
9219 0 : if( w==22 )
9220 : {
9221 0 : r = -8.274e+00;
9222 : }
9223 0 : if( w==21 )
9224 : {
9225 0 : r = -8.454e+00;
9226 : }
9227 0 : if( w==20 )
9228 : {
9229 0 : r = -8.640e+00;
9230 : }
9231 0 : if( w==19 )
9232 : {
9233 0 : r = -8.829e+00;
9234 : }
9235 0 : if( w==18 )
9236 : {
9237 0 : r = -9.023e+00;
9238 : }
9239 0 : if( w==17 )
9240 : {
9241 0 : r = -9.223e+00;
9242 : }
9243 0 : if( w==16 )
9244 : {
9245 0 : r = -9.426e+00;
9246 : }
9247 0 : if( w==15 )
9248 : {
9249 0 : r = -9.636e+00;
9250 : }
9251 0 : if( w==14 )
9252 : {
9253 0 : r = -9.856e+00;
9254 : }
9255 0 : if( w==13 )
9256 : {
9257 0 : r = -1.008e+01;
9258 : }
9259 0 : if( w==12 )
9260 : {
9261 0 : r = -1.031e+01;
9262 : }
9263 0 : if( w==11 )
9264 : {
9265 0 : r = -1.055e+01;
9266 : }
9267 0 : if( w==10 )
9268 : {
9269 0 : r = -1.079e+01;
9270 : }
9271 0 : if( w==9 )
9272 : {
9273 0 : r = -1.106e+01;
9274 : }
9275 0 : if( w==8 )
9276 : {
9277 0 : r = -1.134e+01;
9278 : }
9279 0 : if( w==7 )
9280 : {
9281 0 : r = -1.161e+01;
9282 : }
9283 0 : if( w==6 )
9284 : {
9285 0 : r = -1.192e+01;
9286 : }
9287 0 : if( w==5 )
9288 : {
9289 0 : r = -1.225e+01;
9290 : }
9291 0 : if( w==4 )
9292 : {
9293 0 : r = -1.261e+01;
9294 : }
9295 0 : if( w==3 )
9296 : {
9297 0 : r = -1.295e+01;
9298 : }
9299 0 : if( w==2 )
9300 : {
9301 0 : r = -1.346e+01;
9302 : }
9303 0 : if( w==1 )
9304 : {
9305 0 : r = -1.386e+01;
9306 : }
9307 0 : if( w<=0 )
9308 : {
9309 0 : r = -1.456e+01;
9310 : }
9311 0 : result = r;
9312 0 : return result;
9313 : }
9314 :
9315 :
9316 : /*************************************************************************
9317 : Tail(S, 22)
9318 : *************************************************************************/
9319 0 : static double wsr_w22(double s, ae_state *_state)
9320 : {
9321 : ae_int_t w;
9322 : double r;
9323 : double result;
9324 :
9325 :
9326 0 : r = (double)(0);
9327 0 : w = ae_round(-3.080179e+01*s+1.265000e+02, _state);
9328 0 : if( w>=126 )
9329 : {
9330 0 : r = -6.931e-01;
9331 : }
9332 0 : if( w==125 )
9333 : {
9334 0 : r = -7.189e-01;
9335 : }
9336 0 : if( w==124 )
9337 : {
9338 0 : r = -7.452e-01;
9339 : }
9340 0 : if( w==123 )
9341 : {
9342 0 : r = -7.722e-01;
9343 : }
9344 0 : if( w==122 )
9345 : {
9346 0 : r = -7.999e-01;
9347 : }
9348 0 : if( w==121 )
9349 : {
9350 0 : r = -8.283e-01;
9351 : }
9352 0 : if( w==120 )
9353 : {
9354 0 : r = -8.573e-01;
9355 : }
9356 0 : if( w==119 )
9357 : {
9358 0 : r = -8.871e-01;
9359 : }
9360 0 : if( w==118 )
9361 : {
9362 0 : r = -9.175e-01;
9363 : }
9364 0 : if( w==117 )
9365 : {
9366 0 : r = -9.486e-01;
9367 : }
9368 0 : if( w==116 )
9369 : {
9370 0 : r = -9.805e-01;
9371 : }
9372 0 : if( w==115 )
9373 : {
9374 0 : r = -1.013e+00;
9375 : }
9376 0 : if( w==114 )
9377 : {
9378 0 : r = -1.046e+00;
9379 : }
9380 0 : if( w==113 )
9381 : {
9382 0 : r = -1.080e+00;
9383 : }
9384 0 : if( w==112 )
9385 : {
9386 0 : r = -1.115e+00;
9387 : }
9388 0 : if( w==111 )
9389 : {
9390 0 : r = -1.151e+00;
9391 : }
9392 0 : if( w==110 )
9393 : {
9394 0 : r = -1.187e+00;
9395 : }
9396 0 : if( w==109 )
9397 : {
9398 0 : r = -1.224e+00;
9399 : }
9400 0 : if( w==108 )
9401 : {
9402 0 : r = -1.262e+00;
9403 : }
9404 0 : if( w==107 )
9405 : {
9406 0 : r = -1.301e+00;
9407 : }
9408 0 : if( w==106 )
9409 : {
9410 0 : r = -1.340e+00;
9411 : }
9412 0 : if( w==105 )
9413 : {
9414 0 : r = -1.381e+00;
9415 : }
9416 0 : if( w==104 )
9417 : {
9418 0 : r = -1.422e+00;
9419 : }
9420 0 : if( w==103 )
9421 : {
9422 0 : r = -1.464e+00;
9423 : }
9424 0 : if( w==102 )
9425 : {
9426 0 : r = -1.506e+00;
9427 : }
9428 0 : if( w==101 )
9429 : {
9430 0 : r = -1.550e+00;
9431 : }
9432 0 : if( w==100 )
9433 : {
9434 0 : r = -1.594e+00;
9435 : }
9436 0 : if( w==99 )
9437 : {
9438 0 : r = -1.640e+00;
9439 : }
9440 0 : if( w==98 )
9441 : {
9442 0 : r = -1.686e+00;
9443 : }
9444 0 : if( w==97 )
9445 : {
9446 0 : r = -1.733e+00;
9447 : }
9448 0 : if( w==96 )
9449 : {
9450 0 : r = -1.781e+00;
9451 : }
9452 0 : if( w==95 )
9453 : {
9454 0 : r = -1.830e+00;
9455 : }
9456 0 : if( w==94 )
9457 : {
9458 0 : r = -1.880e+00;
9459 : }
9460 0 : if( w==93 )
9461 : {
9462 0 : r = -1.930e+00;
9463 : }
9464 0 : if( w==92 )
9465 : {
9466 0 : r = -1.982e+00;
9467 : }
9468 0 : if( w==91 )
9469 : {
9470 0 : r = -2.034e+00;
9471 : }
9472 0 : if( w==90 )
9473 : {
9474 0 : r = -2.088e+00;
9475 : }
9476 0 : if( w==89 )
9477 : {
9478 0 : r = -2.142e+00;
9479 : }
9480 0 : if( w==88 )
9481 : {
9482 0 : r = -2.198e+00;
9483 : }
9484 0 : if( w==87 )
9485 : {
9486 0 : r = -2.254e+00;
9487 : }
9488 0 : if( w==86 )
9489 : {
9490 0 : r = -2.312e+00;
9491 : }
9492 0 : if( w==85 )
9493 : {
9494 0 : r = -2.370e+00;
9495 : }
9496 0 : if( w==84 )
9497 : {
9498 0 : r = -2.429e+00;
9499 : }
9500 0 : if( w==83 )
9501 : {
9502 0 : r = -2.490e+00;
9503 : }
9504 0 : if( w==82 )
9505 : {
9506 0 : r = -2.551e+00;
9507 : }
9508 0 : if( w==81 )
9509 : {
9510 0 : r = -2.614e+00;
9511 : }
9512 0 : if( w==80 )
9513 : {
9514 0 : r = -2.677e+00;
9515 : }
9516 0 : if( w==79 )
9517 : {
9518 0 : r = -2.742e+00;
9519 : }
9520 0 : if( w==78 )
9521 : {
9522 0 : r = -2.808e+00;
9523 : }
9524 0 : if( w==77 )
9525 : {
9526 0 : r = -2.875e+00;
9527 : }
9528 0 : if( w==76 )
9529 : {
9530 0 : r = -2.943e+00;
9531 : }
9532 0 : if( w==75 )
9533 : {
9534 0 : r = -3.012e+00;
9535 : }
9536 0 : if( w==74 )
9537 : {
9538 0 : r = -3.082e+00;
9539 : }
9540 0 : if( w==73 )
9541 : {
9542 0 : r = -3.153e+00;
9543 : }
9544 0 : if( w==72 )
9545 : {
9546 0 : r = -3.226e+00;
9547 : }
9548 0 : if( w==71 )
9549 : {
9550 0 : r = -3.300e+00;
9551 : }
9552 0 : if( w==70 )
9553 : {
9554 0 : r = -3.375e+00;
9555 : }
9556 0 : if( w==69 )
9557 : {
9558 0 : r = -3.451e+00;
9559 : }
9560 0 : if( w==68 )
9561 : {
9562 0 : r = -3.529e+00;
9563 : }
9564 0 : if( w==67 )
9565 : {
9566 0 : r = -3.607e+00;
9567 : }
9568 0 : if( w==66 )
9569 : {
9570 0 : r = -3.687e+00;
9571 : }
9572 0 : if( w==65 )
9573 : {
9574 0 : r = -3.769e+00;
9575 : }
9576 0 : if( w==64 )
9577 : {
9578 0 : r = -3.851e+00;
9579 : }
9580 0 : if( w==63 )
9581 : {
9582 0 : r = -3.935e+00;
9583 : }
9584 0 : if( w==62 )
9585 : {
9586 0 : r = -4.021e+00;
9587 : }
9588 0 : if( w==61 )
9589 : {
9590 0 : r = -4.108e+00;
9591 : }
9592 0 : if( w==60 )
9593 : {
9594 0 : r = -4.196e+00;
9595 : }
9596 0 : if( w==59 )
9597 : {
9598 0 : r = -4.285e+00;
9599 : }
9600 0 : if( w==58 )
9601 : {
9602 0 : r = -4.376e+00;
9603 : }
9604 0 : if( w==57 )
9605 : {
9606 0 : r = -4.469e+00;
9607 : }
9608 0 : if( w==56 )
9609 : {
9610 0 : r = -4.563e+00;
9611 : }
9612 0 : if( w==55 )
9613 : {
9614 0 : r = -4.659e+00;
9615 : }
9616 0 : if( w==54 )
9617 : {
9618 0 : r = -4.756e+00;
9619 : }
9620 0 : if( w==53 )
9621 : {
9622 0 : r = -4.855e+00;
9623 : }
9624 0 : if( w==52 )
9625 : {
9626 0 : r = -4.955e+00;
9627 : }
9628 0 : if( w==51 )
9629 : {
9630 0 : r = -5.057e+00;
9631 : }
9632 0 : if( w==50 )
9633 : {
9634 0 : r = -5.161e+00;
9635 : }
9636 0 : if( w==49 )
9637 : {
9638 0 : r = -5.266e+00;
9639 : }
9640 0 : if( w==48 )
9641 : {
9642 0 : r = -5.374e+00;
9643 : }
9644 0 : if( w==47 )
9645 : {
9646 0 : r = -5.483e+00;
9647 : }
9648 0 : if( w==46 )
9649 : {
9650 0 : r = -5.594e+00;
9651 : }
9652 0 : if( w==45 )
9653 : {
9654 0 : r = -5.706e+00;
9655 : }
9656 0 : if( w==44 )
9657 : {
9658 0 : r = -5.821e+00;
9659 : }
9660 0 : if( w==43 )
9661 : {
9662 0 : r = -5.938e+00;
9663 : }
9664 0 : if( w==42 )
9665 : {
9666 0 : r = -6.057e+00;
9667 : }
9668 0 : if( w==41 )
9669 : {
9670 0 : r = -6.177e+00;
9671 : }
9672 0 : if( w==40 )
9673 : {
9674 0 : r = -6.300e+00;
9675 : }
9676 0 : if( w==39 )
9677 : {
9678 0 : r = -6.426e+00;
9679 : }
9680 0 : if( w==38 )
9681 : {
9682 0 : r = -6.553e+00;
9683 : }
9684 0 : if( w==37 )
9685 : {
9686 0 : r = -6.683e+00;
9687 : }
9688 0 : if( w==36 )
9689 : {
9690 0 : r = -6.815e+00;
9691 : }
9692 0 : if( w==35 )
9693 : {
9694 0 : r = -6.949e+00;
9695 : }
9696 0 : if( w==34 )
9697 : {
9698 0 : r = -7.086e+00;
9699 : }
9700 0 : if( w==33 )
9701 : {
9702 0 : r = -7.226e+00;
9703 : }
9704 0 : if( w==32 )
9705 : {
9706 0 : r = -7.368e+00;
9707 : }
9708 0 : if( w==31 )
9709 : {
9710 0 : r = -7.513e+00;
9711 : }
9712 0 : if( w==30 )
9713 : {
9714 0 : r = -7.661e+00;
9715 : }
9716 0 : if( w==29 )
9717 : {
9718 0 : r = -7.813e+00;
9719 : }
9720 0 : if( w==28 )
9721 : {
9722 0 : r = -7.966e+00;
9723 : }
9724 0 : if( w==27 )
9725 : {
9726 0 : r = -8.124e+00;
9727 : }
9728 0 : if( w==26 )
9729 : {
9730 0 : r = -8.285e+00;
9731 : }
9732 0 : if( w==25 )
9733 : {
9734 0 : r = -8.449e+00;
9735 : }
9736 0 : if( w==24 )
9737 : {
9738 0 : r = -8.617e+00;
9739 : }
9740 0 : if( w==23 )
9741 : {
9742 0 : r = -8.789e+00;
9743 : }
9744 0 : if( w==22 )
9745 : {
9746 0 : r = -8.965e+00;
9747 : }
9748 0 : if( w==21 )
9749 : {
9750 0 : r = -9.147e+00;
9751 : }
9752 0 : if( w==20 )
9753 : {
9754 0 : r = -9.333e+00;
9755 : }
9756 0 : if( w==19 )
9757 : {
9758 0 : r = -9.522e+00;
9759 : }
9760 0 : if( w==18 )
9761 : {
9762 0 : r = -9.716e+00;
9763 : }
9764 0 : if( w==17 )
9765 : {
9766 0 : r = -9.917e+00;
9767 : }
9768 0 : if( w==16 )
9769 : {
9770 0 : r = -1.012e+01;
9771 : }
9772 0 : if( w==15 )
9773 : {
9774 0 : r = -1.033e+01;
9775 : }
9776 0 : if( w==14 )
9777 : {
9778 0 : r = -1.055e+01;
9779 : }
9780 0 : if( w==13 )
9781 : {
9782 0 : r = -1.077e+01;
9783 : }
9784 0 : if( w==12 )
9785 : {
9786 0 : r = -1.100e+01;
9787 : }
9788 0 : if( w==11 )
9789 : {
9790 0 : r = -1.124e+01;
9791 : }
9792 0 : if( w==10 )
9793 : {
9794 0 : r = -1.149e+01;
9795 : }
9796 0 : if( w==9 )
9797 : {
9798 0 : r = -1.175e+01;
9799 : }
9800 0 : if( w==8 )
9801 : {
9802 0 : r = -1.203e+01;
9803 : }
9804 0 : if( w==7 )
9805 : {
9806 0 : r = -1.230e+01;
9807 : }
9808 0 : if( w==6 )
9809 : {
9810 0 : r = -1.261e+01;
9811 : }
9812 0 : if( w==5 )
9813 : {
9814 0 : r = -1.295e+01;
9815 : }
9816 0 : if( w==4 )
9817 : {
9818 0 : r = -1.330e+01;
9819 : }
9820 0 : if( w==3 )
9821 : {
9822 0 : r = -1.364e+01;
9823 : }
9824 0 : if( w==2 )
9825 : {
9826 0 : r = -1.415e+01;
9827 : }
9828 0 : if( w==1 )
9829 : {
9830 0 : r = -1.456e+01;
9831 : }
9832 0 : if( w<=0 )
9833 : {
9834 0 : r = -1.525e+01;
9835 : }
9836 0 : result = r;
9837 0 : return result;
9838 : }
9839 :
9840 :
9841 : /*************************************************************************
9842 : Tail(S, 23)
9843 : *************************************************************************/
9844 0 : static double wsr_w23(double s, ae_state *_state)
9845 : {
9846 : ae_int_t w;
9847 : double r;
9848 : double result;
9849 :
9850 :
9851 0 : r = (double)(0);
9852 0 : w = ae_round(-3.287856e+01*s+1.380000e+02, _state);
9853 0 : if( w>=138 )
9854 : {
9855 0 : r = -6.813e-01;
9856 : }
9857 0 : if( w==137 )
9858 : {
9859 0 : r = -7.051e-01;
9860 : }
9861 0 : if( w==136 )
9862 : {
9863 0 : r = -7.295e-01;
9864 : }
9865 0 : if( w==135 )
9866 : {
9867 0 : r = -7.544e-01;
9868 : }
9869 0 : if( w==134 )
9870 : {
9871 0 : r = -7.800e-01;
9872 : }
9873 0 : if( w==133 )
9874 : {
9875 0 : r = -8.061e-01;
9876 : }
9877 0 : if( w==132 )
9878 : {
9879 0 : r = -8.328e-01;
9880 : }
9881 0 : if( w==131 )
9882 : {
9883 0 : r = -8.601e-01;
9884 : }
9885 0 : if( w==130 )
9886 : {
9887 0 : r = -8.880e-01;
9888 : }
9889 0 : if( w==129 )
9890 : {
9891 0 : r = -9.166e-01;
9892 : }
9893 0 : if( w==128 )
9894 : {
9895 0 : r = -9.457e-01;
9896 : }
9897 0 : if( w==127 )
9898 : {
9899 0 : r = -9.755e-01;
9900 : }
9901 0 : if( w==126 )
9902 : {
9903 0 : r = -1.006e+00;
9904 : }
9905 0 : if( w==125 )
9906 : {
9907 0 : r = -1.037e+00;
9908 : }
9909 0 : if( w==124 )
9910 : {
9911 0 : r = -1.069e+00;
9912 : }
9913 0 : if( w==123 )
9914 : {
9915 0 : r = -1.101e+00;
9916 : }
9917 0 : if( w==122 )
9918 : {
9919 0 : r = -1.134e+00;
9920 : }
9921 0 : if( w==121 )
9922 : {
9923 0 : r = -1.168e+00;
9924 : }
9925 0 : if( w==120 )
9926 : {
9927 0 : r = -1.202e+00;
9928 : }
9929 0 : if( w==119 )
9930 : {
9931 0 : r = -1.237e+00;
9932 : }
9933 0 : if( w==118 )
9934 : {
9935 0 : r = -1.273e+00;
9936 : }
9937 0 : if( w==117 )
9938 : {
9939 0 : r = -1.309e+00;
9940 : }
9941 0 : if( w==116 )
9942 : {
9943 0 : r = -1.347e+00;
9944 : }
9945 0 : if( w==115 )
9946 : {
9947 0 : r = -1.384e+00;
9948 : }
9949 0 : if( w==114 )
9950 : {
9951 0 : r = -1.423e+00;
9952 : }
9953 0 : if( w==113 )
9954 : {
9955 0 : r = -1.462e+00;
9956 : }
9957 0 : if( w==112 )
9958 : {
9959 0 : r = -1.502e+00;
9960 : }
9961 0 : if( w==111 )
9962 : {
9963 0 : r = -1.543e+00;
9964 : }
9965 0 : if( w==110 )
9966 : {
9967 0 : r = -1.585e+00;
9968 : }
9969 0 : if( w==109 )
9970 : {
9971 0 : r = -1.627e+00;
9972 : }
9973 0 : if( w==108 )
9974 : {
9975 0 : r = -1.670e+00;
9976 : }
9977 0 : if( w==107 )
9978 : {
9979 0 : r = -1.714e+00;
9980 : }
9981 0 : if( w==106 )
9982 : {
9983 0 : r = -1.758e+00;
9984 : }
9985 0 : if( w==105 )
9986 : {
9987 0 : r = -1.804e+00;
9988 : }
9989 0 : if( w==104 )
9990 : {
9991 0 : r = -1.850e+00;
9992 : }
9993 0 : if( w==103 )
9994 : {
9995 0 : r = -1.897e+00;
9996 : }
9997 0 : if( w==102 )
9998 : {
9999 0 : r = -1.944e+00;
10000 : }
10001 0 : if( w==101 )
10002 : {
10003 0 : r = -1.993e+00;
10004 : }
10005 0 : if( w==100 )
10006 : {
10007 0 : r = -2.042e+00;
10008 : }
10009 0 : if( w==99 )
10010 : {
10011 0 : r = -2.093e+00;
10012 : }
10013 0 : if( w==98 )
10014 : {
10015 0 : r = -2.144e+00;
10016 : }
10017 0 : if( w==97 )
10018 : {
10019 0 : r = -2.195e+00;
10020 : }
10021 0 : if( w==96 )
10022 : {
10023 0 : r = -2.248e+00;
10024 : }
10025 0 : if( w==95 )
10026 : {
10027 0 : r = -2.302e+00;
10028 : }
10029 0 : if( w==94 )
10030 : {
10031 0 : r = -2.356e+00;
10032 : }
10033 0 : if( w==93 )
10034 : {
10035 0 : r = -2.412e+00;
10036 : }
10037 0 : if( w==92 )
10038 : {
10039 0 : r = -2.468e+00;
10040 : }
10041 0 : if( w==91 )
10042 : {
10043 0 : r = -2.525e+00;
10044 : }
10045 0 : if( w==90 )
10046 : {
10047 0 : r = -2.583e+00;
10048 : }
10049 0 : if( w==89 )
10050 : {
10051 0 : r = -2.642e+00;
10052 : }
10053 0 : if( w==88 )
10054 : {
10055 0 : r = -2.702e+00;
10056 : }
10057 0 : if( w==87 )
10058 : {
10059 0 : r = -2.763e+00;
10060 : }
10061 0 : if( w==86 )
10062 : {
10063 0 : r = -2.825e+00;
10064 : }
10065 0 : if( w==85 )
10066 : {
10067 0 : r = -2.888e+00;
10068 : }
10069 0 : if( w==84 )
10070 : {
10071 0 : r = -2.951e+00;
10072 : }
10073 0 : if( w==83 )
10074 : {
10075 0 : r = -3.016e+00;
10076 : }
10077 0 : if( w==82 )
10078 : {
10079 0 : r = -3.082e+00;
10080 : }
10081 0 : if( w==81 )
10082 : {
10083 0 : r = -3.149e+00;
10084 : }
10085 0 : if( w==80 )
10086 : {
10087 0 : r = -3.216e+00;
10088 : }
10089 0 : if( w==79 )
10090 : {
10091 0 : r = -3.285e+00;
10092 : }
10093 0 : if( w==78 )
10094 : {
10095 0 : r = -3.355e+00;
10096 : }
10097 0 : if( w==77 )
10098 : {
10099 0 : r = -3.426e+00;
10100 : }
10101 0 : if( w==76 )
10102 : {
10103 0 : r = -3.498e+00;
10104 : }
10105 0 : if( w==75 )
10106 : {
10107 0 : r = -3.571e+00;
10108 : }
10109 0 : if( w==74 )
10110 : {
10111 0 : r = -3.645e+00;
10112 : }
10113 0 : if( w==73 )
10114 : {
10115 0 : r = -3.721e+00;
10116 : }
10117 0 : if( w==72 )
10118 : {
10119 0 : r = -3.797e+00;
10120 : }
10121 0 : if( w==71 )
10122 : {
10123 0 : r = -3.875e+00;
10124 : }
10125 0 : if( w==70 )
10126 : {
10127 0 : r = -3.953e+00;
10128 : }
10129 0 : if( w==69 )
10130 : {
10131 0 : r = -4.033e+00;
10132 : }
10133 0 : if( w==68 )
10134 : {
10135 0 : r = -4.114e+00;
10136 : }
10137 0 : if( w==67 )
10138 : {
10139 0 : r = -4.197e+00;
10140 : }
10141 0 : if( w==66 )
10142 : {
10143 0 : r = -4.280e+00;
10144 : }
10145 0 : if( w==65 )
10146 : {
10147 0 : r = -4.365e+00;
10148 : }
10149 0 : if( w==64 )
10150 : {
10151 0 : r = -4.451e+00;
10152 : }
10153 0 : if( w==63 )
10154 : {
10155 0 : r = -4.539e+00;
10156 : }
10157 0 : if( w==62 )
10158 : {
10159 0 : r = -4.628e+00;
10160 : }
10161 0 : if( w==61 )
10162 : {
10163 0 : r = -4.718e+00;
10164 : }
10165 0 : if( w==60 )
10166 : {
10167 0 : r = -4.809e+00;
10168 : }
10169 0 : if( w==59 )
10170 : {
10171 0 : r = -4.902e+00;
10172 : }
10173 0 : if( w==58 )
10174 : {
10175 0 : r = -4.996e+00;
10176 : }
10177 0 : if( w==57 )
10178 : {
10179 0 : r = -5.092e+00;
10180 : }
10181 0 : if( w==56 )
10182 : {
10183 0 : r = -5.189e+00;
10184 : }
10185 0 : if( w==55 )
10186 : {
10187 0 : r = -5.287e+00;
10188 : }
10189 0 : if( w==54 )
10190 : {
10191 0 : r = -5.388e+00;
10192 : }
10193 0 : if( w==53 )
10194 : {
10195 0 : r = -5.489e+00;
10196 : }
10197 0 : if( w==52 )
10198 : {
10199 0 : r = -5.592e+00;
10200 : }
10201 0 : if( w==51 )
10202 : {
10203 0 : r = -5.697e+00;
10204 : }
10205 0 : if( w==50 )
10206 : {
10207 0 : r = -5.804e+00;
10208 : }
10209 0 : if( w==49 )
10210 : {
10211 0 : r = -5.912e+00;
10212 : }
10213 0 : if( w==48 )
10214 : {
10215 0 : r = -6.022e+00;
10216 : }
10217 0 : if( w==47 )
10218 : {
10219 0 : r = -6.133e+00;
10220 : }
10221 0 : if( w==46 )
10222 : {
10223 0 : r = -6.247e+00;
10224 : }
10225 0 : if( w==45 )
10226 : {
10227 0 : r = -6.362e+00;
10228 : }
10229 0 : if( w==44 )
10230 : {
10231 0 : r = -6.479e+00;
10232 : }
10233 0 : if( w==43 )
10234 : {
10235 0 : r = -6.598e+00;
10236 : }
10237 0 : if( w==42 )
10238 : {
10239 0 : r = -6.719e+00;
10240 : }
10241 0 : if( w==41 )
10242 : {
10243 0 : r = -6.842e+00;
10244 : }
10245 0 : if( w==40 )
10246 : {
10247 0 : r = -6.967e+00;
10248 : }
10249 0 : if( w==39 )
10250 : {
10251 0 : r = -7.094e+00;
10252 : }
10253 0 : if( w==38 )
10254 : {
10255 0 : r = -7.224e+00;
10256 : }
10257 0 : if( w==37 )
10258 : {
10259 0 : r = -7.355e+00;
10260 : }
10261 0 : if( w==36 )
10262 : {
10263 0 : r = -7.489e+00;
10264 : }
10265 0 : if( w==35 )
10266 : {
10267 0 : r = -7.625e+00;
10268 : }
10269 0 : if( w==34 )
10270 : {
10271 0 : r = -7.764e+00;
10272 : }
10273 0 : if( w==33 )
10274 : {
10275 0 : r = -7.905e+00;
10276 : }
10277 0 : if( w==32 )
10278 : {
10279 0 : r = -8.049e+00;
10280 : }
10281 0 : if( w==31 )
10282 : {
10283 0 : r = -8.196e+00;
10284 : }
10285 0 : if( w==30 )
10286 : {
10287 0 : r = -8.345e+00;
10288 : }
10289 0 : if( w==29 )
10290 : {
10291 0 : r = -8.498e+00;
10292 : }
10293 0 : if( w==28 )
10294 : {
10295 0 : r = -8.653e+00;
10296 : }
10297 0 : if( w==27 )
10298 : {
10299 0 : r = -8.811e+00;
10300 : }
10301 0 : if( w==26 )
10302 : {
10303 0 : r = -8.974e+00;
10304 : }
10305 0 : if( w==25 )
10306 : {
10307 0 : r = -9.139e+00;
10308 : }
10309 0 : if( w==24 )
10310 : {
10311 0 : r = -9.308e+00;
10312 : }
10313 0 : if( w==23 )
10314 : {
10315 0 : r = -9.481e+00;
10316 : }
10317 0 : if( w==22 )
10318 : {
10319 0 : r = -9.658e+00;
10320 : }
10321 0 : if( w==21 )
10322 : {
10323 0 : r = -9.840e+00;
10324 : }
10325 0 : if( w==20 )
10326 : {
10327 0 : r = -1.003e+01;
10328 : }
10329 0 : if( w==19 )
10330 : {
10331 0 : r = -1.022e+01;
10332 : }
10333 0 : if( w==18 )
10334 : {
10335 0 : r = -1.041e+01;
10336 : }
10337 0 : if( w==17 )
10338 : {
10339 0 : r = -1.061e+01;
10340 : }
10341 0 : if( w==16 )
10342 : {
10343 0 : r = -1.081e+01;
10344 : }
10345 0 : if( w==15 )
10346 : {
10347 0 : r = -1.102e+01;
10348 : }
10349 0 : if( w==14 )
10350 : {
10351 0 : r = -1.124e+01;
10352 : }
10353 0 : if( w==13 )
10354 : {
10355 0 : r = -1.147e+01;
10356 : }
10357 0 : if( w==12 )
10358 : {
10359 0 : r = -1.169e+01;
10360 : }
10361 0 : if( w==11 )
10362 : {
10363 0 : r = -1.194e+01;
10364 : }
10365 0 : if( w==10 )
10366 : {
10367 0 : r = -1.218e+01;
10368 : }
10369 0 : if( w==9 )
10370 : {
10371 0 : r = -1.245e+01;
10372 : }
10373 0 : if( w==8 )
10374 : {
10375 0 : r = -1.272e+01;
10376 : }
10377 0 : if( w==7 )
10378 : {
10379 0 : r = -1.300e+01;
10380 : }
10381 0 : if( w==6 )
10382 : {
10383 0 : r = -1.330e+01;
10384 : }
10385 0 : if( w==5 )
10386 : {
10387 0 : r = -1.364e+01;
10388 : }
10389 0 : if( w==4 )
10390 : {
10391 0 : r = -1.400e+01;
10392 : }
10393 0 : if( w==3 )
10394 : {
10395 0 : r = -1.433e+01;
10396 : }
10397 0 : if( w==2 )
10398 : {
10399 0 : r = -1.484e+01;
10400 : }
10401 0 : if( w==1 )
10402 : {
10403 0 : r = -1.525e+01;
10404 : }
10405 0 : if( w<=0 )
10406 : {
10407 0 : r = -1.594e+01;
10408 : }
10409 0 : result = r;
10410 0 : return result;
10411 : }
10412 :
10413 :
10414 : /*************************************************************************
10415 : Tail(S, 24)
10416 : *************************************************************************/
10417 0 : static double wsr_w24(double s, ae_state *_state)
10418 : {
10419 : ae_int_t w;
10420 : double r;
10421 : double result;
10422 :
10423 :
10424 0 : r = (double)(0);
10425 0 : w = ae_round(-3.500000e+01*s+1.500000e+02, _state);
10426 0 : if( w>=150 )
10427 : {
10428 0 : r = -6.820e-01;
10429 : }
10430 0 : if( w==149 )
10431 : {
10432 0 : r = -7.044e-01;
10433 : }
10434 0 : if( w==148 )
10435 : {
10436 0 : r = -7.273e-01;
10437 : }
10438 0 : if( w==147 )
10439 : {
10440 0 : r = -7.507e-01;
10441 : }
10442 0 : if( w==146 )
10443 : {
10444 0 : r = -7.746e-01;
10445 : }
10446 0 : if( w==145 )
10447 : {
10448 0 : r = -7.990e-01;
10449 : }
10450 0 : if( w==144 )
10451 : {
10452 0 : r = -8.239e-01;
10453 : }
10454 0 : if( w==143 )
10455 : {
10456 0 : r = -8.494e-01;
10457 : }
10458 0 : if( w==142 )
10459 : {
10460 0 : r = -8.754e-01;
10461 : }
10462 0 : if( w==141 )
10463 : {
10464 0 : r = -9.020e-01;
10465 : }
10466 0 : if( w==140 )
10467 : {
10468 0 : r = -9.291e-01;
10469 : }
10470 0 : if( w==139 )
10471 : {
10472 0 : r = -9.567e-01;
10473 : }
10474 0 : if( w==138 )
10475 : {
10476 0 : r = -9.849e-01;
10477 : }
10478 0 : if( w==137 )
10479 : {
10480 0 : r = -1.014e+00;
10481 : }
10482 0 : if( w==136 )
10483 : {
10484 0 : r = -1.043e+00;
10485 : }
10486 0 : if( w==135 )
10487 : {
10488 0 : r = -1.073e+00;
10489 : }
10490 0 : if( w==134 )
10491 : {
10492 0 : r = -1.103e+00;
10493 : }
10494 0 : if( w==133 )
10495 : {
10496 0 : r = -1.135e+00;
10497 : }
10498 0 : if( w==132 )
10499 : {
10500 0 : r = -1.166e+00;
10501 : }
10502 0 : if( w==131 )
10503 : {
10504 0 : r = -1.198e+00;
10505 : }
10506 0 : if( w==130 )
10507 : {
10508 0 : r = -1.231e+00;
10509 : }
10510 0 : if( w==129 )
10511 : {
10512 0 : r = -1.265e+00;
10513 : }
10514 0 : if( w==128 )
10515 : {
10516 0 : r = -1.299e+00;
10517 : }
10518 0 : if( w==127 )
10519 : {
10520 0 : r = -1.334e+00;
10521 : }
10522 0 : if( w==126 )
10523 : {
10524 0 : r = -1.369e+00;
10525 : }
10526 0 : if( w==125 )
10527 : {
10528 0 : r = -1.405e+00;
10529 : }
10530 0 : if( w==124 )
10531 : {
10532 0 : r = -1.441e+00;
10533 : }
10534 0 : if( w==123 )
10535 : {
10536 0 : r = -1.479e+00;
10537 : }
10538 0 : if( w==122 )
10539 : {
10540 0 : r = -1.517e+00;
10541 : }
10542 0 : if( w==121 )
10543 : {
10544 0 : r = -1.555e+00;
10545 : }
10546 0 : if( w==120 )
10547 : {
10548 0 : r = -1.594e+00;
10549 : }
10550 0 : if( w==119 )
10551 : {
10552 0 : r = -1.634e+00;
10553 : }
10554 0 : if( w==118 )
10555 : {
10556 0 : r = -1.675e+00;
10557 : }
10558 0 : if( w==117 )
10559 : {
10560 0 : r = -1.716e+00;
10561 : }
10562 0 : if( w==116 )
10563 : {
10564 0 : r = -1.758e+00;
10565 : }
10566 0 : if( w==115 )
10567 : {
10568 0 : r = -1.800e+00;
10569 : }
10570 0 : if( w==114 )
10571 : {
10572 0 : r = -1.844e+00;
10573 : }
10574 0 : if( w==113 )
10575 : {
10576 0 : r = -1.888e+00;
10577 : }
10578 0 : if( w==112 )
10579 : {
10580 0 : r = -1.932e+00;
10581 : }
10582 0 : if( w==111 )
10583 : {
10584 0 : r = -1.978e+00;
10585 : }
10586 0 : if( w==110 )
10587 : {
10588 0 : r = -2.024e+00;
10589 : }
10590 0 : if( w==109 )
10591 : {
10592 0 : r = -2.070e+00;
10593 : }
10594 0 : if( w==108 )
10595 : {
10596 0 : r = -2.118e+00;
10597 : }
10598 0 : if( w==107 )
10599 : {
10600 0 : r = -2.166e+00;
10601 : }
10602 0 : if( w==106 )
10603 : {
10604 0 : r = -2.215e+00;
10605 : }
10606 0 : if( w==105 )
10607 : {
10608 0 : r = -2.265e+00;
10609 : }
10610 0 : if( w==104 )
10611 : {
10612 0 : r = -2.316e+00;
10613 : }
10614 0 : if( w==103 )
10615 : {
10616 0 : r = -2.367e+00;
10617 : }
10618 0 : if( w==102 )
10619 : {
10620 0 : r = -2.419e+00;
10621 : }
10622 0 : if( w==101 )
10623 : {
10624 0 : r = -2.472e+00;
10625 : }
10626 0 : if( w==100 )
10627 : {
10628 0 : r = -2.526e+00;
10629 : }
10630 0 : if( w==99 )
10631 : {
10632 0 : r = -2.580e+00;
10633 : }
10634 0 : if( w==98 )
10635 : {
10636 0 : r = -2.636e+00;
10637 : }
10638 0 : if( w==97 )
10639 : {
10640 0 : r = -2.692e+00;
10641 : }
10642 0 : if( w==96 )
10643 : {
10644 0 : r = -2.749e+00;
10645 : }
10646 0 : if( w==95 )
10647 : {
10648 0 : r = -2.806e+00;
10649 : }
10650 0 : if( w==94 )
10651 : {
10652 0 : r = -2.865e+00;
10653 : }
10654 0 : if( w==93 )
10655 : {
10656 0 : r = -2.925e+00;
10657 : }
10658 0 : if( w==92 )
10659 : {
10660 0 : r = -2.985e+00;
10661 : }
10662 0 : if( w==91 )
10663 : {
10664 0 : r = -3.046e+00;
10665 : }
10666 0 : if( w==90 )
10667 : {
10668 0 : r = -3.108e+00;
10669 : }
10670 0 : if( w==89 )
10671 : {
10672 0 : r = -3.171e+00;
10673 : }
10674 0 : if( w==88 )
10675 : {
10676 0 : r = -3.235e+00;
10677 : }
10678 0 : if( w==87 )
10679 : {
10680 0 : r = -3.300e+00;
10681 : }
10682 0 : if( w==86 )
10683 : {
10684 0 : r = -3.365e+00;
10685 : }
10686 0 : if( w==85 )
10687 : {
10688 0 : r = -3.432e+00;
10689 : }
10690 0 : if( w==84 )
10691 : {
10692 0 : r = -3.499e+00;
10693 : }
10694 0 : if( w==83 )
10695 : {
10696 0 : r = -3.568e+00;
10697 : }
10698 0 : if( w==82 )
10699 : {
10700 0 : r = -3.637e+00;
10701 : }
10702 0 : if( w==81 )
10703 : {
10704 0 : r = -3.708e+00;
10705 : }
10706 0 : if( w==80 )
10707 : {
10708 0 : r = -3.779e+00;
10709 : }
10710 0 : if( w==79 )
10711 : {
10712 0 : r = -3.852e+00;
10713 : }
10714 0 : if( w==78 )
10715 : {
10716 0 : r = -3.925e+00;
10717 : }
10718 0 : if( w==77 )
10719 : {
10720 0 : r = -4.000e+00;
10721 : }
10722 0 : if( w==76 )
10723 : {
10724 0 : r = -4.075e+00;
10725 : }
10726 0 : if( w==75 )
10727 : {
10728 0 : r = -4.151e+00;
10729 : }
10730 0 : if( w==74 )
10731 : {
10732 0 : r = -4.229e+00;
10733 : }
10734 0 : if( w==73 )
10735 : {
10736 0 : r = -4.308e+00;
10737 : }
10738 0 : if( w==72 )
10739 : {
10740 0 : r = -4.387e+00;
10741 : }
10742 0 : if( w==71 )
10743 : {
10744 0 : r = -4.468e+00;
10745 : }
10746 0 : if( w==70 )
10747 : {
10748 0 : r = -4.550e+00;
10749 : }
10750 0 : if( w==69 )
10751 : {
10752 0 : r = -4.633e+00;
10753 : }
10754 0 : if( w==68 )
10755 : {
10756 0 : r = -4.718e+00;
10757 : }
10758 0 : if( w==67 )
10759 : {
10760 0 : r = -4.803e+00;
10761 : }
10762 0 : if( w==66 )
10763 : {
10764 0 : r = -4.890e+00;
10765 : }
10766 0 : if( w==65 )
10767 : {
10768 0 : r = -4.978e+00;
10769 : }
10770 0 : if( w==64 )
10771 : {
10772 0 : r = -5.067e+00;
10773 : }
10774 0 : if( w==63 )
10775 : {
10776 0 : r = -5.157e+00;
10777 : }
10778 0 : if( w==62 )
10779 : {
10780 0 : r = -5.249e+00;
10781 : }
10782 0 : if( w==61 )
10783 : {
10784 0 : r = -5.342e+00;
10785 : }
10786 0 : if( w==60 )
10787 : {
10788 0 : r = -5.436e+00;
10789 : }
10790 0 : if( w==59 )
10791 : {
10792 0 : r = -5.531e+00;
10793 : }
10794 0 : if( w==58 )
10795 : {
10796 0 : r = -5.628e+00;
10797 : }
10798 0 : if( w==57 )
10799 : {
10800 0 : r = -5.727e+00;
10801 : }
10802 0 : if( w==56 )
10803 : {
10804 0 : r = -5.826e+00;
10805 : }
10806 0 : if( w==55 )
10807 : {
10808 0 : r = -5.927e+00;
10809 : }
10810 0 : if( w==54 )
10811 : {
10812 0 : r = -6.030e+00;
10813 : }
10814 0 : if( w==53 )
10815 : {
10816 0 : r = -6.134e+00;
10817 : }
10818 0 : if( w==52 )
10819 : {
10820 0 : r = -6.240e+00;
10821 : }
10822 0 : if( w==51 )
10823 : {
10824 0 : r = -6.347e+00;
10825 : }
10826 0 : if( w==50 )
10827 : {
10828 0 : r = -6.456e+00;
10829 : }
10830 0 : if( w==49 )
10831 : {
10832 0 : r = -6.566e+00;
10833 : }
10834 0 : if( w==48 )
10835 : {
10836 0 : r = -6.678e+00;
10837 : }
10838 0 : if( w==47 )
10839 : {
10840 0 : r = -6.792e+00;
10841 : }
10842 0 : if( w==46 )
10843 : {
10844 0 : r = -6.907e+00;
10845 : }
10846 0 : if( w==45 )
10847 : {
10848 0 : r = -7.025e+00;
10849 : }
10850 0 : if( w==44 )
10851 : {
10852 0 : r = -7.144e+00;
10853 : }
10854 0 : if( w==43 )
10855 : {
10856 0 : r = -7.265e+00;
10857 : }
10858 0 : if( w==42 )
10859 : {
10860 0 : r = -7.387e+00;
10861 : }
10862 0 : if( w==41 )
10863 : {
10864 0 : r = -7.512e+00;
10865 : }
10866 0 : if( w==40 )
10867 : {
10868 0 : r = -7.639e+00;
10869 : }
10870 0 : if( w==39 )
10871 : {
10872 0 : r = -7.768e+00;
10873 : }
10874 0 : if( w==38 )
10875 : {
10876 0 : r = -7.899e+00;
10877 : }
10878 0 : if( w==37 )
10879 : {
10880 0 : r = -8.032e+00;
10881 : }
10882 0 : if( w==36 )
10883 : {
10884 0 : r = -8.167e+00;
10885 : }
10886 0 : if( w==35 )
10887 : {
10888 0 : r = -8.305e+00;
10889 : }
10890 0 : if( w==34 )
10891 : {
10892 0 : r = -8.445e+00;
10893 : }
10894 0 : if( w==33 )
10895 : {
10896 0 : r = -8.588e+00;
10897 : }
10898 0 : if( w==32 )
10899 : {
10900 0 : r = -8.733e+00;
10901 : }
10902 0 : if( w==31 )
10903 : {
10904 0 : r = -8.881e+00;
10905 : }
10906 0 : if( w==30 )
10907 : {
10908 0 : r = -9.031e+00;
10909 : }
10910 0 : if( w==29 )
10911 : {
10912 0 : r = -9.185e+00;
10913 : }
10914 0 : if( w==28 )
10915 : {
10916 0 : r = -9.341e+00;
10917 : }
10918 0 : if( w==27 )
10919 : {
10920 0 : r = -9.501e+00;
10921 : }
10922 0 : if( w==26 )
10923 : {
10924 0 : r = -9.664e+00;
10925 : }
10926 0 : if( w==25 )
10927 : {
10928 0 : r = -9.830e+00;
10929 : }
10930 0 : if( w==24 )
10931 : {
10932 0 : r = -1.000e+01;
10933 : }
10934 0 : if( w==23 )
10935 : {
10936 0 : r = -1.017e+01;
10937 : }
10938 0 : if( w==22 )
10939 : {
10940 0 : r = -1.035e+01;
10941 : }
10942 0 : if( w==21 )
10943 : {
10944 0 : r = -1.053e+01;
10945 : }
10946 0 : if( w==20 )
10947 : {
10948 0 : r = -1.072e+01;
10949 : }
10950 0 : if( w==19 )
10951 : {
10952 0 : r = -1.091e+01;
10953 : }
10954 0 : if( w==18 )
10955 : {
10956 0 : r = -1.110e+01;
10957 : }
10958 0 : if( w==17 )
10959 : {
10960 0 : r = -1.130e+01;
10961 : }
10962 0 : if( w==16 )
10963 : {
10964 0 : r = -1.151e+01;
10965 : }
10966 0 : if( w==15 )
10967 : {
10968 0 : r = -1.172e+01;
10969 : }
10970 0 : if( w==14 )
10971 : {
10972 0 : r = -1.194e+01;
10973 : }
10974 0 : if( w==13 )
10975 : {
10976 0 : r = -1.216e+01;
10977 : }
10978 0 : if( w==12 )
10979 : {
10980 0 : r = -1.239e+01;
10981 : }
10982 0 : if( w==11 )
10983 : {
10984 0 : r = -1.263e+01;
10985 : }
10986 0 : if( w==10 )
10987 : {
10988 0 : r = -1.287e+01;
10989 : }
10990 0 : if( w==9 )
10991 : {
10992 0 : r = -1.314e+01;
10993 : }
10994 0 : if( w==8 )
10995 : {
10996 0 : r = -1.342e+01;
10997 : }
10998 0 : if( w==7 )
10999 : {
11000 0 : r = -1.369e+01;
11001 : }
11002 0 : if( w==6 )
11003 : {
11004 0 : r = -1.400e+01;
11005 : }
11006 0 : if( w==5 )
11007 : {
11008 0 : r = -1.433e+01;
11009 : }
11010 0 : if( w==4 )
11011 : {
11012 0 : r = -1.469e+01;
11013 : }
11014 0 : if( w==3 )
11015 : {
11016 0 : r = -1.503e+01;
11017 : }
11018 0 : if( w==2 )
11019 : {
11020 0 : r = -1.554e+01;
11021 : }
11022 0 : if( w==1 )
11023 : {
11024 0 : r = -1.594e+01;
11025 : }
11026 0 : if( w<=0 )
11027 : {
11028 0 : r = -1.664e+01;
11029 : }
11030 0 : result = r;
11031 0 : return result;
11032 : }
11033 :
11034 :
11035 : /*************************************************************************
11036 : Tail(S, 25)
11037 : *************************************************************************/
11038 0 : static double wsr_w25(double s, ae_state *_state)
11039 : {
11040 : double x;
11041 : double tj;
11042 : double tj1;
11043 : double result;
11044 :
11045 :
11046 0 : result = (double)(0);
11047 0 : x = ae_minreal(2*(s-0.000000e+00)/4.000000e+00-1, 1.0, _state);
11048 0 : tj = (double)(1);
11049 0 : tj1 = x;
11050 0 : wsr_wcheb(x, -5.150509e+00, &tj, &tj1, &result, _state);
11051 0 : wsr_wcheb(x, -5.695528e+00, &tj, &tj1, &result, _state);
11052 0 : wsr_wcheb(x, -1.437637e+00, &tj, &tj1, &result, _state);
11053 0 : wsr_wcheb(x, -2.611906e-01, &tj, &tj1, &result, _state);
11054 0 : wsr_wcheb(x, -7.625722e-02, &tj, &tj1, &result, _state);
11055 0 : wsr_wcheb(x, -2.579892e-02, &tj, &tj1, &result, _state);
11056 0 : wsr_wcheb(x, -1.086876e-02, &tj, &tj1, &result, _state);
11057 0 : wsr_wcheb(x, -2.906543e-03, &tj, &tj1, &result, _state);
11058 0 : wsr_wcheb(x, -2.354881e-03, &tj, &tj1, &result, _state);
11059 0 : wsr_wcheb(x, 1.007195e-04, &tj, &tj1, &result, _state);
11060 0 : wsr_wcheb(x, -8.437327e-04, &tj, &tj1, &result, _state);
11061 0 : return result;
11062 : }
11063 :
11064 :
11065 : /*************************************************************************
11066 : Tail(S, 26)
11067 : *************************************************************************/
11068 0 : static double wsr_w26(double s, ae_state *_state)
11069 : {
11070 : double x;
11071 : double tj;
11072 : double tj1;
11073 : double result;
11074 :
11075 :
11076 0 : result = (double)(0);
11077 0 : x = ae_minreal(2*(s-0.000000e+00)/4.000000e+00-1, 1.0, _state);
11078 0 : tj = (double)(1);
11079 0 : tj1 = x;
11080 0 : wsr_wcheb(x, -5.117622e+00, &tj, &tj1, &result, _state);
11081 0 : wsr_wcheb(x, -5.635159e+00, &tj, &tj1, &result, _state);
11082 0 : wsr_wcheb(x, -1.395167e+00, &tj, &tj1, &result, _state);
11083 0 : wsr_wcheb(x, -2.382823e-01, &tj, &tj1, &result, _state);
11084 0 : wsr_wcheb(x, -6.531987e-02, &tj, &tj1, &result, _state);
11085 0 : wsr_wcheb(x, -2.060112e-02, &tj, &tj1, &result, _state);
11086 0 : wsr_wcheb(x, -8.203697e-03, &tj, &tj1, &result, _state);
11087 0 : wsr_wcheb(x, -1.516523e-03, &tj, &tj1, &result, _state);
11088 0 : wsr_wcheb(x, -1.431364e-03, &tj, &tj1, &result, _state);
11089 0 : wsr_wcheb(x, 6.384553e-04, &tj, &tj1, &result, _state);
11090 0 : wsr_wcheb(x, -3.238369e-04, &tj, &tj1, &result, _state);
11091 0 : return result;
11092 : }
11093 :
11094 :
11095 : /*************************************************************************
11096 : Tail(S, 27)
11097 : *************************************************************************/
11098 0 : static double wsr_w27(double s, ae_state *_state)
11099 : {
11100 : double x;
11101 : double tj;
11102 : double tj1;
11103 : double result;
11104 :
11105 :
11106 0 : result = (double)(0);
11107 0 : x = ae_minreal(2*(s-0.000000e+00)/4.000000e+00-1, 1.0, _state);
11108 0 : tj = (double)(1);
11109 0 : tj1 = x;
11110 0 : wsr_wcheb(x, -5.089731e+00, &tj, &tj1, &result, _state);
11111 0 : wsr_wcheb(x, -5.584248e+00, &tj, &tj1, &result, _state);
11112 0 : wsr_wcheb(x, -1.359966e+00, &tj, &tj1, &result, _state);
11113 0 : wsr_wcheb(x, -2.203696e-01, &tj, &tj1, &result, _state);
11114 0 : wsr_wcheb(x, -5.753344e-02, &tj, &tj1, &result, _state);
11115 0 : wsr_wcheb(x, -1.761891e-02, &tj, &tj1, &result, _state);
11116 0 : wsr_wcheb(x, -7.096897e-03, &tj, &tj1, &result, _state);
11117 0 : wsr_wcheb(x, -1.419108e-03, &tj, &tj1, &result, _state);
11118 0 : wsr_wcheb(x, -1.581214e-03, &tj, &tj1, &result, _state);
11119 0 : wsr_wcheb(x, 3.033766e-04, &tj, &tj1, &result, _state);
11120 0 : wsr_wcheb(x, -5.901441e-04, &tj, &tj1, &result, _state);
11121 0 : return result;
11122 : }
11123 :
11124 :
11125 : /*************************************************************************
11126 : Tail(S, 28)
11127 : *************************************************************************/
11128 0 : static double wsr_w28(double s, ae_state *_state)
11129 : {
11130 : double x;
11131 : double tj;
11132 : double tj1;
11133 : double result;
11134 :
11135 :
11136 0 : result = (double)(0);
11137 0 : x = ae_minreal(2*(s-0.000000e+00)/4.000000e+00-1, 1.0, _state);
11138 0 : tj = (double)(1);
11139 0 : tj1 = x;
11140 0 : wsr_wcheb(x, -5.065046e+00, &tj, &tj1, &result, _state);
11141 0 : wsr_wcheb(x, -5.539163e+00, &tj, &tj1, &result, _state);
11142 0 : wsr_wcheb(x, -1.328939e+00, &tj, &tj1, &result, _state);
11143 0 : wsr_wcheb(x, -2.046376e-01, &tj, &tj1, &result, _state);
11144 0 : wsr_wcheb(x, -5.061515e-02, &tj, &tj1, &result, _state);
11145 0 : wsr_wcheb(x, -1.469271e-02, &tj, &tj1, &result, _state);
11146 0 : wsr_wcheb(x, -5.711578e-03, &tj, &tj1, &result, _state);
11147 0 : wsr_wcheb(x, -8.389153e-04, &tj, &tj1, &result, _state);
11148 0 : wsr_wcheb(x, -1.250575e-03, &tj, &tj1, &result, _state);
11149 0 : wsr_wcheb(x, 4.047245e-04, &tj, &tj1, &result, _state);
11150 0 : wsr_wcheb(x, -5.128555e-04, &tj, &tj1, &result, _state);
11151 0 : return result;
11152 : }
11153 :
11154 :
11155 : /*************************************************************************
11156 : Tail(S, 29)
11157 : *************************************************************************/
11158 0 : static double wsr_w29(double s, ae_state *_state)
11159 : {
11160 : double x;
11161 : double tj;
11162 : double tj1;
11163 : double result;
11164 :
11165 :
11166 0 : result = (double)(0);
11167 0 : x = ae_minreal(2*(s-0.000000e+00)/4.000000e+00-1, 1.0, _state);
11168 0 : tj = (double)(1);
11169 0 : tj1 = x;
11170 0 : wsr_wcheb(x, -5.043413e+00, &tj, &tj1, &result, _state);
11171 0 : wsr_wcheb(x, -5.499756e+00, &tj, &tj1, &result, _state);
11172 0 : wsr_wcheb(x, -1.302137e+00, &tj, &tj1, &result, _state);
11173 0 : wsr_wcheb(x, -1.915129e-01, &tj, &tj1, &result, _state);
11174 0 : wsr_wcheb(x, -4.516329e-02, &tj, &tj1, &result, _state);
11175 0 : wsr_wcheb(x, -1.260064e-02, &tj, &tj1, &result, _state);
11176 0 : wsr_wcheb(x, -4.817269e-03, &tj, &tj1, &result, _state);
11177 0 : wsr_wcheb(x, -5.478130e-04, &tj, &tj1, &result, _state);
11178 0 : wsr_wcheb(x, -1.111668e-03, &tj, &tj1, &result, _state);
11179 0 : wsr_wcheb(x, 4.093451e-04, &tj, &tj1, &result, _state);
11180 0 : wsr_wcheb(x, -5.135860e-04, &tj, &tj1, &result, _state);
11181 0 : return result;
11182 : }
11183 :
11184 :
11185 : /*************************************************************************
11186 : Tail(S, 30)
11187 : *************************************************************************/
11188 0 : static double wsr_w30(double s, ae_state *_state)
11189 : {
11190 : double x;
11191 : double tj;
11192 : double tj1;
11193 : double result;
11194 :
11195 :
11196 0 : result = (double)(0);
11197 0 : x = ae_minreal(2*(s-0.000000e+00)/4.000000e+00-1, 1.0, _state);
11198 0 : tj = (double)(1);
11199 0 : tj1 = x;
11200 0 : wsr_wcheb(x, -5.024071e+00, &tj, &tj1, &result, _state);
11201 0 : wsr_wcheb(x, -5.464515e+00, &tj, &tj1, &result, _state);
11202 0 : wsr_wcheb(x, -1.278342e+00, &tj, &tj1, &result, _state);
11203 0 : wsr_wcheb(x, -1.800030e-01, &tj, &tj1, &result, _state);
11204 0 : wsr_wcheb(x, -4.046294e-02, &tj, &tj1, &result, _state);
11205 0 : wsr_wcheb(x, -1.076162e-02, &tj, &tj1, &result, _state);
11206 0 : wsr_wcheb(x, -3.968677e-03, &tj, &tj1, &result, _state);
11207 0 : wsr_wcheb(x, -1.911679e-04, &tj, &tj1, &result, _state);
11208 0 : wsr_wcheb(x, -8.619185e-04, &tj, &tj1, &result, _state);
11209 0 : wsr_wcheb(x, 5.125362e-04, &tj, &tj1, &result, _state);
11210 0 : wsr_wcheb(x, -3.984370e-04, &tj, &tj1, &result, _state);
11211 0 : return result;
11212 : }
11213 :
11214 :
11215 : /*************************************************************************
11216 : Tail(S, 40)
11217 : *************************************************************************/
11218 0 : static double wsr_w40(double s, ae_state *_state)
11219 : {
11220 : double x;
11221 : double tj;
11222 : double tj1;
11223 : double result;
11224 :
11225 :
11226 0 : result = (double)(0);
11227 0 : x = ae_minreal(2*(s-0.000000e+00)/4.000000e+00-1, 1.0, _state);
11228 0 : tj = (double)(1);
11229 0 : tj1 = x;
11230 0 : wsr_wcheb(x, -4.904809e+00, &tj, &tj1, &result, _state);
11231 0 : wsr_wcheb(x, -5.248327e+00, &tj, &tj1, &result, _state);
11232 0 : wsr_wcheb(x, -1.136698e+00, &tj, &tj1, &result, _state);
11233 0 : wsr_wcheb(x, -1.170982e-01, &tj, &tj1, &result, _state);
11234 0 : wsr_wcheb(x, -1.824427e-02, &tj, &tj1, &result, _state);
11235 0 : wsr_wcheb(x, -3.888648e-03, &tj, &tj1, &result, _state);
11236 0 : wsr_wcheb(x, -1.344929e-03, &tj, &tj1, &result, _state);
11237 0 : wsr_wcheb(x, 2.790407e-04, &tj, &tj1, &result, _state);
11238 0 : wsr_wcheb(x, -4.619858e-04, &tj, &tj1, &result, _state);
11239 0 : wsr_wcheb(x, 3.359121e-04, &tj, &tj1, &result, _state);
11240 0 : wsr_wcheb(x, -2.883026e-04, &tj, &tj1, &result, _state);
11241 0 : return result;
11242 : }
11243 :
11244 :
11245 : /*************************************************************************
11246 : Tail(S, 60)
11247 : *************************************************************************/
11248 0 : static double wsr_w60(double s, ae_state *_state)
11249 : {
11250 : double x;
11251 : double tj;
11252 : double tj1;
11253 : double result;
11254 :
11255 :
11256 0 : result = (double)(0);
11257 0 : x = ae_minreal(2*(s-0.000000e+00)/4.000000e+00-1, 1.0, _state);
11258 0 : tj = (double)(1);
11259 0 : tj1 = x;
11260 0 : wsr_wcheb(x, -4.809656e+00, &tj, &tj1, &result, _state);
11261 0 : wsr_wcheb(x, -5.077191e+00, &tj, &tj1, &result, _state);
11262 0 : wsr_wcheb(x, -1.029402e+00, &tj, &tj1, &result, _state);
11263 0 : wsr_wcheb(x, -7.507931e-02, &tj, &tj1, &result, _state);
11264 0 : wsr_wcheb(x, -6.506226e-03, &tj, &tj1, &result, _state);
11265 0 : wsr_wcheb(x, -1.391278e-03, &tj, &tj1, &result, _state);
11266 0 : wsr_wcheb(x, -4.263635e-04, &tj, &tj1, &result, _state);
11267 0 : wsr_wcheb(x, 2.302271e-04, &tj, &tj1, &result, _state);
11268 0 : wsr_wcheb(x, -2.384348e-04, &tj, &tj1, &result, _state);
11269 0 : wsr_wcheb(x, 1.865587e-04, &tj, &tj1, &result, _state);
11270 0 : wsr_wcheb(x, -1.622355e-04, &tj, &tj1, &result, _state);
11271 0 : return result;
11272 : }
11273 :
11274 :
11275 : /*************************************************************************
11276 : Tail(S, 120)
11277 : *************************************************************************/
11278 0 : static double wsr_w120(double s, ae_state *_state)
11279 : {
11280 : double x;
11281 : double tj;
11282 : double tj1;
11283 : double result;
11284 :
11285 :
11286 0 : result = (double)(0);
11287 0 : x = ae_minreal(2*(s-0.000000e+00)/4.000000e+00-1, 1.0, _state);
11288 0 : tj = (double)(1);
11289 0 : tj1 = x;
11290 0 : wsr_wcheb(x, -4.729426e+00, &tj, &tj1, &result, _state);
11291 0 : wsr_wcheb(x, -4.934426e+00, &tj, &tj1, &result, _state);
11292 0 : wsr_wcheb(x, -9.433231e-01, &tj, &tj1, &result, _state);
11293 0 : wsr_wcheb(x, -4.492504e-02, &tj, &tj1, &result, _state);
11294 0 : wsr_wcheb(x, 1.673948e-05, &tj, &tj1, &result, _state);
11295 0 : wsr_wcheb(x, -6.077014e-04, &tj, &tj1, &result, _state);
11296 0 : wsr_wcheb(x, -7.215768e-05, &tj, &tj1, &result, _state);
11297 0 : wsr_wcheb(x, 9.086734e-05, &tj, &tj1, &result, _state);
11298 0 : wsr_wcheb(x, -8.447980e-05, &tj, &tj1, &result, _state);
11299 0 : wsr_wcheb(x, 6.705028e-05, &tj, &tj1, &result, _state);
11300 0 : wsr_wcheb(x, -5.828507e-05, &tj, &tj1, &result, _state);
11301 0 : return result;
11302 : }
11303 :
11304 :
11305 : /*************************************************************************
11306 : Tail(S, 200)
11307 : *************************************************************************/
11308 0 : static double wsr_w200(double s, ae_state *_state)
11309 : {
11310 : double x;
11311 : double tj;
11312 : double tj1;
11313 : double result;
11314 :
11315 :
11316 0 : result = (double)(0);
11317 0 : x = ae_minreal(2*(s-0.000000e+00)/4.000000e+00-1, 1.0, _state);
11318 0 : tj = (double)(1);
11319 0 : tj1 = x;
11320 0 : wsr_wcheb(x, -4.700240e+00, &tj, &tj1, &result, _state);
11321 0 : wsr_wcheb(x, -4.883080e+00, &tj, &tj1, &result, _state);
11322 0 : wsr_wcheb(x, -9.132168e-01, &tj, &tj1, &result, _state);
11323 0 : wsr_wcheb(x, -3.512684e-02, &tj, &tj1, &result, _state);
11324 0 : wsr_wcheb(x, 1.726342e-03, &tj, &tj1, &result, _state);
11325 0 : wsr_wcheb(x, -5.189796e-04, &tj, &tj1, &result, _state);
11326 0 : wsr_wcheb(x, -1.628659e-06, &tj, &tj1, &result, _state);
11327 0 : wsr_wcheb(x, 4.261786e-05, &tj, &tj1, &result, _state);
11328 0 : wsr_wcheb(x, -4.002498e-05, &tj, &tj1, &result, _state);
11329 0 : wsr_wcheb(x, 3.146287e-05, &tj, &tj1, &result, _state);
11330 0 : wsr_wcheb(x, -2.727576e-05, &tj, &tj1, &result, _state);
11331 0 : return result;
11332 : }
11333 :
11334 :
11335 : /*************************************************************************
11336 : Tail(S,N), S>=0
11337 : *************************************************************************/
11338 0 : static double wsr_wsigma(double s, ae_int_t n, ae_state *_state)
11339 : {
11340 : double f0;
11341 : double f1;
11342 : double f2;
11343 : double f3;
11344 : double f4;
11345 : double x0;
11346 : double x1;
11347 : double x2;
11348 : double x3;
11349 : double x4;
11350 : double x;
11351 : double result;
11352 :
11353 :
11354 0 : result = (double)(0);
11355 0 : if( n==5 )
11356 : {
11357 0 : result = wsr_w5(s, _state);
11358 : }
11359 0 : if( n==6 )
11360 : {
11361 0 : result = wsr_w6(s, _state);
11362 : }
11363 0 : if( n==7 )
11364 : {
11365 0 : result = wsr_w7(s, _state);
11366 : }
11367 0 : if( n==8 )
11368 : {
11369 0 : result = wsr_w8(s, _state);
11370 : }
11371 0 : if( n==9 )
11372 : {
11373 0 : result = wsr_w9(s, _state);
11374 : }
11375 0 : if( n==10 )
11376 : {
11377 0 : result = wsr_w10(s, _state);
11378 : }
11379 0 : if( n==11 )
11380 : {
11381 0 : result = wsr_w11(s, _state);
11382 : }
11383 0 : if( n==12 )
11384 : {
11385 0 : result = wsr_w12(s, _state);
11386 : }
11387 0 : if( n==13 )
11388 : {
11389 0 : result = wsr_w13(s, _state);
11390 : }
11391 0 : if( n==14 )
11392 : {
11393 0 : result = wsr_w14(s, _state);
11394 : }
11395 0 : if( n==15 )
11396 : {
11397 0 : result = wsr_w15(s, _state);
11398 : }
11399 0 : if( n==16 )
11400 : {
11401 0 : result = wsr_w16(s, _state);
11402 : }
11403 0 : if( n==17 )
11404 : {
11405 0 : result = wsr_w17(s, _state);
11406 : }
11407 0 : if( n==18 )
11408 : {
11409 0 : result = wsr_w18(s, _state);
11410 : }
11411 0 : if( n==19 )
11412 : {
11413 0 : result = wsr_w19(s, _state);
11414 : }
11415 0 : if( n==20 )
11416 : {
11417 0 : result = wsr_w20(s, _state);
11418 : }
11419 0 : if( n==21 )
11420 : {
11421 0 : result = wsr_w21(s, _state);
11422 : }
11423 0 : if( n==22 )
11424 : {
11425 0 : result = wsr_w22(s, _state);
11426 : }
11427 0 : if( n==23 )
11428 : {
11429 0 : result = wsr_w23(s, _state);
11430 : }
11431 0 : if( n==24 )
11432 : {
11433 0 : result = wsr_w24(s, _state);
11434 : }
11435 0 : if( n==25 )
11436 : {
11437 0 : result = wsr_w25(s, _state);
11438 : }
11439 0 : if( n==26 )
11440 : {
11441 0 : result = wsr_w26(s, _state);
11442 : }
11443 0 : if( n==27 )
11444 : {
11445 0 : result = wsr_w27(s, _state);
11446 : }
11447 0 : if( n==28 )
11448 : {
11449 0 : result = wsr_w28(s, _state);
11450 : }
11451 0 : if( n==29 )
11452 : {
11453 0 : result = wsr_w29(s, _state);
11454 : }
11455 0 : if( n==30 )
11456 : {
11457 0 : result = wsr_w30(s, _state);
11458 : }
11459 0 : if( n>30 )
11460 : {
11461 0 : x = 1.0/n;
11462 0 : x0 = 1.0/30;
11463 0 : f0 = wsr_w30(s, _state);
11464 0 : x1 = 1.0/40;
11465 0 : f1 = wsr_w40(s, _state);
11466 0 : x2 = 1.0/60;
11467 0 : f2 = wsr_w60(s, _state);
11468 0 : x3 = 1.0/120;
11469 0 : f3 = wsr_w120(s, _state);
11470 0 : x4 = 1.0/200;
11471 0 : f4 = wsr_w200(s, _state);
11472 0 : f1 = ((x-x0)*f1-(x-x1)*f0)/(x1-x0);
11473 0 : f2 = ((x-x0)*f2-(x-x2)*f0)/(x2-x0);
11474 0 : f3 = ((x-x0)*f3-(x-x3)*f0)/(x3-x0);
11475 0 : f4 = ((x-x0)*f4-(x-x4)*f0)/(x4-x0);
11476 0 : f2 = ((x-x1)*f2-(x-x2)*f1)/(x2-x1);
11477 0 : f3 = ((x-x1)*f3-(x-x3)*f1)/(x3-x1);
11478 0 : f4 = ((x-x1)*f4-(x-x4)*f1)/(x4-x1);
11479 0 : f3 = ((x-x2)*f3-(x-x3)*f2)/(x3-x2);
11480 0 : f4 = ((x-x2)*f4-(x-x4)*f2)/(x4-x2);
11481 0 : f4 = ((x-x3)*f4-(x-x4)*f3)/(x4-x3);
11482 0 : result = f4;
11483 : }
11484 0 : return result;
11485 : }
11486 :
11487 :
11488 : #endif
11489 : #if defined(AE_COMPILE_STEST) || !defined(AE_PARTIAL_BUILD)
11490 :
11491 :
11492 : /*************************************************************************
11493 : Sign test
11494 :
11495 : This test checks three hypotheses about the median of the given sample.
11496 : The following tests are performed:
11497 : * two-tailed test (null hypothesis - the median is equal to the given
11498 : value)
11499 : * left-tailed test (null hypothesis - the median is greater than or
11500 : equal to the given value)
11501 : * right-tailed test (null hypothesis - the median is less than or
11502 : equal to the given value)
11503 :
11504 : Requirements:
11505 : * the scale of measurement should be ordinal, interval or ratio (i.e.
11506 : the test could not be applied to nominal variables).
11507 :
11508 : The test is non-parametric and doesn't require distribution X to be normal
11509 :
11510 : Input parameters:
11511 : X - sample. Array whose index goes from 0 to N-1.
11512 : N - size of the sample.
11513 : Median - assumed median value.
11514 :
11515 : Output parameters:
11516 : BothTails - p-value for two-tailed test.
11517 : If BothTails is less than the given significance level
11518 : the null hypothesis is rejected.
11519 : LeftTail - p-value for left-tailed test.
11520 : If LeftTail is less than the given significance level,
11521 : the null hypothesis is rejected.
11522 : RightTail - p-value for right-tailed test.
11523 : If RightTail is less than the given significance level
11524 : the null hypothesis is rejected.
11525 :
11526 : While calculating p-values high-precision binomial distribution
11527 : approximation is used, so significance levels have about 15 exact digits.
11528 :
11529 : -- ALGLIB --
11530 : Copyright 08.09.2006 by Bochkanov Sergey
11531 : *************************************************************************/
11532 0 : void onesamplesigntest(/* Real */ ae_vector* x,
11533 : ae_int_t n,
11534 : double median,
11535 : double* bothtails,
11536 : double* lefttail,
11537 : double* righttail,
11538 : ae_state *_state)
11539 : {
11540 : ae_int_t i;
11541 : ae_int_t gtcnt;
11542 : ae_int_t necnt;
11543 :
11544 0 : *bothtails = 0;
11545 0 : *lefttail = 0;
11546 0 : *righttail = 0;
11547 :
11548 0 : if( n<=1 )
11549 : {
11550 0 : *bothtails = 1.0;
11551 0 : *lefttail = 1.0;
11552 0 : *righttail = 1.0;
11553 0 : return;
11554 : }
11555 :
11556 : /*
11557 : * Calculate:
11558 : * GTCnt - count of x[i]>Median
11559 : * NECnt - count of x[i]<>Median
11560 : */
11561 0 : gtcnt = 0;
11562 0 : necnt = 0;
11563 0 : for(i=0; i<=n-1; i++)
11564 : {
11565 0 : if( ae_fp_greater(x->ptr.p_double[i],median) )
11566 : {
11567 0 : gtcnt = gtcnt+1;
11568 : }
11569 0 : if( ae_fp_neq(x->ptr.p_double[i],median) )
11570 : {
11571 0 : necnt = necnt+1;
11572 : }
11573 : }
11574 0 : if( necnt==0 )
11575 : {
11576 :
11577 : /*
11578 : * all x[i] are equal to Median.
11579 : * So we can conclude that Median is a true median :)
11580 : */
11581 0 : *bothtails = 1.0;
11582 0 : *lefttail = 1.0;
11583 0 : *righttail = 1.0;
11584 0 : return;
11585 : }
11586 0 : *bothtails = ae_minreal(2*binomialdistribution(ae_minint(gtcnt, necnt-gtcnt, _state), necnt, 0.5, _state), 1.0, _state);
11587 0 : *lefttail = binomialdistribution(gtcnt, necnt, 0.5, _state);
11588 0 : *righttail = binomialcdistribution(gtcnt-1, necnt, 0.5, _state);
11589 : }
11590 :
11591 :
11592 : #endif
11593 : #if defined(AE_COMPILE_CORRELATIONTESTS) || !defined(AE_PARTIAL_BUILD)
11594 :
11595 :
11596 : /*************************************************************************
11597 : Pearson's correlation coefficient significance test
11598 :
11599 : This test checks hypotheses about whether X and Y are samples of two
11600 : continuous distributions having zero correlation or whether their
11601 : correlation is non-zero.
11602 :
11603 : The following tests are performed:
11604 : * two-tailed test (null hypothesis - X and Y have zero correlation)
11605 : * left-tailed test (null hypothesis - the correlation coefficient is
11606 : greater than or equal to 0)
11607 : * right-tailed test (null hypothesis - the correlation coefficient is
11608 : less than or equal to 0).
11609 :
11610 : Requirements:
11611 : * the number of elements in each sample is not less than 5
11612 : * normality of distributions of X and Y.
11613 :
11614 : Input parameters:
11615 : R - Pearson's correlation coefficient for X and Y
11616 : N - number of elements in samples, N>=5.
11617 :
11618 : Output parameters:
11619 : BothTails - p-value for two-tailed test.
11620 : If BothTails is less than the given significance level
11621 : the null hypothesis is rejected.
11622 : LeftTail - p-value for left-tailed test.
11623 : If LeftTail is less than the given significance level,
11624 : the null hypothesis is rejected.
11625 : RightTail - p-value for right-tailed test.
11626 : If RightTail is less than the given significance level
11627 : the null hypothesis is rejected.
11628 :
11629 : -- ALGLIB --
11630 : Copyright 09.04.2007 by Bochkanov Sergey
11631 : *************************************************************************/
11632 0 : void pearsoncorrelationsignificance(double r,
11633 : ae_int_t n,
11634 : double* bothtails,
11635 : double* lefttail,
11636 : double* righttail,
11637 : ae_state *_state)
11638 : {
11639 : double t;
11640 : double p;
11641 :
11642 0 : *bothtails = 0;
11643 0 : *lefttail = 0;
11644 0 : *righttail = 0;
11645 :
11646 :
11647 : /*
11648 : * Some special cases
11649 : */
11650 0 : if( ae_fp_greater_eq(r,(double)(1)) )
11651 : {
11652 0 : *bothtails = 0.0;
11653 0 : *lefttail = 1.0;
11654 0 : *righttail = 0.0;
11655 0 : return;
11656 : }
11657 0 : if( ae_fp_less_eq(r,(double)(-1)) )
11658 : {
11659 0 : *bothtails = 0.0;
11660 0 : *lefttail = 0.0;
11661 0 : *righttail = 1.0;
11662 0 : return;
11663 : }
11664 0 : if( n<5 )
11665 : {
11666 0 : *bothtails = 1.0;
11667 0 : *lefttail = 1.0;
11668 0 : *righttail = 1.0;
11669 0 : return;
11670 : }
11671 :
11672 : /*
11673 : * General case
11674 : */
11675 0 : t = r*ae_sqrt((n-2)/(1-ae_sqr(r, _state)), _state);
11676 0 : p = studenttdistribution(n-2, t, _state);
11677 0 : *bothtails = 2*ae_minreal(p, 1-p, _state);
11678 0 : *lefttail = p;
11679 0 : *righttail = 1-p;
11680 : }
11681 :
11682 :
11683 : /*************************************************************************
11684 : Spearman's rank correlation coefficient significance test
11685 :
11686 : This test checks hypotheses about whether X and Y are samples of two
11687 : continuous distributions having zero correlation or whether their
11688 : correlation is non-zero.
11689 :
11690 : The following tests are performed:
11691 : * two-tailed test (null hypothesis - X and Y have zero correlation)
11692 : * left-tailed test (null hypothesis - the correlation coefficient is
11693 : greater than or equal to 0)
11694 : * right-tailed test (null hypothesis - the correlation coefficient is
11695 : less than or equal to 0).
11696 :
11697 : Requirements:
11698 : * the number of elements in each sample is not less than 5.
11699 :
11700 : The test is non-parametric and doesn't require distributions X and Y to be
11701 : normal.
11702 :
11703 : Input parameters:
11704 : R - Spearman's rank correlation coefficient for X and Y
11705 : N - number of elements in samples, N>=5.
11706 :
11707 : Output parameters:
11708 : BothTails - p-value for two-tailed test.
11709 : If BothTails is less than the given significance level
11710 : the null hypothesis is rejected.
11711 : LeftTail - p-value for left-tailed test.
11712 : If LeftTail is less than the given significance level,
11713 : the null hypothesis is rejected.
11714 : RightTail - p-value for right-tailed test.
11715 : If RightTail is less than the given significance level
11716 : the null hypothesis is rejected.
11717 :
11718 : -- ALGLIB --
11719 : Copyright 09.04.2007 by Bochkanov Sergey
11720 : *************************************************************************/
11721 0 : void spearmanrankcorrelationsignificance(double r,
11722 : ae_int_t n,
11723 : double* bothtails,
11724 : double* lefttail,
11725 : double* righttail,
11726 : ae_state *_state)
11727 : {
11728 : double t;
11729 : double p;
11730 :
11731 0 : *bothtails = 0;
11732 0 : *lefttail = 0;
11733 0 : *righttail = 0;
11734 :
11735 :
11736 : /*
11737 : * Special case
11738 : */
11739 0 : if( n<5 )
11740 : {
11741 0 : *bothtails = 1.0;
11742 0 : *lefttail = 1.0;
11743 0 : *righttail = 1.0;
11744 0 : return;
11745 : }
11746 :
11747 : /*
11748 : * General case
11749 : */
11750 0 : if( ae_fp_greater_eq(r,(double)(1)) )
11751 : {
11752 0 : t = 1.0E10;
11753 : }
11754 : else
11755 : {
11756 0 : if( ae_fp_less_eq(r,(double)(-1)) )
11757 : {
11758 0 : t = -1.0E10;
11759 : }
11760 : else
11761 : {
11762 0 : t = r*ae_sqrt((n-2)/(1-ae_sqr(r, _state)), _state);
11763 : }
11764 : }
11765 0 : if( ae_fp_less(t,(double)(0)) )
11766 : {
11767 0 : p = correlationtests_spearmantail(t, n, _state);
11768 0 : *bothtails = 2*p;
11769 0 : *lefttail = p;
11770 0 : *righttail = 1-p;
11771 : }
11772 : else
11773 : {
11774 0 : p = correlationtests_spearmantail(-t, n, _state);
11775 0 : *bothtails = 2*p;
11776 0 : *lefttail = 1-p;
11777 0 : *righttail = p;
11778 : }
11779 : }
11780 :
11781 :
11782 : /*************************************************************************
11783 : Tail(S, 5)
11784 : *************************************************************************/
11785 0 : static double correlationtests_spearmantail5(double s, ae_state *_state)
11786 : {
11787 : double result;
11788 :
11789 :
11790 0 : if( ae_fp_less(s,0.000e+00) )
11791 : {
11792 0 : result = studenttdistribution(3, -s, _state);
11793 0 : return result;
11794 : }
11795 0 : if( ae_fp_greater_eq(s,3.580e+00) )
11796 : {
11797 0 : result = 8.304e-03;
11798 0 : return result;
11799 : }
11800 0 : if( ae_fp_greater_eq(s,2.322e+00) )
11801 : {
11802 0 : result = 4.163e-02;
11803 0 : return result;
11804 : }
11805 0 : if( ae_fp_greater_eq(s,1.704e+00) )
11806 : {
11807 0 : result = 6.641e-02;
11808 0 : return result;
11809 : }
11810 0 : if( ae_fp_greater_eq(s,1.303e+00) )
11811 : {
11812 0 : result = 1.164e-01;
11813 0 : return result;
11814 : }
11815 0 : if( ae_fp_greater_eq(s,1.003e+00) )
11816 : {
11817 0 : result = 1.748e-01;
11818 0 : return result;
11819 : }
11820 0 : if( ae_fp_greater_eq(s,7.584e-01) )
11821 : {
11822 0 : result = 2.249e-01;
11823 0 : return result;
11824 : }
11825 0 : if( ae_fp_greater_eq(s,5.468e-01) )
11826 : {
11827 0 : result = 2.581e-01;
11828 0 : return result;
11829 : }
11830 0 : if( ae_fp_greater_eq(s,3.555e-01) )
11831 : {
11832 0 : result = 3.413e-01;
11833 0 : return result;
11834 : }
11835 0 : if( ae_fp_greater_eq(s,1.759e-01) )
11836 : {
11837 0 : result = 3.911e-01;
11838 0 : return result;
11839 : }
11840 0 : if( ae_fp_greater_eq(s,1.741e-03) )
11841 : {
11842 0 : result = 4.747e-01;
11843 0 : return result;
11844 : }
11845 0 : if( ae_fp_greater_eq(s,0.000e+00) )
11846 : {
11847 0 : result = 5.248e-01;
11848 0 : return result;
11849 : }
11850 0 : result = (double)(0);
11851 0 : return result;
11852 : }
11853 :
11854 :
11855 : /*************************************************************************
11856 : Tail(S, 6)
11857 : *************************************************************************/
11858 0 : static double correlationtests_spearmantail6(double s, ae_state *_state)
11859 : {
11860 : double result;
11861 :
11862 :
11863 0 : if( ae_fp_less(s,1.001e+00) )
11864 : {
11865 0 : result = studenttdistribution(4, -s, _state);
11866 0 : return result;
11867 : }
11868 0 : if( ae_fp_greater_eq(s,5.663e+00) )
11869 : {
11870 0 : result = 1.366e-03;
11871 0 : return result;
11872 : }
11873 0 : if( ae_fp_greater_eq(s,3.834e+00) )
11874 : {
11875 0 : result = 8.350e-03;
11876 0 : return result;
11877 : }
11878 0 : if( ae_fp_greater_eq(s,2.968e+00) )
11879 : {
11880 0 : result = 1.668e-02;
11881 0 : return result;
11882 : }
11883 0 : if( ae_fp_greater_eq(s,2.430e+00) )
11884 : {
11885 0 : result = 2.921e-02;
11886 0 : return result;
11887 : }
11888 0 : if( ae_fp_greater_eq(s,2.045e+00) )
11889 : {
11890 0 : result = 5.144e-02;
11891 0 : return result;
11892 : }
11893 0 : if( ae_fp_greater_eq(s,1.747e+00) )
11894 : {
11895 0 : result = 6.797e-02;
11896 0 : return result;
11897 : }
11898 0 : if( ae_fp_greater_eq(s,1.502e+00) )
11899 : {
11900 0 : result = 8.752e-02;
11901 0 : return result;
11902 : }
11903 0 : if( ae_fp_greater_eq(s,1.295e+00) )
11904 : {
11905 0 : result = 1.210e-01;
11906 0 : return result;
11907 : }
11908 0 : if( ae_fp_greater_eq(s,1.113e+00) )
11909 : {
11910 0 : result = 1.487e-01;
11911 0 : return result;
11912 : }
11913 0 : if( ae_fp_greater_eq(s,1.001e+00) )
11914 : {
11915 0 : result = 1.780e-01;
11916 0 : return result;
11917 : }
11918 0 : result = (double)(0);
11919 0 : return result;
11920 : }
11921 :
11922 :
11923 : /*************************************************************************
11924 : Tail(S, 7)
11925 : *************************************************************************/
11926 0 : static double correlationtests_spearmantail7(double s, ae_state *_state)
11927 : {
11928 : double result;
11929 :
11930 :
11931 0 : if( ae_fp_less(s,1.001e+00) )
11932 : {
11933 0 : result = studenttdistribution(5, -s, _state);
11934 0 : return result;
11935 : }
11936 0 : if( ae_fp_greater_eq(s,8.159e+00) )
11937 : {
11938 0 : result = 2.081e-04;
11939 0 : return result;
11940 : }
11941 0 : if( ae_fp_greater_eq(s,5.620e+00) )
11942 : {
11943 0 : result = 1.393e-03;
11944 0 : return result;
11945 : }
11946 0 : if( ae_fp_greater_eq(s,4.445e+00) )
11947 : {
11948 0 : result = 3.398e-03;
11949 0 : return result;
11950 : }
11951 0 : if( ae_fp_greater_eq(s,3.728e+00) )
11952 : {
11953 0 : result = 6.187e-03;
11954 0 : return result;
11955 : }
11956 0 : if( ae_fp_greater_eq(s,3.226e+00) )
11957 : {
11958 0 : result = 1.200e-02;
11959 0 : return result;
11960 : }
11961 0 : if( ae_fp_greater_eq(s,2.844e+00) )
11962 : {
11963 0 : result = 1.712e-02;
11964 0 : return result;
11965 : }
11966 0 : if( ae_fp_greater_eq(s,2.539e+00) )
11967 : {
11968 0 : result = 2.408e-02;
11969 0 : return result;
11970 : }
11971 0 : if( ae_fp_greater_eq(s,2.285e+00) )
11972 : {
11973 0 : result = 3.320e-02;
11974 0 : return result;
11975 : }
11976 0 : if( ae_fp_greater_eq(s,2.068e+00) )
11977 : {
11978 0 : result = 4.406e-02;
11979 0 : return result;
11980 : }
11981 0 : if( ae_fp_greater_eq(s,1.879e+00) )
11982 : {
11983 0 : result = 5.478e-02;
11984 0 : return result;
11985 : }
11986 0 : if( ae_fp_greater_eq(s,1.710e+00) )
11987 : {
11988 0 : result = 6.946e-02;
11989 0 : return result;
11990 : }
11991 0 : if( ae_fp_greater_eq(s,1.559e+00) )
11992 : {
11993 0 : result = 8.331e-02;
11994 0 : return result;
11995 : }
11996 0 : if( ae_fp_greater_eq(s,1.420e+00) )
11997 : {
11998 0 : result = 1.001e-01;
11999 0 : return result;
12000 : }
12001 0 : if( ae_fp_greater_eq(s,1.292e+00) )
12002 : {
12003 0 : result = 1.180e-01;
12004 0 : return result;
12005 : }
12006 0 : if( ae_fp_greater_eq(s,1.173e+00) )
12007 : {
12008 0 : result = 1.335e-01;
12009 0 : return result;
12010 : }
12011 0 : if( ae_fp_greater_eq(s,1.062e+00) )
12012 : {
12013 0 : result = 1.513e-01;
12014 0 : return result;
12015 : }
12016 0 : if( ae_fp_greater_eq(s,1.001e+00) )
12017 : {
12018 0 : result = 1.770e-01;
12019 0 : return result;
12020 : }
12021 0 : result = (double)(0);
12022 0 : return result;
12023 : }
12024 :
12025 :
12026 : /*************************************************************************
12027 : Tail(S, 8)
12028 : *************************************************************************/
12029 0 : static double correlationtests_spearmantail8(double s, ae_state *_state)
12030 : {
12031 : double result;
12032 :
12033 :
12034 0 : if( ae_fp_less(s,2.001e+00) )
12035 : {
12036 0 : result = studenttdistribution(6, -s, _state);
12037 0 : return result;
12038 : }
12039 0 : if( ae_fp_greater_eq(s,1.103e+01) )
12040 : {
12041 0 : result = 2.194e-05;
12042 0 : return result;
12043 : }
12044 0 : if( ae_fp_greater_eq(s,7.685e+00) )
12045 : {
12046 0 : result = 2.008e-04;
12047 0 : return result;
12048 : }
12049 0 : if( ae_fp_greater_eq(s,6.143e+00) )
12050 : {
12051 0 : result = 5.686e-04;
12052 0 : return result;
12053 : }
12054 0 : if( ae_fp_greater_eq(s,5.213e+00) )
12055 : {
12056 0 : result = 1.138e-03;
12057 0 : return result;
12058 : }
12059 0 : if( ae_fp_greater_eq(s,4.567e+00) )
12060 : {
12061 0 : result = 2.310e-03;
12062 0 : return result;
12063 : }
12064 0 : if( ae_fp_greater_eq(s,4.081e+00) )
12065 : {
12066 0 : result = 3.634e-03;
12067 0 : return result;
12068 : }
12069 0 : if( ae_fp_greater_eq(s,3.697e+00) )
12070 : {
12071 0 : result = 5.369e-03;
12072 0 : return result;
12073 : }
12074 0 : if( ae_fp_greater_eq(s,3.381e+00) )
12075 : {
12076 0 : result = 7.708e-03;
12077 0 : return result;
12078 : }
12079 0 : if( ae_fp_greater_eq(s,3.114e+00) )
12080 : {
12081 0 : result = 1.087e-02;
12082 0 : return result;
12083 : }
12084 0 : if( ae_fp_greater_eq(s,2.884e+00) )
12085 : {
12086 0 : result = 1.397e-02;
12087 0 : return result;
12088 : }
12089 0 : if( ae_fp_greater_eq(s,2.682e+00) )
12090 : {
12091 0 : result = 1.838e-02;
12092 0 : return result;
12093 : }
12094 0 : if( ae_fp_greater_eq(s,2.502e+00) )
12095 : {
12096 0 : result = 2.288e-02;
12097 0 : return result;
12098 : }
12099 0 : if( ae_fp_greater_eq(s,2.340e+00) )
12100 : {
12101 0 : result = 2.883e-02;
12102 0 : return result;
12103 : }
12104 0 : if( ae_fp_greater_eq(s,2.192e+00) )
12105 : {
12106 0 : result = 3.469e-02;
12107 0 : return result;
12108 : }
12109 0 : if( ae_fp_greater_eq(s,2.057e+00) )
12110 : {
12111 0 : result = 4.144e-02;
12112 0 : return result;
12113 : }
12114 0 : if( ae_fp_greater_eq(s,2.001e+00) )
12115 : {
12116 0 : result = 4.804e-02;
12117 0 : return result;
12118 : }
12119 0 : result = (double)(0);
12120 0 : return result;
12121 : }
12122 :
12123 :
12124 : /*************************************************************************
12125 : Tail(S, 9)
12126 : *************************************************************************/
12127 0 : static double correlationtests_spearmantail9(double s, ae_state *_state)
12128 : {
12129 : double result;
12130 :
12131 :
12132 0 : if( ae_fp_less(s,2.001e+00) )
12133 : {
12134 0 : result = studenttdistribution(7, -s, _state);
12135 0 : return result;
12136 : }
12137 0 : if( ae_fp_greater_eq(s,9.989e+00) )
12138 : {
12139 0 : result = 2.306e-05;
12140 0 : return result;
12141 : }
12142 0 : if( ae_fp_greater_eq(s,8.069e+00) )
12143 : {
12144 0 : result = 8.167e-05;
12145 0 : return result;
12146 : }
12147 0 : if( ae_fp_greater_eq(s,6.890e+00) )
12148 : {
12149 0 : result = 1.744e-04;
12150 0 : return result;
12151 : }
12152 0 : if( ae_fp_greater_eq(s,6.077e+00) )
12153 : {
12154 0 : result = 3.625e-04;
12155 0 : return result;
12156 : }
12157 0 : if( ae_fp_greater_eq(s,5.469e+00) )
12158 : {
12159 0 : result = 6.450e-04;
12160 0 : return result;
12161 : }
12162 0 : if( ae_fp_greater_eq(s,4.991e+00) )
12163 : {
12164 0 : result = 1.001e-03;
12165 0 : return result;
12166 : }
12167 0 : if( ae_fp_greater_eq(s,4.600e+00) )
12168 : {
12169 0 : result = 1.514e-03;
12170 0 : return result;
12171 : }
12172 0 : if( ae_fp_greater_eq(s,4.272e+00) )
12173 : {
12174 0 : result = 2.213e-03;
12175 0 : return result;
12176 : }
12177 0 : if( ae_fp_greater_eq(s,3.991e+00) )
12178 : {
12179 0 : result = 2.990e-03;
12180 0 : return result;
12181 : }
12182 0 : if( ae_fp_greater_eq(s,3.746e+00) )
12183 : {
12184 0 : result = 4.101e-03;
12185 0 : return result;
12186 : }
12187 0 : if( ae_fp_greater_eq(s,3.530e+00) )
12188 : {
12189 0 : result = 5.355e-03;
12190 0 : return result;
12191 : }
12192 0 : if( ae_fp_greater_eq(s,3.336e+00) )
12193 : {
12194 0 : result = 6.887e-03;
12195 0 : return result;
12196 : }
12197 0 : if( ae_fp_greater_eq(s,3.161e+00) )
12198 : {
12199 0 : result = 8.598e-03;
12200 0 : return result;
12201 : }
12202 0 : if( ae_fp_greater_eq(s,3.002e+00) )
12203 : {
12204 0 : result = 1.065e-02;
12205 0 : return result;
12206 : }
12207 0 : if( ae_fp_greater_eq(s,2.855e+00) )
12208 : {
12209 0 : result = 1.268e-02;
12210 0 : return result;
12211 : }
12212 0 : if( ae_fp_greater_eq(s,2.720e+00) )
12213 : {
12214 0 : result = 1.552e-02;
12215 0 : return result;
12216 : }
12217 0 : if( ae_fp_greater_eq(s,2.595e+00) )
12218 : {
12219 0 : result = 1.836e-02;
12220 0 : return result;
12221 : }
12222 0 : if( ae_fp_greater_eq(s,2.477e+00) )
12223 : {
12224 0 : result = 2.158e-02;
12225 0 : return result;
12226 : }
12227 0 : if( ae_fp_greater_eq(s,2.368e+00) )
12228 : {
12229 0 : result = 2.512e-02;
12230 0 : return result;
12231 : }
12232 0 : if( ae_fp_greater_eq(s,2.264e+00) )
12233 : {
12234 0 : result = 2.942e-02;
12235 0 : return result;
12236 : }
12237 0 : if( ae_fp_greater_eq(s,2.166e+00) )
12238 : {
12239 0 : result = 3.325e-02;
12240 0 : return result;
12241 : }
12242 0 : if( ae_fp_greater_eq(s,2.073e+00) )
12243 : {
12244 0 : result = 3.800e-02;
12245 0 : return result;
12246 : }
12247 0 : if( ae_fp_greater_eq(s,2.001e+00) )
12248 : {
12249 0 : result = 4.285e-02;
12250 0 : return result;
12251 : }
12252 0 : result = (double)(0);
12253 0 : return result;
12254 : }
12255 :
12256 :
12257 : /*************************************************************************
12258 : Tail(T,N), accepts T<0
12259 : *************************************************************************/
12260 0 : static double correlationtests_spearmantail(double t,
12261 : ae_int_t n,
12262 : ae_state *_state)
12263 : {
12264 : double result;
12265 :
12266 :
12267 0 : if( n==5 )
12268 : {
12269 0 : result = correlationtests_spearmantail5(-t, _state);
12270 0 : return result;
12271 : }
12272 0 : if( n==6 )
12273 : {
12274 0 : result = correlationtests_spearmantail6(-t, _state);
12275 0 : return result;
12276 : }
12277 0 : if( n==7 )
12278 : {
12279 0 : result = correlationtests_spearmantail7(-t, _state);
12280 0 : return result;
12281 : }
12282 0 : if( n==8 )
12283 : {
12284 0 : result = correlationtests_spearmantail8(-t, _state);
12285 0 : return result;
12286 : }
12287 0 : if( n==9 )
12288 : {
12289 0 : result = correlationtests_spearmantail9(-t, _state);
12290 0 : return result;
12291 : }
12292 0 : result = studenttdistribution(n-2, t, _state);
12293 0 : return result;
12294 : }
12295 :
12296 :
12297 : #endif
12298 : #if defined(AE_COMPILE_STUDENTTTESTS) || !defined(AE_PARTIAL_BUILD)
12299 :
12300 :
12301 : /*************************************************************************
12302 : One-sample t-test
12303 :
12304 : This test checks three hypotheses about the mean of the given sample. The
12305 : following tests are performed:
12306 : * two-tailed test (null hypothesis - the mean is equal to the given
12307 : value)
12308 : * left-tailed test (null hypothesis - the mean is greater than or
12309 : equal to the given value)
12310 : * right-tailed test (null hypothesis - the mean is less than or equal
12311 : to the given value).
12312 :
12313 : The test is based on the assumption that a given sample has a normal
12314 : distribution and an unknown dispersion. If the distribution sharply
12315 : differs from normal, the test will work incorrectly.
12316 :
12317 : INPUT PARAMETERS:
12318 : X - sample. Array whose index goes from 0 to N-1.
12319 : N - size of sample, N>=0
12320 : Mean - assumed value of the mean.
12321 :
12322 : OUTPUT PARAMETERS:
12323 : BothTails - p-value for two-tailed test.
12324 : If BothTails is less than the given significance level
12325 : the null hypothesis is rejected.
12326 : LeftTail - p-value for left-tailed test.
12327 : If LeftTail is less than the given significance level,
12328 : the null hypothesis is rejected.
12329 : RightTail - p-value for right-tailed test.
12330 : If RightTail is less than the given significance level
12331 : the null hypothesis is rejected.
12332 :
12333 : NOTE: this function correctly handles degenerate cases:
12334 : * when N=0, all p-values are set to 1.0
12335 : * when variance of X[] is exactly zero, p-values are set
12336 : to 1.0 or 0.0, depending on difference between sample mean and
12337 : value of mean being tested.
12338 :
12339 :
12340 : -- ALGLIB --
12341 : Copyright 08.09.2006 by Bochkanov Sergey
12342 : *************************************************************************/
12343 0 : void studentttest1(/* Real */ ae_vector* x,
12344 : ae_int_t n,
12345 : double mean,
12346 : double* bothtails,
12347 : double* lefttail,
12348 : double* righttail,
12349 : ae_state *_state)
12350 : {
12351 : ae_int_t i;
12352 : double xmean;
12353 : double x0;
12354 : double v;
12355 : ae_bool samex;
12356 : double xvariance;
12357 : double xstddev;
12358 : double v1;
12359 : double v2;
12360 : double stat;
12361 : double s;
12362 :
12363 0 : *bothtails = 0;
12364 0 : *lefttail = 0;
12365 0 : *righttail = 0;
12366 :
12367 0 : if( n<=0 )
12368 : {
12369 0 : *bothtails = 1.0;
12370 0 : *lefttail = 1.0;
12371 0 : *righttail = 1.0;
12372 0 : return;
12373 : }
12374 :
12375 : /*
12376 : * Mean
12377 : */
12378 0 : xmean = (double)(0);
12379 0 : x0 = x->ptr.p_double[0];
12380 0 : samex = ae_true;
12381 0 : for(i=0; i<=n-1; i++)
12382 : {
12383 0 : v = x->ptr.p_double[i];
12384 0 : xmean = xmean+v;
12385 0 : samex = samex&&ae_fp_eq(v,x0);
12386 : }
12387 0 : if( samex )
12388 : {
12389 0 : xmean = x0;
12390 : }
12391 : else
12392 : {
12393 0 : xmean = xmean/n;
12394 : }
12395 :
12396 : /*
12397 : * Variance (using corrected two-pass algorithm)
12398 : */
12399 0 : xvariance = (double)(0);
12400 0 : xstddev = (double)(0);
12401 0 : if( n!=1&&!samex )
12402 : {
12403 0 : v1 = (double)(0);
12404 0 : for(i=0; i<=n-1; i++)
12405 : {
12406 0 : v1 = v1+ae_sqr(x->ptr.p_double[i]-xmean, _state);
12407 : }
12408 0 : v2 = (double)(0);
12409 0 : for(i=0; i<=n-1; i++)
12410 : {
12411 0 : v2 = v2+(x->ptr.p_double[i]-xmean);
12412 : }
12413 0 : v2 = ae_sqr(v2, _state)/n;
12414 0 : xvariance = (v1-v2)/(n-1);
12415 0 : if( ae_fp_less(xvariance,(double)(0)) )
12416 : {
12417 0 : xvariance = (double)(0);
12418 : }
12419 0 : xstddev = ae_sqrt(xvariance, _state);
12420 : }
12421 0 : if( ae_fp_eq(xstddev,(double)(0)) )
12422 : {
12423 0 : if( ae_fp_eq(xmean,mean) )
12424 : {
12425 0 : *bothtails = 1.0;
12426 : }
12427 : else
12428 : {
12429 0 : *bothtails = 0.0;
12430 : }
12431 0 : if( ae_fp_greater_eq(xmean,mean) )
12432 : {
12433 0 : *lefttail = 1.0;
12434 : }
12435 : else
12436 : {
12437 0 : *lefttail = 0.0;
12438 : }
12439 0 : if( ae_fp_less_eq(xmean,mean) )
12440 : {
12441 0 : *righttail = 1.0;
12442 : }
12443 : else
12444 : {
12445 0 : *righttail = 0.0;
12446 : }
12447 0 : return;
12448 : }
12449 :
12450 : /*
12451 : * Statistic
12452 : */
12453 0 : stat = (xmean-mean)/(xstddev/ae_sqrt((double)(n), _state));
12454 0 : s = studenttdistribution(n-1, stat, _state);
12455 0 : *bothtails = 2*ae_minreal(s, 1-s, _state);
12456 0 : *lefttail = s;
12457 0 : *righttail = 1-s;
12458 : }
12459 :
12460 :
12461 : /*************************************************************************
12462 : Two-sample pooled test
12463 :
12464 : This test checks three hypotheses about the mean of the given samples. The
12465 : following tests are performed:
12466 : * two-tailed test (null hypothesis - the means are equal)
12467 : * left-tailed test (null hypothesis - the mean of the first sample is
12468 : greater than or equal to the mean of the second sample)
12469 : * right-tailed test (null hypothesis - the mean of the first sample is
12470 : less than or equal to the mean of the second sample).
12471 :
12472 : Test is based on the following assumptions:
12473 : * given samples have normal distributions
12474 : * dispersions are equal
12475 : * samples are independent.
12476 :
12477 : Input parameters:
12478 : X - sample 1. Array whose index goes from 0 to N-1.
12479 : N - size of sample.
12480 : Y - sample 2. Array whose index goes from 0 to M-1.
12481 : M - size of sample.
12482 :
12483 : Output parameters:
12484 : BothTails - p-value for two-tailed test.
12485 : If BothTails is less than the given significance level
12486 : the null hypothesis is rejected.
12487 : LeftTail - p-value for left-tailed test.
12488 : If LeftTail is less than the given significance level,
12489 : the null hypothesis is rejected.
12490 : RightTail - p-value for right-tailed test.
12491 : If RightTail is less than the given significance level
12492 : the null hypothesis is rejected.
12493 :
12494 : NOTE: this function correctly handles degenerate cases:
12495 : * when N=0 or M=0, all p-values are set to 1.0
12496 : * when both samples has exactly zero variance, p-values are set
12497 : to 1.0 or 0.0, depending on difference between means.
12498 :
12499 : -- ALGLIB --
12500 : Copyright 18.09.2006 by Bochkanov Sergey
12501 : *************************************************************************/
12502 0 : void studentttest2(/* Real */ ae_vector* x,
12503 : ae_int_t n,
12504 : /* Real */ ae_vector* y,
12505 : ae_int_t m,
12506 : double* bothtails,
12507 : double* lefttail,
12508 : double* righttail,
12509 : ae_state *_state)
12510 : {
12511 : ae_int_t i;
12512 : ae_bool samex;
12513 : ae_bool samey;
12514 : double x0;
12515 : double y0;
12516 : double xmean;
12517 : double ymean;
12518 : double v;
12519 : double stat;
12520 : double s;
12521 : double p;
12522 :
12523 0 : *bothtails = 0;
12524 0 : *lefttail = 0;
12525 0 : *righttail = 0;
12526 :
12527 0 : if( n<=0||m<=0 )
12528 : {
12529 0 : *bothtails = 1.0;
12530 0 : *lefttail = 1.0;
12531 0 : *righttail = 1.0;
12532 0 : return;
12533 : }
12534 :
12535 : /*
12536 : * Mean
12537 : */
12538 0 : xmean = (double)(0);
12539 0 : x0 = x->ptr.p_double[0];
12540 0 : samex = ae_true;
12541 0 : for(i=0; i<=n-1; i++)
12542 : {
12543 0 : v = x->ptr.p_double[i];
12544 0 : xmean = xmean+v;
12545 0 : samex = samex&&ae_fp_eq(v,x0);
12546 : }
12547 0 : if( samex )
12548 : {
12549 0 : xmean = x0;
12550 : }
12551 : else
12552 : {
12553 0 : xmean = xmean/n;
12554 : }
12555 0 : ymean = (double)(0);
12556 0 : y0 = y->ptr.p_double[0];
12557 0 : samey = ae_true;
12558 0 : for(i=0; i<=m-1; i++)
12559 : {
12560 0 : v = y->ptr.p_double[i];
12561 0 : ymean = ymean+v;
12562 0 : samey = samey&&ae_fp_eq(v,y0);
12563 : }
12564 0 : if( samey )
12565 : {
12566 0 : ymean = y0;
12567 : }
12568 : else
12569 : {
12570 0 : ymean = ymean/m;
12571 : }
12572 :
12573 : /*
12574 : * S
12575 : */
12576 0 : s = (double)(0);
12577 0 : if( n+m>2 )
12578 : {
12579 0 : for(i=0; i<=n-1; i++)
12580 : {
12581 0 : s = s+ae_sqr(x->ptr.p_double[i]-xmean, _state);
12582 : }
12583 0 : for(i=0; i<=m-1; i++)
12584 : {
12585 0 : s = s+ae_sqr(y->ptr.p_double[i]-ymean, _state);
12586 : }
12587 0 : s = ae_sqrt(s*((double)1/(double)n+(double)1/(double)m)/(n+m-2), _state);
12588 : }
12589 0 : if( ae_fp_eq(s,(double)(0)) )
12590 : {
12591 0 : if( ae_fp_eq(xmean,ymean) )
12592 : {
12593 0 : *bothtails = 1.0;
12594 : }
12595 : else
12596 : {
12597 0 : *bothtails = 0.0;
12598 : }
12599 0 : if( ae_fp_greater_eq(xmean,ymean) )
12600 : {
12601 0 : *lefttail = 1.0;
12602 : }
12603 : else
12604 : {
12605 0 : *lefttail = 0.0;
12606 : }
12607 0 : if( ae_fp_less_eq(xmean,ymean) )
12608 : {
12609 0 : *righttail = 1.0;
12610 : }
12611 : else
12612 : {
12613 0 : *righttail = 0.0;
12614 : }
12615 0 : return;
12616 : }
12617 :
12618 : /*
12619 : * Statistic
12620 : */
12621 0 : stat = (xmean-ymean)/s;
12622 0 : p = studenttdistribution(n+m-2, stat, _state);
12623 0 : *bothtails = 2*ae_minreal(p, 1-p, _state);
12624 0 : *lefttail = p;
12625 0 : *righttail = 1-p;
12626 : }
12627 :
12628 :
12629 : /*************************************************************************
12630 : Two-sample unpooled test
12631 :
12632 : This test checks three hypotheses about the mean of the given samples. The
12633 : following tests are performed:
12634 : * two-tailed test (null hypothesis - the means are equal)
12635 : * left-tailed test (null hypothesis - the mean of the first sample is
12636 : greater than or equal to the mean of the second sample)
12637 : * right-tailed test (null hypothesis - the mean of the first sample is
12638 : less than or equal to the mean of the second sample).
12639 :
12640 : Test is based on the following assumptions:
12641 : * given samples have normal distributions
12642 : * samples are independent.
12643 : Equality of variances is NOT required.
12644 :
12645 : Input parameters:
12646 : X - sample 1. Array whose index goes from 0 to N-1.
12647 : N - size of the sample.
12648 : Y - sample 2. Array whose index goes from 0 to M-1.
12649 : M - size of the sample.
12650 :
12651 : Output parameters:
12652 : BothTails - p-value for two-tailed test.
12653 : If BothTails is less than the given significance level
12654 : the null hypothesis is rejected.
12655 : LeftTail - p-value for left-tailed test.
12656 : If LeftTail is less than the given significance level,
12657 : the null hypothesis is rejected.
12658 : RightTail - p-value for right-tailed test.
12659 : If RightTail is less than the given significance level
12660 : the null hypothesis is rejected.
12661 :
12662 : NOTE: this function correctly handles degenerate cases:
12663 : * when N=0 or M=0, all p-values are set to 1.0
12664 : * when both samples has zero variance, p-values are set
12665 : to 1.0 or 0.0, depending on difference between means.
12666 : * when only one sample has zero variance, test reduces to 1-sample
12667 : version.
12668 :
12669 : -- ALGLIB --
12670 : Copyright 18.09.2006 by Bochkanov Sergey
12671 : *************************************************************************/
12672 0 : void unequalvariancettest(/* Real */ ae_vector* x,
12673 : ae_int_t n,
12674 : /* Real */ ae_vector* y,
12675 : ae_int_t m,
12676 : double* bothtails,
12677 : double* lefttail,
12678 : double* righttail,
12679 : ae_state *_state)
12680 : {
12681 : ae_int_t i;
12682 : ae_bool samex;
12683 : ae_bool samey;
12684 : double x0;
12685 : double y0;
12686 : double xmean;
12687 : double ymean;
12688 : double xvar;
12689 : double yvar;
12690 : double v;
12691 : double df;
12692 : double p;
12693 : double stat;
12694 : double c;
12695 :
12696 0 : *bothtails = 0;
12697 0 : *lefttail = 0;
12698 0 : *righttail = 0;
12699 :
12700 0 : if( n<=0||m<=0 )
12701 : {
12702 0 : *bothtails = 1.0;
12703 0 : *lefttail = 1.0;
12704 0 : *righttail = 1.0;
12705 0 : return;
12706 : }
12707 :
12708 : /*
12709 : * Mean
12710 : */
12711 0 : xmean = (double)(0);
12712 0 : x0 = x->ptr.p_double[0];
12713 0 : samex = ae_true;
12714 0 : for(i=0; i<=n-1; i++)
12715 : {
12716 0 : v = x->ptr.p_double[i];
12717 0 : xmean = xmean+v;
12718 0 : samex = samex&&ae_fp_eq(v,x0);
12719 : }
12720 0 : if( samex )
12721 : {
12722 0 : xmean = x0;
12723 : }
12724 : else
12725 : {
12726 0 : xmean = xmean/n;
12727 : }
12728 0 : ymean = (double)(0);
12729 0 : y0 = y->ptr.p_double[0];
12730 0 : samey = ae_true;
12731 0 : for(i=0; i<=m-1; i++)
12732 : {
12733 0 : v = y->ptr.p_double[i];
12734 0 : ymean = ymean+v;
12735 0 : samey = samey&&ae_fp_eq(v,y0);
12736 : }
12737 0 : if( samey )
12738 : {
12739 0 : ymean = y0;
12740 : }
12741 : else
12742 : {
12743 0 : ymean = ymean/m;
12744 : }
12745 :
12746 : /*
12747 : * Variance (using corrected two-pass algorithm)
12748 : */
12749 0 : xvar = (double)(0);
12750 0 : if( n>=2&&!samex )
12751 : {
12752 0 : for(i=0; i<=n-1; i++)
12753 : {
12754 0 : xvar = xvar+ae_sqr(x->ptr.p_double[i]-xmean, _state);
12755 : }
12756 0 : xvar = xvar/(n-1);
12757 : }
12758 0 : yvar = (double)(0);
12759 0 : if( m>=2&&!samey )
12760 : {
12761 0 : for(i=0; i<=m-1; i++)
12762 : {
12763 0 : yvar = yvar+ae_sqr(y->ptr.p_double[i]-ymean, _state);
12764 : }
12765 0 : yvar = yvar/(m-1);
12766 : }
12767 :
12768 : /*
12769 : * Handle different special cases
12770 : * (one or both variances are zero).
12771 : */
12772 0 : if( ae_fp_eq(xvar,(double)(0))&&ae_fp_eq(yvar,(double)(0)) )
12773 : {
12774 0 : if( ae_fp_eq(xmean,ymean) )
12775 : {
12776 0 : *bothtails = 1.0;
12777 : }
12778 : else
12779 : {
12780 0 : *bothtails = 0.0;
12781 : }
12782 0 : if( ae_fp_greater_eq(xmean,ymean) )
12783 : {
12784 0 : *lefttail = 1.0;
12785 : }
12786 : else
12787 : {
12788 0 : *lefttail = 0.0;
12789 : }
12790 0 : if( ae_fp_less_eq(xmean,ymean) )
12791 : {
12792 0 : *righttail = 1.0;
12793 : }
12794 : else
12795 : {
12796 0 : *righttail = 0.0;
12797 : }
12798 0 : return;
12799 : }
12800 0 : if( ae_fp_eq(xvar,(double)(0)) )
12801 : {
12802 :
12803 : /*
12804 : * X is constant, unpooled 2-sample test reduces to 1-sample test.
12805 : *
12806 : * NOTE: right-tail and left-tail must be passed to 1-sample
12807 : * t-test in reverse order because we reverse order of
12808 : * of samples.
12809 : */
12810 0 : studentttest1(y, m, xmean, bothtails, righttail, lefttail, _state);
12811 0 : return;
12812 : }
12813 0 : if( ae_fp_eq(yvar,(double)(0)) )
12814 : {
12815 :
12816 : /*
12817 : * Y is constant, unpooled 2-sample test reduces to 1-sample test.
12818 : */
12819 0 : studentttest1(x, n, ymean, bothtails, lefttail, righttail, _state);
12820 0 : return;
12821 : }
12822 :
12823 : /*
12824 : * Statistic
12825 : */
12826 0 : stat = (xmean-ymean)/ae_sqrt(xvar/n+yvar/m, _state);
12827 0 : c = xvar/n/(xvar/n+yvar/m);
12828 0 : df = rmul2((double)(n-1), (double)(m-1), _state)/((m-1)*ae_sqr(c, _state)+(n-1)*ae_sqr(1-c, _state));
12829 0 : if( ae_fp_greater(stat,(double)(0)) )
12830 : {
12831 0 : p = 1-0.5*incompletebeta(df/2, 0.5, df/(df+ae_sqr(stat, _state)), _state);
12832 : }
12833 : else
12834 : {
12835 0 : p = 0.5*incompletebeta(df/2, 0.5, df/(df+ae_sqr(stat, _state)), _state);
12836 : }
12837 0 : *bothtails = 2*ae_minreal(p, 1-p, _state);
12838 0 : *lefttail = p;
12839 0 : *righttail = 1-p;
12840 : }
12841 :
12842 :
12843 : #endif
12844 : #if defined(AE_COMPILE_MANNWHITNEYU) || !defined(AE_PARTIAL_BUILD)
12845 :
12846 :
12847 : /*************************************************************************
12848 : Mann-Whitney U-test
12849 :
12850 : This test checks hypotheses about whether X and Y are samples of two
12851 : continuous distributions of the same shape and same median or whether
12852 : their medians are different.
12853 :
12854 : The following tests are performed:
12855 : * two-tailed test (null hypothesis - the medians are equal)
12856 : * left-tailed test (null hypothesis - the median of the first sample
12857 : is greater than or equal to the median of the second sample)
12858 : * right-tailed test (null hypothesis - the median of the first sample
12859 : is less than or equal to the median of the second sample).
12860 :
12861 : Requirements:
12862 : * the samples are independent
12863 : * X and Y are continuous distributions (or discrete distributions well-
12864 : approximating continuous distributions)
12865 : * distributions of X and Y have the same shape. The only possible
12866 : difference is their position (i.e. the value of the median)
12867 : * the number of elements in each sample is not less than 5
12868 : * the scale of measurement should be ordinal, interval or ratio (i.e.
12869 : the test could not be applied to nominal variables).
12870 :
12871 : The test is non-parametric and doesn't require distributions to be normal.
12872 :
12873 : Input parameters:
12874 : X - sample 1. Array whose index goes from 0 to N-1.
12875 : N - size of the sample. N>=5
12876 : Y - sample 2. Array whose index goes from 0 to M-1.
12877 : M - size of the sample. M>=5
12878 :
12879 : Output parameters:
12880 : BothTails - p-value for two-tailed test.
12881 : If BothTails is less than the given significance level
12882 : the null hypothesis is rejected.
12883 : LeftTail - p-value for left-tailed test.
12884 : If LeftTail is less than the given significance level,
12885 : the null hypothesis is rejected.
12886 : RightTail - p-value for right-tailed test.
12887 : If RightTail is less than the given significance level
12888 : the null hypothesis is rejected.
12889 :
12890 : To calculate p-values, special approximation is used. This method lets us
12891 : calculate p-values with satisfactory accuracy in interval [0.0001, 1].
12892 : There is no approximation outside the [0.0001, 1] interval. Therefore, if
12893 : the significance level outlies this interval, the test returns 0.0001.
12894 :
12895 : Relative precision of approximation of p-value:
12896 :
12897 : N M Max.err. Rms.err.
12898 : 5..10 N..10 1.4e-02 6.0e-04
12899 : 5..10 N..100 2.2e-02 5.3e-06
12900 : 10..15 N..15 1.0e-02 3.2e-04
12901 : 10..15 N..100 1.0e-02 2.2e-05
12902 : 15..100 N..100 6.1e-03 2.7e-06
12903 :
12904 : For N,M>100 accuracy checks weren't put into practice, but taking into
12905 : account characteristics of asymptotic approximation used, precision should
12906 : not be sharply different from the values for interval [5, 100].
12907 :
12908 : NOTE: P-value approximation was optimized for 0.0001<=p<=0.2500. Thus,
12909 : P's outside of this interval are enforced to these bounds. Say, you
12910 : may quite often get P equal to exactly 0.25 or 0.0001.
12911 :
12912 : -- ALGLIB --
12913 : Copyright 09.04.2007 by Bochkanov Sergey
12914 : *************************************************************************/
12915 0 : void mannwhitneyutest(/* Real */ ae_vector* x,
12916 : ae_int_t n,
12917 : /* Real */ ae_vector* y,
12918 : ae_int_t m,
12919 : double* bothtails,
12920 : double* lefttail,
12921 : double* righttail,
12922 : ae_state *_state)
12923 : {
12924 : ae_frame _frame_block;
12925 : ae_int_t i;
12926 : ae_int_t j;
12927 : ae_int_t k;
12928 : ae_int_t t;
12929 : double tmp;
12930 : ae_int_t tmpi;
12931 : ae_int_t ns;
12932 : ae_vector r;
12933 : ae_vector c;
12934 : double u;
12935 : double p;
12936 : double mp;
12937 : double s;
12938 : double sigma;
12939 : double mu;
12940 : ae_int_t tiecount;
12941 : ae_vector tiesize;
12942 :
12943 0 : ae_frame_make(_state, &_frame_block);
12944 0 : memset(&r, 0, sizeof(r));
12945 0 : memset(&c, 0, sizeof(c));
12946 0 : memset(&tiesize, 0, sizeof(tiesize));
12947 0 : *bothtails = 0;
12948 0 : *lefttail = 0;
12949 0 : *righttail = 0;
12950 0 : ae_vector_init(&r, 0, DT_REAL, _state, ae_true);
12951 0 : ae_vector_init(&c, 0, DT_INT, _state, ae_true);
12952 0 : ae_vector_init(&tiesize, 0, DT_INT, _state, ae_true);
12953 :
12954 :
12955 : /*
12956 : * Prepare
12957 : */
12958 0 : if( n<=4||m<=4 )
12959 : {
12960 0 : *bothtails = 1.0;
12961 0 : *lefttail = 1.0;
12962 0 : *righttail = 1.0;
12963 0 : ae_frame_leave(_state);
12964 0 : return;
12965 : }
12966 0 : ns = n+m;
12967 0 : ae_vector_set_length(&r, ns-1+1, _state);
12968 0 : ae_vector_set_length(&c, ns-1+1, _state);
12969 0 : for(i=0; i<=n-1; i++)
12970 : {
12971 0 : r.ptr.p_double[i] = x->ptr.p_double[i];
12972 0 : c.ptr.p_int[i] = 0;
12973 : }
12974 0 : for(i=0; i<=m-1; i++)
12975 : {
12976 0 : r.ptr.p_double[n+i] = y->ptr.p_double[i];
12977 0 : c.ptr.p_int[n+i] = 1;
12978 : }
12979 :
12980 : /*
12981 : * sort {R, C}
12982 : */
12983 0 : if( ns!=1 )
12984 : {
12985 0 : i = 2;
12986 : do
12987 : {
12988 0 : t = i;
12989 0 : while(t!=1)
12990 : {
12991 0 : k = t/2;
12992 0 : if( ae_fp_greater_eq(r.ptr.p_double[k-1],r.ptr.p_double[t-1]) )
12993 : {
12994 0 : t = 1;
12995 : }
12996 : else
12997 : {
12998 0 : tmp = r.ptr.p_double[k-1];
12999 0 : r.ptr.p_double[k-1] = r.ptr.p_double[t-1];
13000 0 : r.ptr.p_double[t-1] = tmp;
13001 0 : tmpi = c.ptr.p_int[k-1];
13002 0 : c.ptr.p_int[k-1] = c.ptr.p_int[t-1];
13003 0 : c.ptr.p_int[t-1] = tmpi;
13004 0 : t = k;
13005 : }
13006 : }
13007 0 : i = i+1;
13008 : }
13009 0 : while(i<=ns);
13010 0 : i = ns-1;
13011 : do
13012 : {
13013 0 : tmp = r.ptr.p_double[i];
13014 0 : r.ptr.p_double[i] = r.ptr.p_double[0];
13015 0 : r.ptr.p_double[0] = tmp;
13016 0 : tmpi = c.ptr.p_int[i];
13017 0 : c.ptr.p_int[i] = c.ptr.p_int[0];
13018 0 : c.ptr.p_int[0] = tmpi;
13019 0 : t = 1;
13020 0 : while(t!=0)
13021 : {
13022 0 : k = 2*t;
13023 0 : if( k>i )
13024 : {
13025 0 : t = 0;
13026 : }
13027 : else
13028 : {
13029 0 : if( k<i )
13030 : {
13031 0 : if( ae_fp_greater(r.ptr.p_double[k],r.ptr.p_double[k-1]) )
13032 : {
13033 0 : k = k+1;
13034 : }
13035 : }
13036 0 : if( ae_fp_greater_eq(r.ptr.p_double[t-1],r.ptr.p_double[k-1]) )
13037 : {
13038 0 : t = 0;
13039 : }
13040 : else
13041 : {
13042 0 : tmp = r.ptr.p_double[k-1];
13043 0 : r.ptr.p_double[k-1] = r.ptr.p_double[t-1];
13044 0 : r.ptr.p_double[t-1] = tmp;
13045 0 : tmpi = c.ptr.p_int[k-1];
13046 0 : c.ptr.p_int[k-1] = c.ptr.p_int[t-1];
13047 0 : c.ptr.p_int[t-1] = tmpi;
13048 0 : t = k;
13049 : }
13050 : }
13051 : }
13052 0 : i = i-1;
13053 : }
13054 0 : while(i>=1);
13055 : }
13056 :
13057 : /*
13058 : * compute tied ranks
13059 : */
13060 0 : i = 0;
13061 0 : tiecount = 0;
13062 0 : ae_vector_set_length(&tiesize, ns-1+1, _state);
13063 0 : while(i<=ns-1)
13064 : {
13065 0 : j = i+1;
13066 0 : while(j<=ns-1)
13067 : {
13068 0 : if( ae_fp_neq(r.ptr.p_double[j],r.ptr.p_double[i]) )
13069 : {
13070 0 : break;
13071 : }
13072 0 : j = j+1;
13073 : }
13074 0 : for(k=i; k<=j-1; k++)
13075 : {
13076 0 : r.ptr.p_double[k] = 1+(double)(i+j-1)/(double)2;
13077 : }
13078 0 : tiesize.ptr.p_int[tiecount] = j-i;
13079 0 : tiecount = tiecount+1;
13080 0 : i = j;
13081 : }
13082 :
13083 : /*
13084 : * Compute U
13085 : */
13086 0 : u = (double)(0);
13087 0 : for(i=0; i<=ns-1; i++)
13088 : {
13089 0 : if( c.ptr.p_int[i]==0 )
13090 : {
13091 0 : u = u+r.ptr.p_double[i];
13092 : }
13093 : }
13094 0 : u = rmul2((double)(n), (double)(m), _state)+rmul2((double)(n), (double)(n+1), _state)*0.5-u;
13095 :
13096 : /*
13097 : * Result
13098 : */
13099 0 : mu = rmul2((double)(n), (double)(m), _state)/2;
13100 0 : tmp = ns*(ae_sqr((double)(ns), _state)-1)/12;
13101 0 : for(i=0; i<=tiecount-1; i++)
13102 : {
13103 0 : tmp = tmp-tiesize.ptr.p_int[i]*(ae_sqr((double)(tiesize.ptr.p_int[i]), _state)-1)/12;
13104 : }
13105 0 : sigma = ae_sqrt(rmul2((double)(n), (double)(m), _state)/ns/(ns-1)*tmp, _state);
13106 0 : s = (u-mu)/sigma;
13107 0 : if( ae_fp_less_eq(s,(double)(0)) )
13108 : {
13109 0 : p = ae_exp(mannwhitneyu_usigma(-(u-mu)/sigma, n, m, _state), _state);
13110 0 : mp = 1-ae_exp(mannwhitneyu_usigma(-(u-1-mu)/sigma, n, m, _state), _state);
13111 : }
13112 : else
13113 : {
13114 0 : mp = ae_exp(mannwhitneyu_usigma((u-mu)/sigma, n, m, _state), _state);
13115 0 : p = 1-ae_exp(mannwhitneyu_usigma((u+1-mu)/sigma, n, m, _state), _state);
13116 : }
13117 0 : *lefttail = boundval(ae_maxreal(mp, 1.0E-4, _state), 0.0001, 0.2500, _state);
13118 0 : *righttail = boundval(ae_maxreal(p, 1.0E-4, _state), 0.0001, 0.2500, _state);
13119 0 : *bothtails = 2*ae_minreal(*lefttail, *righttail, _state);
13120 0 : ae_frame_leave(_state);
13121 : }
13122 :
13123 :
13124 : /*************************************************************************
13125 : Sequential Chebyshev interpolation.
13126 : *************************************************************************/
13127 0 : static void mannwhitneyu_ucheb(double x,
13128 : double c,
13129 : double* tj,
13130 : double* tj1,
13131 : double* r,
13132 : ae_state *_state)
13133 : {
13134 : double t;
13135 :
13136 :
13137 0 : *r = *r+c*(*tj);
13138 0 : t = 2*x*(*tj1)-(*tj);
13139 0 : *tj = *tj1;
13140 0 : *tj1 = t;
13141 0 : }
13142 :
13143 :
13144 : /*************************************************************************
13145 : Three-point polynomial interpolation.
13146 : *************************************************************************/
13147 0 : static double mannwhitneyu_uninterpolate(double p1,
13148 : double p2,
13149 : double p3,
13150 : ae_int_t n,
13151 : ae_state *_state)
13152 : {
13153 : double t1;
13154 : double t2;
13155 : double t3;
13156 : double t;
13157 : double p12;
13158 : double p23;
13159 : double result;
13160 :
13161 :
13162 0 : t1 = 1.0/15.0;
13163 0 : t2 = 1.0/30.0;
13164 0 : t3 = 1.0/100.0;
13165 0 : t = 1.0/n;
13166 0 : p12 = ((t-t2)*p1+(t1-t)*p2)/(t1-t2);
13167 0 : p23 = ((t-t3)*p2+(t2-t)*p3)/(t2-t3);
13168 0 : result = ((t-t3)*p12+(t1-t)*p23)/(t1-t3);
13169 0 : return result;
13170 : }
13171 :
13172 :
13173 : /*************************************************************************
13174 : Tail(0, N1, N2)
13175 : *************************************************************************/
13176 0 : static double mannwhitneyu_usigma000(ae_int_t n1,
13177 : ae_int_t n2,
13178 : ae_state *_state)
13179 : {
13180 : double p1;
13181 : double p2;
13182 : double p3;
13183 : double result;
13184 :
13185 :
13186 0 : p1 = mannwhitneyu_uninterpolate(-6.76984e-01, -6.83700e-01, -6.89873e-01, n2, _state);
13187 0 : p2 = mannwhitneyu_uninterpolate(-6.83700e-01, -6.87311e-01, -6.90957e-01, n2, _state);
13188 0 : p3 = mannwhitneyu_uninterpolate(-6.89873e-01, -6.90957e-01, -6.92175e-01, n2, _state);
13189 0 : result = mannwhitneyu_uninterpolate(p1, p2, p3, n1, _state);
13190 0 : return result;
13191 : }
13192 :
13193 :
13194 : /*************************************************************************
13195 : Tail(0.75, N1, N2)
13196 : *************************************************************************/
13197 0 : static double mannwhitneyu_usigma075(ae_int_t n1,
13198 : ae_int_t n2,
13199 : ae_state *_state)
13200 : {
13201 : double p1;
13202 : double p2;
13203 : double p3;
13204 : double result;
13205 :
13206 :
13207 0 : p1 = mannwhitneyu_uninterpolate(-1.44500e+00, -1.45906e+00, -1.47063e+00, n2, _state);
13208 0 : p2 = mannwhitneyu_uninterpolate(-1.45906e+00, -1.46856e+00, -1.47644e+00, n2, _state);
13209 0 : p3 = mannwhitneyu_uninterpolate(-1.47063e+00, -1.47644e+00, -1.48100e+00, n2, _state);
13210 0 : result = mannwhitneyu_uninterpolate(p1, p2, p3, n1, _state);
13211 0 : return result;
13212 : }
13213 :
13214 :
13215 : /*************************************************************************
13216 : Tail(1.5, N1, N2)
13217 : *************************************************************************/
13218 0 : static double mannwhitneyu_usigma150(ae_int_t n1,
13219 : ae_int_t n2,
13220 : ae_state *_state)
13221 : {
13222 : double p1;
13223 : double p2;
13224 : double p3;
13225 : double result;
13226 :
13227 :
13228 0 : p1 = mannwhitneyu_uninterpolate(-2.65380e+00, -2.67352e+00, -2.69011e+00, n2, _state);
13229 0 : p2 = mannwhitneyu_uninterpolate(-2.67352e+00, -2.68591e+00, -2.69659e+00, n2, _state);
13230 0 : p3 = mannwhitneyu_uninterpolate(-2.69011e+00, -2.69659e+00, -2.70192e+00, n2, _state);
13231 0 : result = mannwhitneyu_uninterpolate(p1, p2, p3, n1, _state);
13232 0 : return result;
13233 : }
13234 :
13235 :
13236 : /*************************************************************************
13237 : Tail(2.25, N1, N2)
13238 : *************************************************************************/
13239 0 : static double mannwhitneyu_usigma225(ae_int_t n1,
13240 : ae_int_t n2,
13241 : ae_state *_state)
13242 : {
13243 : double p1;
13244 : double p2;
13245 : double p3;
13246 : double result;
13247 :
13248 :
13249 0 : p1 = mannwhitneyu_uninterpolate(-4.41465e+00, -4.42260e+00, -4.43702e+00, n2, _state);
13250 0 : p2 = mannwhitneyu_uninterpolate(-4.42260e+00, -4.41639e+00, -4.41928e+00, n2, _state);
13251 0 : p3 = mannwhitneyu_uninterpolate(-4.43702e+00, -4.41928e+00, -4.41030e+00, n2, _state);
13252 0 : result = mannwhitneyu_uninterpolate(p1, p2, p3, n1, _state);
13253 0 : return result;
13254 : }
13255 :
13256 :
13257 : /*************************************************************************
13258 : Tail(3.0, N1, N2)
13259 : *************************************************************************/
13260 0 : static double mannwhitneyu_usigma300(ae_int_t n1,
13261 : ae_int_t n2,
13262 : ae_state *_state)
13263 : {
13264 : double p1;
13265 : double p2;
13266 : double p3;
13267 : double result;
13268 :
13269 :
13270 0 : p1 = mannwhitneyu_uninterpolate(-6.89839e+00, -6.83477e+00, -6.82340e+00, n2, _state);
13271 0 : p2 = mannwhitneyu_uninterpolate(-6.83477e+00, -6.74559e+00, -6.71117e+00, n2, _state);
13272 0 : p3 = mannwhitneyu_uninterpolate(-6.82340e+00, -6.71117e+00, -6.64929e+00, n2, _state);
13273 0 : result = mannwhitneyu_uninterpolate(p1, p2, p3, n1, _state);
13274 0 : return result;
13275 : }
13276 :
13277 :
13278 : /*************************************************************************
13279 : Tail(3.33, N1, N2)
13280 : *************************************************************************/
13281 0 : static double mannwhitneyu_usigma333(ae_int_t n1,
13282 : ae_int_t n2,
13283 : ae_state *_state)
13284 : {
13285 : double p1;
13286 : double p2;
13287 : double p3;
13288 : double result;
13289 :
13290 :
13291 0 : p1 = mannwhitneyu_uninterpolate(-8.31272e+00, -8.17096e+00, -8.13125e+00, n2, _state);
13292 0 : p2 = mannwhitneyu_uninterpolate(-8.17096e+00, -8.00156e+00, -7.93245e+00, n2, _state);
13293 0 : p3 = mannwhitneyu_uninterpolate(-8.13125e+00, -7.93245e+00, -7.82502e+00, n2, _state);
13294 0 : result = mannwhitneyu_uninterpolate(p1, p2, p3, n1, _state);
13295 0 : return result;
13296 : }
13297 :
13298 :
13299 : /*************************************************************************
13300 : Tail(3.66, N1, N2)
13301 : *************************************************************************/
13302 0 : static double mannwhitneyu_usigma367(ae_int_t n1,
13303 : ae_int_t n2,
13304 : ae_state *_state)
13305 : {
13306 : double p1;
13307 : double p2;
13308 : double p3;
13309 : double result;
13310 :
13311 :
13312 0 : p1 = mannwhitneyu_uninterpolate(-9.98837e+00, -9.70844e+00, -9.62087e+00, n2, _state);
13313 0 : p2 = mannwhitneyu_uninterpolate(-9.70844e+00, -9.41156e+00, -9.28998e+00, n2, _state);
13314 0 : p3 = mannwhitneyu_uninterpolate(-9.62087e+00, -9.28998e+00, -9.11686e+00, n2, _state);
13315 0 : result = mannwhitneyu_uninterpolate(p1, p2, p3, n1, _state);
13316 0 : return result;
13317 : }
13318 :
13319 :
13320 : /*************************************************************************
13321 : Tail(4.0, N1, N2)
13322 : *************************************************************************/
13323 0 : static double mannwhitneyu_usigma400(ae_int_t n1,
13324 : ae_int_t n2,
13325 : ae_state *_state)
13326 : {
13327 : double p1;
13328 : double p2;
13329 : double p3;
13330 : double result;
13331 :
13332 :
13333 0 : p1 = mannwhitneyu_uninterpolate(-1.20250e+01, -1.14911e+01, -1.13231e+01, n2, _state);
13334 0 : p2 = mannwhitneyu_uninterpolate(-1.14911e+01, -1.09927e+01, -1.07937e+01, n2, _state);
13335 0 : p3 = mannwhitneyu_uninterpolate(-1.13231e+01, -1.07937e+01, -1.05285e+01, n2, _state);
13336 0 : result = mannwhitneyu_uninterpolate(p1, p2, p3, n1, _state);
13337 0 : return result;
13338 : }
13339 :
13340 :
13341 : /*************************************************************************
13342 : Tail(S, 5, 5)
13343 : *************************************************************************/
13344 0 : static double mannwhitneyu_utbln5n5(double s, ae_state *_state)
13345 : {
13346 : double x;
13347 : double tj;
13348 : double tj1;
13349 : double result;
13350 :
13351 :
13352 0 : result = (double)(0);
13353 0 : x = ae_minreal(2*(s-0.000000e+00)/2.611165e+00-1, 1.0, _state);
13354 0 : tj = (double)(1);
13355 0 : tj1 = x;
13356 0 : mannwhitneyu_ucheb(x, -2.596264e+00, &tj, &tj1, &result, _state);
13357 0 : mannwhitneyu_ucheb(x, -2.412086e+00, &tj, &tj1, &result, _state);
13358 0 : mannwhitneyu_ucheb(x, -4.858542e-01, &tj, &tj1, &result, _state);
13359 0 : mannwhitneyu_ucheb(x, -5.614282e-02, &tj, &tj1, &result, _state);
13360 0 : mannwhitneyu_ucheb(x, 3.372686e-03, &tj, &tj1, &result, _state);
13361 0 : mannwhitneyu_ucheb(x, 8.524731e-03, &tj, &tj1, &result, _state);
13362 0 : mannwhitneyu_ucheb(x, 4.435331e-03, &tj, &tj1, &result, _state);
13363 0 : mannwhitneyu_ucheb(x, 1.284665e-03, &tj, &tj1, &result, _state);
13364 0 : mannwhitneyu_ucheb(x, 4.184141e-03, &tj, &tj1, &result, _state);
13365 0 : mannwhitneyu_ucheb(x, 5.298360e-03, &tj, &tj1, &result, _state);
13366 0 : mannwhitneyu_ucheb(x, 7.447272e-04, &tj, &tj1, &result, _state);
13367 0 : mannwhitneyu_ucheb(x, -3.938769e-03, &tj, &tj1, &result, _state);
13368 0 : mannwhitneyu_ucheb(x, -4.276205e-03, &tj, &tj1, &result, _state);
13369 0 : mannwhitneyu_ucheb(x, -1.138481e-03, &tj, &tj1, &result, _state);
13370 0 : mannwhitneyu_ucheb(x, 8.684625e-04, &tj, &tj1, &result, _state);
13371 0 : mannwhitneyu_ucheb(x, 1.558104e-03, &tj, &tj1, &result, _state);
13372 0 : return result;
13373 : }
13374 :
13375 :
13376 : /*************************************************************************
13377 : Tail(S, 5, 6)
13378 : *************************************************************************/
13379 0 : static double mannwhitneyu_utbln5n6(double s, ae_state *_state)
13380 : {
13381 : double x;
13382 : double tj;
13383 : double tj1;
13384 : double result;
13385 :
13386 :
13387 0 : result = (double)(0);
13388 0 : x = ae_minreal(2*(s-0.000000e+00)/2.738613e+00-1, 1.0, _state);
13389 0 : tj = (double)(1);
13390 0 : tj1 = x;
13391 0 : mannwhitneyu_ucheb(x, -2.810459e+00, &tj, &tj1, &result, _state);
13392 0 : mannwhitneyu_ucheb(x, -2.684429e+00, &tj, &tj1, &result, _state);
13393 0 : mannwhitneyu_ucheb(x, -5.712858e-01, &tj, &tj1, &result, _state);
13394 0 : mannwhitneyu_ucheb(x, -8.009324e-02, &tj, &tj1, &result, _state);
13395 0 : mannwhitneyu_ucheb(x, -6.644391e-03, &tj, &tj1, &result, _state);
13396 0 : mannwhitneyu_ucheb(x, 6.034173e-03, &tj, &tj1, &result, _state);
13397 0 : mannwhitneyu_ucheb(x, 4.953498e-03, &tj, &tj1, &result, _state);
13398 0 : mannwhitneyu_ucheb(x, 3.279293e-03, &tj, &tj1, &result, _state);
13399 0 : mannwhitneyu_ucheb(x, 3.563485e-03, &tj, &tj1, &result, _state);
13400 0 : mannwhitneyu_ucheb(x, 4.971952e-03, &tj, &tj1, &result, _state);
13401 0 : mannwhitneyu_ucheb(x, 3.506309e-03, &tj, &tj1, &result, _state);
13402 0 : mannwhitneyu_ucheb(x, -1.541406e-04, &tj, &tj1, &result, _state);
13403 0 : mannwhitneyu_ucheb(x, -3.283205e-03, &tj, &tj1, &result, _state);
13404 0 : mannwhitneyu_ucheb(x, -3.016347e-03, &tj, &tj1, &result, _state);
13405 0 : mannwhitneyu_ucheb(x, -1.221626e-03, &tj, &tj1, &result, _state);
13406 0 : mannwhitneyu_ucheb(x, -1.286752e-03, &tj, &tj1, &result, _state);
13407 0 : return result;
13408 : }
13409 :
13410 :
13411 : /*************************************************************************
13412 : Tail(S, 5, 7)
13413 : *************************************************************************/
13414 0 : static double mannwhitneyu_utbln5n7(double s, ae_state *_state)
13415 : {
13416 : double x;
13417 : double tj;
13418 : double tj1;
13419 : double result;
13420 :
13421 :
13422 0 : result = (double)(0);
13423 0 : x = ae_minreal(2*(s-0.000000e+00)/2.841993e+00-1, 1.0, _state);
13424 0 : tj = (double)(1);
13425 0 : tj1 = x;
13426 0 : mannwhitneyu_ucheb(x, -2.994677e+00, &tj, &tj1, &result, _state);
13427 0 : mannwhitneyu_ucheb(x, -2.923264e+00, &tj, &tj1, &result, _state);
13428 0 : mannwhitneyu_ucheb(x, -6.506190e-01, &tj, &tj1, &result, _state);
13429 0 : mannwhitneyu_ucheb(x, -1.054280e-01, &tj, &tj1, &result, _state);
13430 0 : mannwhitneyu_ucheb(x, -1.794587e-02, &tj, &tj1, &result, _state);
13431 0 : mannwhitneyu_ucheb(x, 1.726290e-03, &tj, &tj1, &result, _state);
13432 0 : mannwhitneyu_ucheb(x, 4.534180e-03, &tj, &tj1, &result, _state);
13433 0 : mannwhitneyu_ucheb(x, 4.517845e-03, &tj, &tj1, &result, _state);
13434 0 : mannwhitneyu_ucheb(x, 3.904428e-03, &tj, &tj1, &result, _state);
13435 0 : mannwhitneyu_ucheb(x, 3.882443e-03, &tj, &tj1, &result, _state);
13436 0 : mannwhitneyu_ucheb(x, 3.482988e-03, &tj, &tj1, &result, _state);
13437 0 : mannwhitneyu_ucheb(x, 2.114875e-03, &tj, &tj1, &result, _state);
13438 0 : mannwhitneyu_ucheb(x, -1.515082e-04, &tj, &tj1, &result, _state);
13439 0 : mannwhitneyu_ucheb(x, -1.996056e-03, &tj, &tj1, &result, _state);
13440 0 : mannwhitneyu_ucheb(x, -2.293581e-03, &tj, &tj1, &result, _state);
13441 0 : mannwhitneyu_ucheb(x, -2.349444e-03, &tj, &tj1, &result, _state);
13442 0 : return result;
13443 : }
13444 :
13445 :
13446 : /*************************************************************************
13447 : Tail(S, 5, 8)
13448 : *************************************************************************/
13449 0 : static double mannwhitneyu_utbln5n8(double s, ae_state *_state)
13450 : {
13451 : double x;
13452 : double tj;
13453 : double tj1;
13454 : double result;
13455 :
13456 :
13457 0 : result = (double)(0);
13458 0 : x = ae_minreal(2*(s-0.000000e+00)/2.927700e+00-1, 1.0, _state);
13459 0 : tj = (double)(1);
13460 0 : tj1 = x;
13461 0 : mannwhitneyu_ucheb(x, -3.155727e+00, &tj, &tj1, &result, _state);
13462 0 : mannwhitneyu_ucheb(x, -3.135078e+00, &tj, &tj1, &result, _state);
13463 0 : mannwhitneyu_ucheb(x, -7.247203e-01, &tj, &tj1, &result, _state);
13464 0 : mannwhitneyu_ucheb(x, -1.309697e-01, &tj, &tj1, &result, _state);
13465 0 : mannwhitneyu_ucheb(x, -2.993725e-02, &tj, &tj1, &result, _state);
13466 0 : mannwhitneyu_ucheb(x, -3.567219e-03, &tj, &tj1, &result, _state);
13467 0 : mannwhitneyu_ucheb(x, 3.383704e-03, &tj, &tj1, &result, _state);
13468 0 : mannwhitneyu_ucheb(x, 5.002188e-03, &tj, &tj1, &result, _state);
13469 0 : mannwhitneyu_ucheb(x, 4.487322e-03, &tj, &tj1, &result, _state);
13470 0 : mannwhitneyu_ucheb(x, 3.443899e-03, &tj, &tj1, &result, _state);
13471 0 : mannwhitneyu_ucheb(x, 2.688270e-03, &tj, &tj1, &result, _state);
13472 0 : mannwhitneyu_ucheb(x, 2.600339e-03, &tj, &tj1, &result, _state);
13473 0 : mannwhitneyu_ucheb(x, 1.874948e-03, &tj, &tj1, &result, _state);
13474 0 : mannwhitneyu_ucheb(x, 1.811593e-04, &tj, &tj1, &result, _state);
13475 0 : mannwhitneyu_ucheb(x, -1.072353e-03, &tj, &tj1, &result, _state);
13476 0 : mannwhitneyu_ucheb(x, -2.659457e-03, &tj, &tj1, &result, _state);
13477 0 : return result;
13478 : }
13479 :
13480 :
13481 : /*************************************************************************
13482 : Tail(S, 5, 9)
13483 : *************************************************************************/
13484 0 : static double mannwhitneyu_utbln5n9(double s, ae_state *_state)
13485 : {
13486 : double x;
13487 : double tj;
13488 : double tj1;
13489 : double result;
13490 :
13491 :
13492 0 : result = (double)(0);
13493 0 : x = ae_minreal(2*(s-0.000000e+00)/3.000000e+00-1, 1.0, _state);
13494 0 : tj = (double)(1);
13495 0 : tj1 = x;
13496 0 : mannwhitneyu_ucheb(x, -3.298162e+00, &tj, &tj1, &result, _state);
13497 0 : mannwhitneyu_ucheb(x, -3.325016e+00, &tj, &tj1, &result, _state);
13498 0 : mannwhitneyu_ucheb(x, -7.939852e-01, &tj, &tj1, &result, _state);
13499 0 : mannwhitneyu_ucheb(x, -1.563029e-01, &tj, &tj1, &result, _state);
13500 0 : mannwhitneyu_ucheb(x, -4.222652e-02, &tj, &tj1, &result, _state);
13501 0 : mannwhitneyu_ucheb(x, -9.195200e-03, &tj, &tj1, &result, _state);
13502 0 : mannwhitneyu_ucheb(x, 1.445665e-03, &tj, &tj1, &result, _state);
13503 0 : mannwhitneyu_ucheb(x, 5.204792e-03, &tj, &tj1, &result, _state);
13504 0 : mannwhitneyu_ucheb(x, 4.775217e-03, &tj, &tj1, &result, _state);
13505 0 : mannwhitneyu_ucheb(x, 3.527781e-03, &tj, &tj1, &result, _state);
13506 0 : mannwhitneyu_ucheb(x, 2.221948e-03, &tj, &tj1, &result, _state);
13507 0 : mannwhitneyu_ucheb(x, 2.242968e-03, &tj, &tj1, &result, _state);
13508 0 : mannwhitneyu_ucheb(x, 2.607959e-03, &tj, &tj1, &result, _state);
13509 0 : mannwhitneyu_ucheb(x, 1.771285e-03, &tj, &tj1, &result, _state);
13510 0 : mannwhitneyu_ucheb(x, 6.694026e-04, &tj, &tj1, &result, _state);
13511 0 : mannwhitneyu_ucheb(x, -1.481190e-03, &tj, &tj1, &result, _state);
13512 0 : return result;
13513 : }
13514 :
13515 :
13516 : /*************************************************************************
13517 : Tail(S, 5, 10)
13518 : *************************************************************************/
13519 0 : static double mannwhitneyu_utbln5n10(double s, ae_state *_state)
13520 : {
13521 : double x;
13522 : double tj;
13523 : double tj1;
13524 : double result;
13525 :
13526 :
13527 0 : result = (double)(0);
13528 0 : x = ae_minreal(2*(s-0.000000e+00)/3.061862e+00-1, 1.0, _state);
13529 0 : tj = (double)(1);
13530 0 : tj1 = x;
13531 0 : mannwhitneyu_ucheb(x, -3.425360e+00, &tj, &tj1, &result, _state);
13532 0 : mannwhitneyu_ucheb(x, -3.496710e+00, &tj, &tj1, &result, _state);
13533 0 : mannwhitneyu_ucheb(x, -8.587658e-01, &tj, &tj1, &result, _state);
13534 0 : mannwhitneyu_ucheb(x, -1.812005e-01, &tj, &tj1, &result, _state);
13535 0 : mannwhitneyu_ucheb(x, -5.427637e-02, &tj, &tj1, &result, _state);
13536 0 : mannwhitneyu_ucheb(x, -1.515702e-02, &tj, &tj1, &result, _state);
13537 0 : mannwhitneyu_ucheb(x, -5.406867e-04, &tj, &tj1, &result, _state);
13538 0 : mannwhitneyu_ucheb(x, 4.796295e-03, &tj, &tj1, &result, _state);
13539 0 : mannwhitneyu_ucheb(x, 5.237591e-03, &tj, &tj1, &result, _state);
13540 0 : mannwhitneyu_ucheb(x, 3.654249e-03, &tj, &tj1, &result, _state);
13541 0 : mannwhitneyu_ucheb(x, 2.181165e-03, &tj, &tj1, &result, _state);
13542 0 : mannwhitneyu_ucheb(x, 2.011665e-03, &tj, &tj1, &result, _state);
13543 0 : mannwhitneyu_ucheb(x, 2.417927e-03, &tj, &tj1, &result, _state);
13544 0 : mannwhitneyu_ucheb(x, 2.534880e-03, &tj, &tj1, &result, _state);
13545 0 : mannwhitneyu_ucheb(x, 1.791255e-03, &tj, &tj1, &result, _state);
13546 0 : mannwhitneyu_ucheb(x, 1.871512e-05, &tj, &tj1, &result, _state);
13547 0 : return result;
13548 : }
13549 :
13550 :
13551 : /*************************************************************************
13552 : Tail(S, 5, 11)
13553 : *************************************************************************/
13554 0 : static double mannwhitneyu_utbln5n11(double s, ae_state *_state)
13555 : {
13556 : double x;
13557 : double tj;
13558 : double tj1;
13559 : double result;
13560 :
13561 :
13562 0 : result = (double)(0);
13563 0 : x = ae_minreal(2*(s-0.000000e+00)/3.115427e+00-1, 1.0, _state);
13564 0 : tj = (double)(1);
13565 0 : tj1 = x;
13566 0 : mannwhitneyu_ucheb(x, -3.539959e+00, &tj, &tj1, &result, _state);
13567 0 : mannwhitneyu_ucheb(x, -3.652998e+00, &tj, &tj1, &result, _state);
13568 0 : mannwhitneyu_ucheb(x, -9.196503e-01, &tj, &tj1, &result, _state);
13569 0 : mannwhitneyu_ucheb(x, -2.054363e-01, &tj, &tj1, &result, _state);
13570 0 : mannwhitneyu_ucheb(x, -6.618848e-02, &tj, &tj1, &result, _state);
13571 0 : mannwhitneyu_ucheb(x, -2.109411e-02, &tj, &tj1, &result, _state);
13572 0 : mannwhitneyu_ucheb(x, -2.786668e-03, &tj, &tj1, &result, _state);
13573 0 : mannwhitneyu_ucheb(x, 4.215648e-03, &tj, &tj1, &result, _state);
13574 0 : mannwhitneyu_ucheb(x, 5.484220e-03, &tj, &tj1, &result, _state);
13575 0 : mannwhitneyu_ucheb(x, 3.935991e-03, &tj, &tj1, &result, _state);
13576 0 : mannwhitneyu_ucheb(x, 2.396191e-03, &tj, &tj1, &result, _state);
13577 0 : mannwhitneyu_ucheb(x, 1.894177e-03, &tj, &tj1, &result, _state);
13578 0 : mannwhitneyu_ucheb(x, 2.206979e-03, &tj, &tj1, &result, _state);
13579 0 : mannwhitneyu_ucheb(x, 2.519055e-03, &tj, &tj1, &result, _state);
13580 0 : mannwhitneyu_ucheb(x, 2.210326e-03, &tj, &tj1, &result, _state);
13581 0 : mannwhitneyu_ucheb(x, 1.189679e-03, &tj, &tj1, &result, _state);
13582 0 : return result;
13583 : }
13584 :
13585 :
13586 : /*************************************************************************
13587 : Tail(S, 5, 12)
13588 : *************************************************************************/
13589 0 : static double mannwhitneyu_utbln5n12(double s, ae_state *_state)
13590 : {
13591 : double x;
13592 : double tj;
13593 : double tj1;
13594 : double result;
13595 :
13596 :
13597 0 : result = (double)(0);
13598 0 : x = ae_minreal(2*(s-0.000000e+00)/3.162278e+00-1, 1.0, _state);
13599 0 : tj = (double)(1);
13600 0 : tj1 = x;
13601 0 : mannwhitneyu_ucheb(x, -3.644007e+00, &tj, &tj1, &result, _state);
13602 0 : mannwhitneyu_ucheb(x, -3.796173e+00, &tj, &tj1, &result, _state);
13603 0 : mannwhitneyu_ucheb(x, -9.771177e-01, &tj, &tj1, &result, _state);
13604 0 : mannwhitneyu_ucheb(x, -2.290043e-01, &tj, &tj1, &result, _state);
13605 0 : mannwhitneyu_ucheb(x, -7.794686e-02, &tj, &tj1, &result, _state);
13606 0 : mannwhitneyu_ucheb(x, -2.702110e-02, &tj, &tj1, &result, _state);
13607 0 : mannwhitneyu_ucheb(x, -5.185959e-03, &tj, &tj1, &result, _state);
13608 0 : mannwhitneyu_ucheb(x, 3.416259e-03, &tj, &tj1, &result, _state);
13609 0 : mannwhitneyu_ucheb(x, 5.592056e-03, &tj, &tj1, &result, _state);
13610 0 : mannwhitneyu_ucheb(x, 4.201530e-03, &tj, &tj1, &result, _state);
13611 0 : mannwhitneyu_ucheb(x, 2.754365e-03, &tj, &tj1, &result, _state);
13612 0 : mannwhitneyu_ucheb(x, 1.978945e-03, &tj, &tj1, &result, _state);
13613 0 : mannwhitneyu_ucheb(x, 2.012032e-03, &tj, &tj1, &result, _state);
13614 0 : mannwhitneyu_ucheb(x, 2.304579e-03, &tj, &tj1, &result, _state);
13615 0 : mannwhitneyu_ucheb(x, 2.100378e-03, &tj, &tj1, &result, _state);
13616 0 : mannwhitneyu_ucheb(x, 1.728269e-03, &tj, &tj1, &result, _state);
13617 0 : return result;
13618 : }
13619 :
13620 :
13621 : /*************************************************************************
13622 : Tail(S, 5, 13)
13623 : *************************************************************************/
13624 0 : static double mannwhitneyu_utbln5n13(double s, ae_state *_state)
13625 : {
13626 : double x;
13627 : double tj;
13628 : double tj1;
13629 : double result;
13630 :
13631 :
13632 0 : result = (double)(0);
13633 0 : x = ae_minreal(2*(s-0.000000e+00)/3.203616e+00-1, 1.0, _state);
13634 0 : tj = (double)(1);
13635 0 : tj1 = x;
13636 0 : mannwhitneyu_ucheb(x, -3.739120e+00, &tj, &tj1, &result, _state);
13637 0 : mannwhitneyu_ucheb(x, -3.928117e+00, &tj, &tj1, &result, _state);
13638 0 : mannwhitneyu_ucheb(x, -1.031605e+00, &tj, &tj1, &result, _state);
13639 0 : mannwhitneyu_ucheb(x, -2.519403e-01, &tj, &tj1, &result, _state);
13640 0 : mannwhitneyu_ucheb(x, -8.962648e-02, &tj, &tj1, &result, _state);
13641 0 : mannwhitneyu_ucheb(x, -3.292183e-02, &tj, &tj1, &result, _state);
13642 0 : mannwhitneyu_ucheb(x, -7.809293e-03, &tj, &tj1, &result, _state);
13643 0 : mannwhitneyu_ucheb(x, 2.465156e-03, &tj, &tj1, &result, _state);
13644 0 : mannwhitneyu_ucheb(x, 5.456278e-03, &tj, &tj1, &result, _state);
13645 0 : mannwhitneyu_ucheb(x, 4.446055e-03, &tj, &tj1, &result, _state);
13646 0 : mannwhitneyu_ucheb(x, 3.109490e-03, &tj, &tj1, &result, _state);
13647 0 : mannwhitneyu_ucheb(x, 2.218256e-03, &tj, &tj1, &result, _state);
13648 0 : mannwhitneyu_ucheb(x, 1.941479e-03, &tj, &tj1, &result, _state);
13649 0 : mannwhitneyu_ucheb(x, 2.058603e-03, &tj, &tj1, &result, _state);
13650 0 : mannwhitneyu_ucheb(x, 1.824402e-03, &tj, &tj1, &result, _state);
13651 0 : mannwhitneyu_ucheb(x, 1.830947e-03, &tj, &tj1, &result, _state);
13652 0 : return result;
13653 : }
13654 :
13655 :
13656 : /*************************************************************************
13657 : Tail(S, 5, 14)
13658 : *************************************************************************/
13659 0 : static double mannwhitneyu_utbln5n14(double s, ae_state *_state)
13660 : {
13661 : double x;
13662 : double tj;
13663 : double tj1;
13664 : double result;
13665 :
13666 :
13667 0 : result = (double)(0);
13668 0 : x = ae_minreal(2*(s-0.000000e+00)/3.240370e+00-1, 1.0, _state);
13669 0 : tj = (double)(1);
13670 0 : tj1 = x;
13671 0 : mannwhitneyu_ucheb(x, -3.826559e+00, &tj, &tj1, &result, _state);
13672 0 : mannwhitneyu_ucheb(x, -4.050370e+00, &tj, &tj1, &result, _state);
13673 0 : mannwhitneyu_ucheb(x, -1.083408e+00, &tj, &tj1, &result, _state);
13674 0 : mannwhitneyu_ucheb(x, -2.743164e-01, &tj, &tj1, &result, _state);
13675 0 : mannwhitneyu_ucheb(x, -1.012030e-01, &tj, &tj1, &result, _state);
13676 0 : mannwhitneyu_ucheb(x, -3.884686e-02, &tj, &tj1, &result, _state);
13677 0 : mannwhitneyu_ucheb(x, -1.059656e-02, &tj, &tj1, &result, _state);
13678 0 : mannwhitneyu_ucheb(x, 1.327521e-03, &tj, &tj1, &result, _state);
13679 0 : mannwhitneyu_ucheb(x, 5.134026e-03, &tj, &tj1, &result, _state);
13680 0 : mannwhitneyu_ucheb(x, 4.584201e-03, &tj, &tj1, &result, _state);
13681 0 : mannwhitneyu_ucheb(x, 3.440618e-03, &tj, &tj1, &result, _state);
13682 0 : mannwhitneyu_ucheb(x, 2.524133e-03, &tj, &tj1, &result, _state);
13683 0 : mannwhitneyu_ucheb(x, 1.990007e-03, &tj, &tj1, &result, _state);
13684 0 : mannwhitneyu_ucheb(x, 1.887334e-03, &tj, &tj1, &result, _state);
13685 0 : mannwhitneyu_ucheb(x, 1.534977e-03, &tj, &tj1, &result, _state);
13686 0 : mannwhitneyu_ucheb(x, 1.705395e-03, &tj, &tj1, &result, _state);
13687 0 : return result;
13688 : }
13689 :
13690 :
13691 : /*************************************************************************
13692 : Tail(S, 5, 15)
13693 : *************************************************************************/
13694 0 : static double mannwhitneyu_utbln5n15(double s, ae_state *_state)
13695 : {
13696 : double x;
13697 : double tj;
13698 : double tj1;
13699 : double result;
13700 :
13701 :
13702 0 : result = (double)(0);
13703 0 : x = ae_minreal(2*(s-0.000000e+00)/3.250000e+00-1, 1.0, _state);
13704 0 : tj = (double)(1);
13705 0 : tj1 = x;
13706 0 : mannwhitneyu_ucheb(x, -3.851572e+00, &tj, &tj1, &result, _state);
13707 0 : mannwhitneyu_ucheb(x, -4.082033e+00, &tj, &tj1, &result, _state);
13708 0 : mannwhitneyu_ucheb(x, -1.095983e+00, &tj, &tj1, &result, _state);
13709 0 : mannwhitneyu_ucheb(x, -2.814595e-01, &tj, &tj1, &result, _state);
13710 0 : mannwhitneyu_ucheb(x, -1.073148e-01, &tj, &tj1, &result, _state);
13711 0 : mannwhitneyu_ucheb(x, -4.420213e-02, &tj, &tj1, &result, _state);
13712 0 : mannwhitneyu_ucheb(x, -1.517175e-02, &tj, &tj1, &result, _state);
13713 0 : mannwhitneyu_ucheb(x, -2.344180e-03, &tj, &tj1, &result, _state);
13714 0 : mannwhitneyu_ucheb(x, 2.371393e-03, &tj, &tj1, &result, _state);
13715 0 : mannwhitneyu_ucheb(x, 2.711443e-03, &tj, &tj1, &result, _state);
13716 0 : mannwhitneyu_ucheb(x, 2.228569e-03, &tj, &tj1, &result, _state);
13717 0 : mannwhitneyu_ucheb(x, 1.683483e-03, &tj, &tj1, &result, _state);
13718 0 : mannwhitneyu_ucheb(x, 1.267112e-03, &tj, &tj1, &result, _state);
13719 0 : mannwhitneyu_ucheb(x, 1.156044e-03, &tj, &tj1, &result, _state);
13720 0 : mannwhitneyu_ucheb(x, 9.131316e-04, &tj, &tj1, &result, _state);
13721 0 : mannwhitneyu_ucheb(x, 1.301023e-03, &tj, &tj1, &result, _state);
13722 0 : return result;
13723 : }
13724 :
13725 :
13726 : /*************************************************************************
13727 : Tail(S, 5, 16)
13728 : *************************************************************************/
13729 0 : static double mannwhitneyu_utbln5n16(double s, ae_state *_state)
13730 : {
13731 : double x;
13732 : double tj;
13733 : double tj1;
13734 : double result;
13735 :
13736 :
13737 0 : result = (double)(0);
13738 0 : x = ae_minreal(2*(s-0.000000e+00)/3.250000e+00-1, 1.0, _state);
13739 0 : tj = (double)(1);
13740 0 : tj1 = x;
13741 0 : mannwhitneyu_ucheb(x, -3.852210e+00, &tj, &tj1, &result, _state);
13742 0 : mannwhitneyu_ucheb(x, -4.077482e+00, &tj, &tj1, &result, _state);
13743 0 : mannwhitneyu_ucheb(x, -1.091186e+00, &tj, &tj1, &result, _state);
13744 0 : mannwhitneyu_ucheb(x, -2.797282e-01, &tj, &tj1, &result, _state);
13745 0 : mannwhitneyu_ucheb(x, -1.084994e-01, &tj, &tj1, &result, _state);
13746 0 : mannwhitneyu_ucheb(x, -4.667054e-02, &tj, &tj1, &result, _state);
13747 0 : mannwhitneyu_ucheb(x, -1.843909e-02, &tj, &tj1, &result, _state);
13748 0 : mannwhitneyu_ucheb(x, -5.456732e-03, &tj, &tj1, &result, _state);
13749 0 : mannwhitneyu_ucheb(x, -5.039830e-04, &tj, &tj1, &result, _state);
13750 0 : mannwhitneyu_ucheb(x, 4.723508e-04, &tj, &tj1, &result, _state);
13751 0 : mannwhitneyu_ucheb(x, 3.940608e-04, &tj, &tj1, &result, _state);
13752 0 : mannwhitneyu_ucheb(x, 1.478285e-04, &tj, &tj1, &result, _state);
13753 0 : mannwhitneyu_ucheb(x, -1.649144e-04, &tj, &tj1, &result, _state);
13754 0 : mannwhitneyu_ucheb(x, -4.237703e-04, &tj, &tj1, &result, _state);
13755 0 : mannwhitneyu_ucheb(x, -4.707410e-04, &tj, &tj1, &result, _state);
13756 0 : mannwhitneyu_ucheb(x, -1.874293e-04, &tj, &tj1, &result, _state);
13757 0 : return result;
13758 : }
13759 :
13760 :
13761 : /*************************************************************************
13762 : Tail(S, 5, 17)
13763 : *************************************************************************/
13764 0 : static double mannwhitneyu_utbln5n17(double s, ae_state *_state)
13765 : {
13766 : double x;
13767 : double tj;
13768 : double tj1;
13769 : double result;
13770 :
13771 :
13772 0 : result = (double)(0);
13773 0 : x = ae_minreal(2*(s-0.000000e+00)/3.250000e+00-1, 1.0, _state);
13774 0 : tj = (double)(1);
13775 0 : tj1 = x;
13776 0 : mannwhitneyu_ucheb(x, -3.851752e+00, &tj, &tj1, &result, _state);
13777 0 : mannwhitneyu_ucheb(x, -4.071259e+00, &tj, &tj1, &result, _state);
13778 0 : mannwhitneyu_ucheb(x, -1.084700e+00, &tj, &tj1, &result, _state);
13779 0 : mannwhitneyu_ucheb(x, -2.758898e-01, &tj, &tj1, &result, _state);
13780 0 : mannwhitneyu_ucheb(x, -1.073846e-01, &tj, &tj1, &result, _state);
13781 0 : mannwhitneyu_ucheb(x, -4.684838e-02, &tj, &tj1, &result, _state);
13782 0 : mannwhitneyu_ucheb(x, -1.964936e-02, &tj, &tj1, &result, _state);
13783 0 : mannwhitneyu_ucheb(x, -6.782442e-03, &tj, &tj1, &result, _state);
13784 0 : mannwhitneyu_ucheb(x, -1.956362e-03, &tj, &tj1, &result, _state);
13785 0 : mannwhitneyu_ucheb(x, -5.984727e-04, &tj, &tj1, &result, _state);
13786 0 : mannwhitneyu_ucheb(x, -5.196936e-04, &tj, &tj1, &result, _state);
13787 0 : mannwhitneyu_ucheb(x, -5.558262e-04, &tj, &tj1, &result, _state);
13788 0 : mannwhitneyu_ucheb(x, -8.690746e-04, &tj, &tj1, &result, _state);
13789 0 : mannwhitneyu_ucheb(x, -1.364855e-03, &tj, &tj1, &result, _state);
13790 0 : mannwhitneyu_ucheb(x, -1.401006e-03, &tj, &tj1, &result, _state);
13791 0 : mannwhitneyu_ucheb(x, -1.546748e-03, &tj, &tj1, &result, _state);
13792 0 : return result;
13793 : }
13794 :
13795 :
13796 : /*************************************************************************
13797 : Tail(S, 5, 18)
13798 : *************************************************************************/
13799 0 : static double mannwhitneyu_utbln5n18(double s, ae_state *_state)
13800 : {
13801 : double x;
13802 : double tj;
13803 : double tj1;
13804 : double result;
13805 :
13806 :
13807 0 : result = (double)(0);
13808 0 : x = ae_minreal(2*(s-0.000000e+00)/3.250000e+00-1, 1.0, _state);
13809 0 : tj = (double)(1);
13810 0 : tj1 = x;
13811 0 : mannwhitneyu_ucheb(x, -3.850840e+00, &tj, &tj1, &result, _state);
13812 0 : mannwhitneyu_ucheb(x, -4.064799e+00, &tj, &tj1, &result, _state);
13813 0 : mannwhitneyu_ucheb(x, -1.077651e+00, &tj, &tj1, &result, _state);
13814 0 : mannwhitneyu_ucheb(x, -2.712659e-01, &tj, &tj1, &result, _state);
13815 0 : mannwhitneyu_ucheb(x, -1.049217e-01, &tj, &tj1, &result, _state);
13816 0 : mannwhitneyu_ucheb(x, -4.571333e-02, &tj, &tj1, &result, _state);
13817 0 : mannwhitneyu_ucheb(x, -1.929809e-02, &tj, &tj1, &result, _state);
13818 0 : mannwhitneyu_ucheb(x, -6.752044e-03, &tj, &tj1, &result, _state);
13819 0 : mannwhitneyu_ucheb(x, -1.949464e-03, &tj, &tj1, &result, _state);
13820 0 : mannwhitneyu_ucheb(x, -3.896101e-04, &tj, &tj1, &result, _state);
13821 0 : mannwhitneyu_ucheb(x, -4.614460e-05, &tj, &tj1, &result, _state);
13822 0 : mannwhitneyu_ucheb(x, 1.384357e-04, &tj, &tj1, &result, _state);
13823 0 : mannwhitneyu_ucheb(x, -6.489113e-05, &tj, &tj1, &result, _state);
13824 0 : mannwhitneyu_ucheb(x, -6.445725e-04, &tj, &tj1, &result, _state);
13825 0 : mannwhitneyu_ucheb(x, -8.945636e-04, &tj, &tj1, &result, _state);
13826 0 : mannwhitneyu_ucheb(x, -1.424653e-03, &tj, &tj1, &result, _state);
13827 0 : return result;
13828 : }
13829 :
13830 :
13831 : /*************************************************************************
13832 : Tail(S, 5, 19)
13833 : *************************************************************************/
13834 0 : static double mannwhitneyu_utbln5n19(double s, ae_state *_state)
13835 : {
13836 : double x;
13837 : double tj;
13838 : double tj1;
13839 : double result;
13840 :
13841 :
13842 0 : result = (double)(0);
13843 0 : x = ae_minreal(2*(s-0.000000e+00)/3.250000e+00-1, 1.0, _state);
13844 0 : tj = (double)(1);
13845 0 : tj1 = x;
13846 0 : mannwhitneyu_ucheb(x, -3.850027e+00, &tj, &tj1, &result, _state);
13847 0 : mannwhitneyu_ucheb(x, -4.059159e+00, &tj, &tj1, &result, _state);
13848 0 : mannwhitneyu_ucheb(x, -1.071106e+00, &tj, &tj1, &result, _state);
13849 0 : mannwhitneyu_ucheb(x, -2.669960e-01, &tj, &tj1, &result, _state);
13850 0 : mannwhitneyu_ucheb(x, -1.022780e-01, &tj, &tj1, &result, _state);
13851 0 : mannwhitneyu_ucheb(x, -4.442555e-02, &tj, &tj1, &result, _state);
13852 0 : mannwhitneyu_ucheb(x, -1.851335e-02, &tj, &tj1, &result, _state);
13853 0 : mannwhitneyu_ucheb(x, -6.433865e-03, &tj, &tj1, &result, _state);
13854 0 : mannwhitneyu_ucheb(x, -1.514465e-03, &tj, &tj1, &result, _state);
13855 0 : mannwhitneyu_ucheb(x, 1.332989e-04, &tj, &tj1, &result, _state);
13856 0 : mannwhitneyu_ucheb(x, 8.606099e-04, &tj, &tj1, &result, _state);
13857 0 : mannwhitneyu_ucheb(x, 1.341945e-03, &tj, &tj1, &result, _state);
13858 0 : mannwhitneyu_ucheb(x, 1.402164e-03, &tj, &tj1, &result, _state);
13859 0 : mannwhitneyu_ucheb(x, 1.039761e-03, &tj, &tj1, &result, _state);
13860 0 : mannwhitneyu_ucheb(x, 5.512831e-04, &tj, &tj1, &result, _state);
13861 0 : mannwhitneyu_ucheb(x, -3.284427e-05, &tj, &tj1, &result, _state);
13862 0 : return result;
13863 : }
13864 :
13865 :
13866 : /*************************************************************************
13867 : Tail(S, 5, 20)
13868 : *************************************************************************/
13869 0 : static double mannwhitneyu_utbln5n20(double s, ae_state *_state)
13870 : {
13871 : double x;
13872 : double tj;
13873 : double tj1;
13874 : double result;
13875 :
13876 :
13877 0 : result = (double)(0);
13878 0 : x = ae_minreal(2*(s-0.000000e+00)/3.250000e+00-1, 1.0, _state);
13879 0 : tj = (double)(1);
13880 0 : tj1 = x;
13881 0 : mannwhitneyu_ucheb(x, -3.849651e+00, &tj, &tj1, &result, _state);
13882 0 : mannwhitneyu_ucheb(x, -4.054729e+00, &tj, &tj1, &result, _state);
13883 0 : mannwhitneyu_ucheb(x, -1.065747e+00, &tj, &tj1, &result, _state);
13884 0 : mannwhitneyu_ucheb(x, -2.636243e-01, &tj, &tj1, &result, _state);
13885 0 : mannwhitneyu_ucheb(x, -1.003234e-01, &tj, &tj1, &result, _state);
13886 0 : mannwhitneyu_ucheb(x, -4.372789e-02, &tj, &tj1, &result, _state);
13887 0 : mannwhitneyu_ucheb(x, -1.831551e-02, &tj, &tj1, &result, _state);
13888 0 : mannwhitneyu_ucheb(x, -6.763090e-03, &tj, &tj1, &result, _state);
13889 0 : mannwhitneyu_ucheb(x, -1.830626e-03, &tj, &tj1, &result, _state);
13890 0 : mannwhitneyu_ucheb(x, -2.122384e-04, &tj, &tj1, &result, _state);
13891 0 : mannwhitneyu_ucheb(x, 8.108328e-04, &tj, &tj1, &result, _state);
13892 0 : mannwhitneyu_ucheb(x, 1.557983e-03, &tj, &tj1, &result, _state);
13893 0 : mannwhitneyu_ucheb(x, 1.945666e-03, &tj, &tj1, &result, _state);
13894 0 : mannwhitneyu_ucheb(x, 1.965696e-03, &tj, &tj1, &result, _state);
13895 0 : mannwhitneyu_ucheb(x, 1.493236e-03, &tj, &tj1, &result, _state);
13896 0 : mannwhitneyu_ucheb(x, 1.162591e-03, &tj, &tj1, &result, _state);
13897 0 : return result;
13898 : }
13899 :
13900 :
13901 : /*************************************************************************
13902 : Tail(S, 5, 21)
13903 : *************************************************************************/
13904 0 : static double mannwhitneyu_utbln5n21(double s, ae_state *_state)
13905 : {
13906 : double x;
13907 : double tj;
13908 : double tj1;
13909 : double result;
13910 :
13911 :
13912 0 : result = (double)(0);
13913 0 : x = ae_minreal(2*(s-0.000000e+00)/3.250000e+00-1, 1.0, _state);
13914 0 : tj = (double)(1);
13915 0 : tj1 = x;
13916 0 : mannwhitneyu_ucheb(x, -3.849649e+00, &tj, &tj1, &result, _state);
13917 0 : mannwhitneyu_ucheb(x, -4.051155e+00, &tj, &tj1, &result, _state);
13918 0 : mannwhitneyu_ucheb(x, -1.061430e+00, &tj, &tj1, &result, _state);
13919 0 : mannwhitneyu_ucheb(x, -2.608869e-01, &tj, &tj1, &result, _state);
13920 0 : mannwhitneyu_ucheb(x, -9.902788e-02, &tj, &tj1, &result, _state);
13921 0 : mannwhitneyu_ucheb(x, -4.346562e-02, &tj, &tj1, &result, _state);
13922 0 : mannwhitneyu_ucheb(x, -1.874709e-02, &tj, &tj1, &result, _state);
13923 0 : mannwhitneyu_ucheb(x, -7.682887e-03, &tj, &tj1, &result, _state);
13924 0 : mannwhitneyu_ucheb(x, -3.026206e-03, &tj, &tj1, &result, _state);
13925 0 : mannwhitneyu_ucheb(x, -1.534551e-03, &tj, &tj1, &result, _state);
13926 0 : mannwhitneyu_ucheb(x, -4.990575e-04, &tj, &tj1, &result, _state);
13927 0 : mannwhitneyu_ucheb(x, 3.713334e-04, &tj, &tj1, &result, _state);
13928 0 : mannwhitneyu_ucheb(x, 9.737011e-04, &tj, &tj1, &result, _state);
13929 0 : mannwhitneyu_ucheb(x, 1.304571e-03, &tj, &tj1, &result, _state);
13930 0 : mannwhitneyu_ucheb(x, 1.133110e-03, &tj, &tj1, &result, _state);
13931 0 : mannwhitneyu_ucheb(x, 1.123457e-03, &tj, &tj1, &result, _state);
13932 0 : return result;
13933 : }
13934 :
13935 :
13936 : /*************************************************************************
13937 : Tail(S, 5, 22)
13938 : *************************************************************************/
13939 0 : static double mannwhitneyu_utbln5n22(double s, ae_state *_state)
13940 : {
13941 : double x;
13942 : double tj;
13943 : double tj1;
13944 : double result;
13945 :
13946 :
13947 0 : result = (double)(0);
13948 0 : x = ae_minreal(2*(s-0.000000e+00)/3.250000e+00-1, 1.0, _state);
13949 0 : tj = (double)(1);
13950 0 : tj1 = x;
13951 0 : mannwhitneyu_ucheb(x, -3.849598e+00, &tj, &tj1, &result, _state);
13952 0 : mannwhitneyu_ucheb(x, -4.047605e+00, &tj, &tj1, &result, _state);
13953 0 : mannwhitneyu_ucheb(x, -1.057264e+00, &tj, &tj1, &result, _state);
13954 0 : mannwhitneyu_ucheb(x, -2.579513e-01, &tj, &tj1, &result, _state);
13955 0 : mannwhitneyu_ucheb(x, -9.749602e-02, &tj, &tj1, &result, _state);
13956 0 : mannwhitneyu_ucheb(x, -4.275137e-02, &tj, &tj1, &result, _state);
13957 0 : mannwhitneyu_ucheb(x, -1.881768e-02, &tj, &tj1, &result, _state);
13958 0 : mannwhitneyu_ucheb(x, -8.177374e-03, &tj, &tj1, &result, _state);
13959 0 : mannwhitneyu_ucheb(x, -3.981056e-03, &tj, &tj1, &result, _state);
13960 0 : mannwhitneyu_ucheb(x, -2.696290e-03, &tj, &tj1, &result, _state);
13961 0 : mannwhitneyu_ucheb(x, -1.886803e-03, &tj, &tj1, &result, _state);
13962 0 : mannwhitneyu_ucheb(x, -1.085378e-03, &tj, &tj1, &result, _state);
13963 0 : mannwhitneyu_ucheb(x, -4.675242e-04, &tj, &tj1, &result, _state);
13964 0 : mannwhitneyu_ucheb(x, -5.426367e-05, &tj, &tj1, &result, _state);
13965 0 : mannwhitneyu_ucheb(x, 1.039613e-04, &tj, &tj1, &result, _state);
13966 0 : mannwhitneyu_ucheb(x, 2.662378e-04, &tj, &tj1, &result, _state);
13967 0 : return result;
13968 : }
13969 :
13970 :
13971 : /*************************************************************************
13972 : Tail(S, 5, 23)
13973 : *************************************************************************/
13974 0 : static double mannwhitneyu_utbln5n23(double s, ae_state *_state)
13975 : {
13976 : double x;
13977 : double tj;
13978 : double tj1;
13979 : double result;
13980 :
13981 :
13982 0 : result = (double)(0);
13983 0 : x = ae_minreal(2*(s-0.000000e+00)/3.250000e+00-1, 1.0, _state);
13984 0 : tj = (double)(1);
13985 0 : tj1 = x;
13986 0 : mannwhitneyu_ucheb(x, -3.849269e+00, &tj, &tj1, &result, _state);
13987 0 : mannwhitneyu_ucheb(x, -4.043761e+00, &tj, &tj1, &result, _state);
13988 0 : mannwhitneyu_ucheb(x, -1.052735e+00, &tj, &tj1, &result, _state);
13989 0 : mannwhitneyu_ucheb(x, -2.544683e-01, &tj, &tj1, &result, _state);
13990 0 : mannwhitneyu_ucheb(x, -9.517503e-02, &tj, &tj1, &result, _state);
13991 0 : mannwhitneyu_ucheb(x, -4.112082e-02, &tj, &tj1, &result, _state);
13992 0 : mannwhitneyu_ucheb(x, -1.782070e-02, &tj, &tj1, &result, _state);
13993 0 : mannwhitneyu_ucheb(x, -7.549483e-03, &tj, &tj1, &result, _state);
13994 0 : mannwhitneyu_ucheb(x, -3.747329e-03, &tj, &tj1, &result, _state);
13995 0 : mannwhitneyu_ucheb(x, -2.694263e-03, &tj, &tj1, &result, _state);
13996 0 : mannwhitneyu_ucheb(x, -2.147141e-03, &tj, &tj1, &result, _state);
13997 0 : mannwhitneyu_ucheb(x, -1.526209e-03, &tj, &tj1, &result, _state);
13998 0 : mannwhitneyu_ucheb(x, -1.039173e-03, &tj, &tj1, &result, _state);
13999 0 : mannwhitneyu_ucheb(x, -7.235615e-04, &tj, &tj1, &result, _state);
14000 0 : mannwhitneyu_ucheb(x, -4.656546e-04, &tj, &tj1, &result, _state);
14001 0 : mannwhitneyu_ucheb(x, -3.014423e-04, &tj, &tj1, &result, _state);
14002 0 : return result;
14003 : }
14004 :
14005 :
14006 : /*************************************************************************
14007 : Tail(S, 5, 24)
14008 : *************************************************************************/
14009 0 : static double mannwhitneyu_utbln5n24(double s, ae_state *_state)
14010 : {
14011 : double x;
14012 : double tj;
14013 : double tj1;
14014 : double result;
14015 :
14016 :
14017 0 : result = (double)(0);
14018 0 : x = ae_minreal(2*(s-0.000000e+00)/3.250000e+00-1, 1.0, _state);
14019 0 : tj = (double)(1);
14020 0 : tj1 = x;
14021 0 : mannwhitneyu_ucheb(x, -3.848925e+00, &tj, &tj1, &result, _state);
14022 0 : mannwhitneyu_ucheb(x, -4.040178e+00, &tj, &tj1, &result, _state);
14023 0 : mannwhitneyu_ucheb(x, -1.048355e+00, &tj, &tj1, &result, _state);
14024 0 : mannwhitneyu_ucheb(x, -2.510198e-01, &tj, &tj1, &result, _state);
14025 0 : mannwhitneyu_ucheb(x, -9.261134e-02, &tj, &tj1, &result, _state);
14026 0 : mannwhitneyu_ucheb(x, -3.915864e-02, &tj, &tj1, &result, _state);
14027 0 : mannwhitneyu_ucheb(x, -1.627423e-02, &tj, &tj1, &result, _state);
14028 0 : mannwhitneyu_ucheb(x, -6.307345e-03, &tj, &tj1, &result, _state);
14029 0 : mannwhitneyu_ucheb(x, -2.732992e-03, &tj, &tj1, &result, _state);
14030 0 : mannwhitneyu_ucheb(x, -1.869652e-03, &tj, &tj1, &result, _state);
14031 0 : mannwhitneyu_ucheb(x, -1.494176e-03, &tj, &tj1, &result, _state);
14032 0 : mannwhitneyu_ucheb(x, -1.047533e-03, &tj, &tj1, &result, _state);
14033 0 : mannwhitneyu_ucheb(x, -7.178439e-04, &tj, &tj1, &result, _state);
14034 0 : mannwhitneyu_ucheb(x, -5.424171e-04, &tj, &tj1, &result, _state);
14035 0 : mannwhitneyu_ucheb(x, -3.829195e-04, &tj, &tj1, &result, _state);
14036 0 : mannwhitneyu_ucheb(x, -2.840810e-04, &tj, &tj1, &result, _state);
14037 0 : return result;
14038 : }
14039 :
14040 :
14041 : /*************************************************************************
14042 : Tail(S, 5, 25)
14043 : *************************************************************************/
14044 0 : static double mannwhitneyu_utbln5n25(double s, ae_state *_state)
14045 : {
14046 : double x;
14047 : double tj;
14048 : double tj1;
14049 : double result;
14050 :
14051 :
14052 0 : result = (double)(0);
14053 0 : x = ae_minreal(2*(s-0.000000e+00)/3.250000e+00-1, 1.0, _state);
14054 0 : tj = (double)(1);
14055 0 : tj1 = x;
14056 0 : mannwhitneyu_ucheb(x, -3.848937e+00, &tj, &tj1, &result, _state);
14057 0 : mannwhitneyu_ucheb(x, -4.037512e+00, &tj, &tj1, &result, _state);
14058 0 : mannwhitneyu_ucheb(x, -1.044866e+00, &tj, &tj1, &result, _state);
14059 0 : mannwhitneyu_ucheb(x, -2.483269e-01, &tj, &tj1, &result, _state);
14060 0 : mannwhitneyu_ucheb(x, -9.063682e-02, &tj, &tj1, &result, _state);
14061 0 : mannwhitneyu_ucheb(x, -3.767778e-02, &tj, &tj1, &result, _state);
14062 0 : mannwhitneyu_ucheb(x, -1.508540e-02, &tj, &tj1, &result, _state);
14063 0 : mannwhitneyu_ucheb(x, -5.332756e-03, &tj, &tj1, &result, _state);
14064 0 : mannwhitneyu_ucheb(x, -1.881511e-03, &tj, &tj1, &result, _state);
14065 0 : mannwhitneyu_ucheb(x, -1.124041e-03, &tj, &tj1, &result, _state);
14066 0 : mannwhitneyu_ucheb(x, -8.368456e-04, &tj, &tj1, &result, _state);
14067 0 : mannwhitneyu_ucheb(x, -4.930499e-04, &tj, &tj1, &result, _state);
14068 0 : mannwhitneyu_ucheb(x, -2.779630e-04, &tj, &tj1, &result, _state);
14069 0 : mannwhitneyu_ucheb(x, -2.029528e-04, &tj, &tj1, &result, _state);
14070 0 : mannwhitneyu_ucheb(x, -1.658678e-04, &tj, &tj1, &result, _state);
14071 0 : mannwhitneyu_ucheb(x, -1.289695e-04, &tj, &tj1, &result, _state);
14072 0 : return result;
14073 : }
14074 :
14075 :
14076 : /*************************************************************************
14077 : Tail(S, 5, 26)
14078 : *************************************************************************/
14079 0 : static double mannwhitneyu_utbln5n26(double s, ae_state *_state)
14080 : {
14081 : double x;
14082 : double tj;
14083 : double tj1;
14084 : double result;
14085 :
14086 :
14087 0 : result = (double)(0);
14088 0 : x = ae_minreal(2*(s-0.000000e+00)/3.250000e+00-1, 1.0, _state);
14089 0 : tj = (double)(1);
14090 0 : tj1 = x;
14091 0 : mannwhitneyu_ucheb(x, -3.849416e+00, &tj, &tj1, &result, _state);
14092 0 : mannwhitneyu_ucheb(x, -4.035915e+00, &tj, &tj1, &result, _state);
14093 0 : mannwhitneyu_ucheb(x, -1.042493e+00, &tj, &tj1, &result, _state);
14094 0 : mannwhitneyu_ucheb(x, -2.466021e-01, &tj, &tj1, &result, _state);
14095 0 : mannwhitneyu_ucheb(x, -8.956432e-02, &tj, &tj1, &result, _state);
14096 0 : mannwhitneyu_ucheb(x, -3.698914e-02, &tj, &tj1, &result, _state);
14097 0 : mannwhitneyu_ucheb(x, -1.465689e-02, &tj, &tj1, &result, _state);
14098 0 : mannwhitneyu_ucheb(x, -5.035254e-03, &tj, &tj1, &result, _state);
14099 0 : mannwhitneyu_ucheb(x, -1.674614e-03, &tj, &tj1, &result, _state);
14100 0 : mannwhitneyu_ucheb(x, -9.492734e-04, &tj, &tj1, &result, _state);
14101 0 : mannwhitneyu_ucheb(x, -7.014021e-04, &tj, &tj1, &result, _state);
14102 0 : mannwhitneyu_ucheb(x, -3.944953e-04, &tj, &tj1, &result, _state);
14103 0 : mannwhitneyu_ucheb(x, -2.255750e-04, &tj, &tj1, &result, _state);
14104 0 : mannwhitneyu_ucheb(x, -2.075841e-04, &tj, &tj1, &result, _state);
14105 0 : mannwhitneyu_ucheb(x, -1.989330e-04, &tj, &tj1, &result, _state);
14106 0 : mannwhitneyu_ucheb(x, -2.134862e-04, &tj, &tj1, &result, _state);
14107 0 : return result;
14108 : }
14109 :
14110 :
14111 : /*************************************************************************
14112 : Tail(S, 5, 27)
14113 : *************************************************************************/
14114 0 : static double mannwhitneyu_utbln5n27(double s, ae_state *_state)
14115 : {
14116 : double x;
14117 : double tj;
14118 : double tj1;
14119 : double result;
14120 :
14121 :
14122 0 : result = (double)(0);
14123 0 : x = ae_minreal(2*(s-0.000000e+00)/3.250000e+00-1, 1.0, _state);
14124 0 : tj = (double)(1);
14125 0 : tj1 = x;
14126 0 : mannwhitneyu_ucheb(x, -3.850070e+00, &tj, &tj1, &result, _state);
14127 0 : mannwhitneyu_ucheb(x, -4.034815e+00, &tj, &tj1, &result, _state);
14128 0 : mannwhitneyu_ucheb(x, -1.040650e+00, &tj, &tj1, &result, _state);
14129 0 : mannwhitneyu_ucheb(x, -2.453117e-01, &tj, &tj1, &result, _state);
14130 0 : mannwhitneyu_ucheb(x, -8.886426e-02, &tj, &tj1, &result, _state);
14131 0 : mannwhitneyu_ucheb(x, -3.661702e-02, &tj, &tj1, &result, _state);
14132 0 : mannwhitneyu_ucheb(x, -1.452346e-02, &tj, &tj1, &result, _state);
14133 0 : mannwhitneyu_ucheb(x, -5.002476e-03, &tj, &tj1, &result, _state);
14134 0 : mannwhitneyu_ucheb(x, -1.720126e-03, &tj, &tj1, &result, _state);
14135 0 : mannwhitneyu_ucheb(x, -1.001400e-03, &tj, &tj1, &result, _state);
14136 0 : mannwhitneyu_ucheb(x, -7.729826e-04, &tj, &tj1, &result, _state);
14137 0 : mannwhitneyu_ucheb(x, -4.740640e-04, &tj, &tj1, &result, _state);
14138 0 : mannwhitneyu_ucheb(x, -3.206333e-04, &tj, &tj1, &result, _state);
14139 0 : mannwhitneyu_ucheb(x, -3.366093e-04, &tj, &tj1, &result, _state);
14140 0 : mannwhitneyu_ucheb(x, -3.193471e-04, &tj, &tj1, &result, _state);
14141 0 : mannwhitneyu_ucheb(x, -3.804091e-04, &tj, &tj1, &result, _state);
14142 0 : return result;
14143 : }
14144 :
14145 :
14146 : /*************************************************************************
14147 : Tail(S, 5, 28)
14148 : *************************************************************************/
14149 0 : static double mannwhitneyu_utbln5n28(double s, ae_state *_state)
14150 : {
14151 : double x;
14152 : double tj;
14153 : double tj1;
14154 : double result;
14155 :
14156 :
14157 0 : result = (double)(0);
14158 0 : x = ae_minreal(2*(s-0.000000e+00)/3.250000e+00-1, 1.0, _state);
14159 0 : tj = (double)(1);
14160 0 : tj1 = x;
14161 0 : mannwhitneyu_ucheb(x, -3.850668e+00, &tj, &tj1, &result, _state);
14162 0 : mannwhitneyu_ucheb(x, -4.033786e+00, &tj, &tj1, &result, _state);
14163 0 : mannwhitneyu_ucheb(x, -1.038853e+00, &tj, &tj1, &result, _state);
14164 0 : mannwhitneyu_ucheb(x, -2.440281e-01, &tj, &tj1, &result, _state);
14165 0 : mannwhitneyu_ucheb(x, -8.806020e-02, &tj, &tj1, &result, _state);
14166 0 : mannwhitneyu_ucheb(x, -3.612883e-02, &tj, &tj1, &result, _state);
14167 0 : mannwhitneyu_ucheb(x, -1.420436e-02, &tj, &tj1, &result, _state);
14168 0 : mannwhitneyu_ucheb(x, -4.787982e-03, &tj, &tj1, &result, _state);
14169 0 : mannwhitneyu_ucheb(x, -1.535230e-03, &tj, &tj1, &result, _state);
14170 0 : mannwhitneyu_ucheb(x, -8.263121e-04, &tj, &tj1, &result, _state);
14171 0 : mannwhitneyu_ucheb(x, -5.849609e-04, &tj, &tj1, &result, _state);
14172 0 : mannwhitneyu_ucheb(x, -2.863967e-04, &tj, &tj1, &result, _state);
14173 0 : mannwhitneyu_ucheb(x, -1.391610e-04, &tj, &tj1, &result, _state);
14174 0 : mannwhitneyu_ucheb(x, -1.720294e-04, &tj, &tj1, &result, _state);
14175 0 : mannwhitneyu_ucheb(x, -1.952273e-04, &tj, &tj1, &result, _state);
14176 0 : mannwhitneyu_ucheb(x, -2.901413e-04, &tj, &tj1, &result, _state);
14177 0 : return result;
14178 : }
14179 :
14180 :
14181 : /*************************************************************************
14182 : Tail(S, 5, 29)
14183 : *************************************************************************/
14184 0 : static double mannwhitneyu_utbln5n29(double s, ae_state *_state)
14185 : {
14186 : double x;
14187 : double tj;
14188 : double tj1;
14189 : double result;
14190 :
14191 :
14192 0 : result = (double)(0);
14193 0 : x = ae_minreal(2*(s-0.000000e+00)/3.250000e+00-1, 1.0, _state);
14194 0 : tj = (double)(1);
14195 0 : tj1 = x;
14196 0 : mannwhitneyu_ucheb(x, -3.851217e+00, &tj, &tj1, &result, _state);
14197 0 : mannwhitneyu_ucheb(x, -4.032834e+00, &tj, &tj1, &result, _state);
14198 0 : mannwhitneyu_ucheb(x, -1.037113e+00, &tj, &tj1, &result, _state);
14199 0 : mannwhitneyu_ucheb(x, -2.427762e-01, &tj, &tj1, &result, _state);
14200 0 : mannwhitneyu_ucheb(x, -8.719146e-02, &tj, &tj1, &result, _state);
14201 0 : mannwhitneyu_ucheb(x, -3.557172e-02, &tj, &tj1, &result, _state);
14202 0 : mannwhitneyu_ucheb(x, -1.375498e-02, &tj, &tj1, &result, _state);
14203 0 : mannwhitneyu_ucheb(x, -4.452033e-03, &tj, &tj1, &result, _state);
14204 0 : mannwhitneyu_ucheb(x, -1.187516e-03, &tj, &tj1, &result, _state);
14205 0 : mannwhitneyu_ucheb(x, -4.916936e-04, &tj, &tj1, &result, _state);
14206 0 : mannwhitneyu_ucheb(x, -2.065533e-04, &tj, &tj1, &result, _state);
14207 0 : mannwhitneyu_ucheb(x, 1.067301e-04, &tj, &tj1, &result, _state);
14208 0 : mannwhitneyu_ucheb(x, 2.615824e-04, &tj, &tj1, &result, _state);
14209 0 : mannwhitneyu_ucheb(x, 2.432244e-04, &tj, &tj1, &result, _state);
14210 0 : mannwhitneyu_ucheb(x, 1.417795e-04, &tj, &tj1, &result, _state);
14211 0 : mannwhitneyu_ucheb(x, 4.710038e-05, &tj, &tj1, &result, _state);
14212 0 : return result;
14213 : }
14214 :
14215 :
14216 : /*************************************************************************
14217 : Tail(S, 5, 30)
14218 : *************************************************************************/
14219 0 : static double mannwhitneyu_utbln5n30(double s, ae_state *_state)
14220 : {
14221 : double x;
14222 : double tj;
14223 : double tj1;
14224 : double result;
14225 :
14226 :
14227 0 : result = (double)(0);
14228 0 : x = ae_minreal(2*(s-0.000000e+00)/3.250000e+00-1, 1.0, _state);
14229 0 : tj = (double)(1);
14230 0 : tj1 = x;
14231 0 : mannwhitneyu_ucheb(x, -3.851845e+00, &tj, &tj1, &result, _state);
14232 0 : mannwhitneyu_ucheb(x, -4.032148e+00, &tj, &tj1, &result, _state);
14233 0 : mannwhitneyu_ucheb(x, -1.035679e+00, &tj, &tj1, &result, _state);
14234 0 : mannwhitneyu_ucheb(x, -2.417758e-01, &tj, &tj1, &result, _state);
14235 0 : mannwhitneyu_ucheb(x, -8.655330e-02, &tj, &tj1, &result, _state);
14236 0 : mannwhitneyu_ucheb(x, -3.522132e-02, &tj, &tj1, &result, _state);
14237 0 : mannwhitneyu_ucheb(x, -1.352106e-02, &tj, &tj1, &result, _state);
14238 0 : mannwhitneyu_ucheb(x, -4.326911e-03, &tj, &tj1, &result, _state);
14239 0 : mannwhitneyu_ucheb(x, -1.064969e-03, &tj, &tj1, &result, _state);
14240 0 : mannwhitneyu_ucheb(x, -3.813321e-04, &tj, &tj1, &result, _state);
14241 0 : mannwhitneyu_ucheb(x, -5.683881e-05, &tj, &tj1, &result, _state);
14242 0 : mannwhitneyu_ucheb(x, 2.813346e-04, &tj, &tj1, &result, _state);
14243 0 : mannwhitneyu_ucheb(x, 4.627085e-04, &tj, &tj1, &result, _state);
14244 0 : mannwhitneyu_ucheb(x, 4.832107e-04, &tj, &tj1, &result, _state);
14245 0 : mannwhitneyu_ucheb(x, 3.519336e-04, &tj, &tj1, &result, _state);
14246 0 : mannwhitneyu_ucheb(x, 2.888530e-04, &tj, &tj1, &result, _state);
14247 0 : return result;
14248 : }
14249 :
14250 :
14251 : /*************************************************************************
14252 : Tail(S, 5, 100)
14253 : *************************************************************************/
14254 0 : static double mannwhitneyu_utbln5n100(double s, ae_state *_state)
14255 : {
14256 : double x;
14257 : double tj;
14258 : double tj1;
14259 : double result;
14260 :
14261 :
14262 0 : result = (double)(0);
14263 0 : x = ae_minreal(2*(s-0.000000e+00)/3.250000e+00-1, 1.0, _state);
14264 0 : tj = (double)(1);
14265 0 : tj1 = x;
14266 0 : mannwhitneyu_ucheb(x, -3.877940e+00, &tj, &tj1, &result, _state);
14267 0 : mannwhitneyu_ucheb(x, -4.039324e+00, &tj, &tj1, &result, _state);
14268 0 : mannwhitneyu_ucheb(x, -1.022243e+00, &tj, &tj1, &result, _state);
14269 0 : mannwhitneyu_ucheb(x, -2.305825e-01, &tj, &tj1, &result, _state);
14270 0 : mannwhitneyu_ucheb(x, -7.960119e-02, &tj, &tj1, &result, _state);
14271 0 : mannwhitneyu_ucheb(x, -3.112000e-02, &tj, &tj1, &result, _state);
14272 0 : mannwhitneyu_ucheb(x, -1.138868e-02, &tj, &tj1, &result, _state);
14273 0 : mannwhitneyu_ucheb(x, -3.418164e-03, &tj, &tj1, &result, _state);
14274 0 : mannwhitneyu_ucheb(x, -9.174520e-04, &tj, &tj1, &result, _state);
14275 0 : mannwhitneyu_ucheb(x, -5.489617e-04, &tj, &tj1, &result, _state);
14276 0 : mannwhitneyu_ucheb(x, -3.878301e-04, &tj, &tj1, &result, _state);
14277 0 : mannwhitneyu_ucheb(x, -1.302233e-04, &tj, &tj1, &result, _state);
14278 0 : mannwhitneyu_ucheb(x, 1.054113e-05, &tj, &tj1, &result, _state);
14279 0 : mannwhitneyu_ucheb(x, 2.458862e-05, &tj, &tj1, &result, _state);
14280 0 : mannwhitneyu_ucheb(x, -4.186591e-06, &tj, &tj1, &result, _state);
14281 0 : mannwhitneyu_ucheb(x, -2.623412e-05, &tj, &tj1, &result, _state);
14282 0 : return result;
14283 : }
14284 :
14285 :
14286 : /*************************************************************************
14287 : Tail(S, 6, 6)
14288 : *************************************************************************/
14289 0 : static double mannwhitneyu_utbln6n6(double s, ae_state *_state)
14290 : {
14291 : double x;
14292 : double tj;
14293 : double tj1;
14294 : double result;
14295 :
14296 :
14297 0 : result = (double)(0);
14298 0 : x = ae_minreal(2*(s-0.000000e+00)/2.882307e+00-1, 1.0, _state);
14299 0 : tj = (double)(1);
14300 0 : tj1 = x;
14301 0 : mannwhitneyu_ucheb(x, -3.054075e+00, &tj, &tj1, &result, _state);
14302 0 : mannwhitneyu_ucheb(x, -2.998804e+00, &tj, &tj1, &result, _state);
14303 0 : mannwhitneyu_ucheb(x, -6.681518e-01, &tj, &tj1, &result, _state);
14304 0 : mannwhitneyu_ucheb(x, -1.067578e-01, &tj, &tj1, &result, _state);
14305 0 : mannwhitneyu_ucheb(x, -1.709435e-02, &tj, &tj1, &result, _state);
14306 0 : mannwhitneyu_ucheb(x, 9.952661e-04, &tj, &tj1, &result, _state);
14307 0 : mannwhitneyu_ucheb(x, 3.641700e-03, &tj, &tj1, &result, _state);
14308 0 : mannwhitneyu_ucheb(x, 2.304572e-03, &tj, &tj1, &result, _state);
14309 0 : mannwhitneyu_ucheb(x, 3.336275e-03, &tj, &tj1, &result, _state);
14310 0 : mannwhitneyu_ucheb(x, 4.770385e-03, &tj, &tj1, &result, _state);
14311 0 : mannwhitneyu_ucheb(x, 5.401891e-03, &tj, &tj1, &result, _state);
14312 0 : mannwhitneyu_ucheb(x, 2.246148e-03, &tj, &tj1, &result, _state);
14313 0 : mannwhitneyu_ucheb(x, -1.442663e-03, &tj, &tj1, &result, _state);
14314 0 : mannwhitneyu_ucheb(x, -2.502866e-03, &tj, &tj1, &result, _state);
14315 0 : mannwhitneyu_ucheb(x, -2.105855e-03, &tj, &tj1, &result, _state);
14316 0 : mannwhitneyu_ucheb(x, -4.739371e-04, &tj, &tj1, &result, _state);
14317 0 : return result;
14318 : }
14319 :
14320 :
14321 : /*************************************************************************
14322 : Tail(S, 6, 7)
14323 : *************************************************************************/
14324 0 : static double mannwhitneyu_utbln6n7(double s, ae_state *_state)
14325 : {
14326 : double x;
14327 : double tj;
14328 : double tj1;
14329 : double result;
14330 :
14331 :
14332 0 : result = (double)(0);
14333 0 : x = ae_minreal(2*(s-0.000000e+00)/3.000000e+00-1, 1.0, _state);
14334 0 : tj = (double)(1);
14335 0 : tj1 = x;
14336 0 : mannwhitneyu_ucheb(x, -3.265287e+00, &tj, &tj1, &result, _state);
14337 0 : mannwhitneyu_ucheb(x, -3.274613e+00, &tj, &tj1, &result, _state);
14338 0 : mannwhitneyu_ucheb(x, -7.582352e-01, &tj, &tj1, &result, _state);
14339 0 : mannwhitneyu_ucheb(x, -1.334293e-01, &tj, &tj1, &result, _state);
14340 0 : mannwhitneyu_ucheb(x, -2.915502e-02, &tj, &tj1, &result, _state);
14341 0 : mannwhitneyu_ucheb(x, -4.108091e-03, &tj, &tj1, &result, _state);
14342 0 : mannwhitneyu_ucheb(x, 1.546701e-03, &tj, &tj1, &result, _state);
14343 0 : mannwhitneyu_ucheb(x, 2.298827e-03, &tj, &tj1, &result, _state);
14344 0 : mannwhitneyu_ucheb(x, 2.891501e-03, &tj, &tj1, &result, _state);
14345 0 : mannwhitneyu_ucheb(x, 4.313717e-03, &tj, &tj1, &result, _state);
14346 0 : mannwhitneyu_ucheb(x, 4.989501e-03, &tj, &tj1, &result, _state);
14347 0 : mannwhitneyu_ucheb(x, 3.914594e-03, &tj, &tj1, &result, _state);
14348 0 : mannwhitneyu_ucheb(x, 1.062372e-03, &tj, &tj1, &result, _state);
14349 0 : mannwhitneyu_ucheb(x, -1.158841e-03, &tj, &tj1, &result, _state);
14350 0 : mannwhitneyu_ucheb(x, -1.596443e-03, &tj, &tj1, &result, _state);
14351 0 : mannwhitneyu_ucheb(x, -1.185662e-03, &tj, &tj1, &result, _state);
14352 0 : return result;
14353 : }
14354 :
14355 :
14356 : /*************************************************************************
14357 : Tail(S, 6, 8)
14358 : *************************************************************************/
14359 0 : static double mannwhitneyu_utbln6n8(double s, ae_state *_state)
14360 : {
14361 : double x;
14362 : double tj;
14363 : double tj1;
14364 : double result;
14365 :
14366 :
14367 0 : result = (double)(0);
14368 0 : x = ae_minreal(2*(s-0.000000e+00)/3.098387e+00-1, 1.0, _state);
14369 0 : tj = (double)(1);
14370 0 : tj1 = x;
14371 0 : mannwhitneyu_ucheb(x, -3.450954e+00, &tj, &tj1, &result, _state);
14372 0 : mannwhitneyu_ucheb(x, -3.520462e+00, &tj, &tj1, &result, _state);
14373 0 : mannwhitneyu_ucheb(x, -8.420299e-01, &tj, &tj1, &result, _state);
14374 0 : mannwhitneyu_ucheb(x, -1.604853e-01, &tj, &tj1, &result, _state);
14375 0 : mannwhitneyu_ucheb(x, -4.165840e-02, &tj, &tj1, &result, _state);
14376 0 : mannwhitneyu_ucheb(x, -1.008756e-02, &tj, &tj1, &result, _state);
14377 0 : mannwhitneyu_ucheb(x, -6.723402e-04, &tj, &tj1, &result, _state);
14378 0 : mannwhitneyu_ucheb(x, 1.843521e-03, &tj, &tj1, &result, _state);
14379 0 : mannwhitneyu_ucheb(x, 2.883405e-03, &tj, &tj1, &result, _state);
14380 0 : mannwhitneyu_ucheb(x, 3.720980e-03, &tj, &tj1, &result, _state);
14381 0 : mannwhitneyu_ucheb(x, 4.301709e-03, &tj, &tj1, &result, _state);
14382 0 : mannwhitneyu_ucheb(x, 3.948034e-03, &tj, &tj1, &result, _state);
14383 0 : mannwhitneyu_ucheb(x, 2.776243e-03, &tj, &tj1, &result, _state);
14384 0 : mannwhitneyu_ucheb(x, 8.623736e-04, &tj, &tj1, &result, _state);
14385 0 : mannwhitneyu_ucheb(x, -3.742068e-04, &tj, &tj1, &result, _state);
14386 0 : mannwhitneyu_ucheb(x, -9.796927e-04, &tj, &tj1, &result, _state);
14387 0 : return result;
14388 : }
14389 :
14390 :
14391 : /*************************************************************************
14392 : Tail(S, 6, 9)
14393 : *************************************************************************/
14394 0 : static double mannwhitneyu_utbln6n9(double s, ae_state *_state)
14395 : {
14396 : double x;
14397 : double tj;
14398 : double tj1;
14399 : double result;
14400 :
14401 :
14402 0 : result = (double)(0);
14403 0 : x = ae_minreal(2*(s-0.000000e+00)/3.181981e+00-1, 1.0, _state);
14404 0 : tj = (double)(1);
14405 0 : tj1 = x;
14406 0 : mannwhitneyu_ucheb(x, -3.616113e+00, &tj, &tj1, &result, _state);
14407 0 : mannwhitneyu_ucheb(x, -3.741650e+00, &tj, &tj1, &result, _state);
14408 0 : mannwhitneyu_ucheb(x, -9.204487e-01, &tj, &tj1, &result, _state);
14409 0 : mannwhitneyu_ucheb(x, -1.873068e-01, &tj, &tj1, &result, _state);
14410 0 : mannwhitneyu_ucheb(x, -5.446794e-02, &tj, &tj1, &result, _state);
14411 0 : mannwhitneyu_ucheb(x, -1.632286e-02, &tj, &tj1, &result, _state);
14412 0 : mannwhitneyu_ucheb(x, -3.266481e-03, &tj, &tj1, &result, _state);
14413 0 : mannwhitneyu_ucheb(x, 1.280067e-03, &tj, &tj1, &result, _state);
14414 0 : mannwhitneyu_ucheb(x, 2.780687e-03, &tj, &tj1, &result, _state);
14415 0 : mannwhitneyu_ucheb(x, 3.480242e-03, &tj, &tj1, &result, _state);
14416 0 : mannwhitneyu_ucheb(x, 3.592200e-03, &tj, &tj1, &result, _state);
14417 0 : mannwhitneyu_ucheb(x, 3.581019e-03, &tj, &tj1, &result, _state);
14418 0 : mannwhitneyu_ucheb(x, 3.264231e-03, &tj, &tj1, &result, _state);
14419 0 : mannwhitneyu_ucheb(x, 2.347174e-03, &tj, &tj1, &result, _state);
14420 0 : mannwhitneyu_ucheb(x, 1.167535e-03, &tj, &tj1, &result, _state);
14421 0 : mannwhitneyu_ucheb(x, -1.092185e-04, &tj, &tj1, &result, _state);
14422 0 : return result;
14423 : }
14424 :
14425 :
14426 : /*************************************************************************
14427 : Tail(S, 6, 10)
14428 : *************************************************************************/
14429 0 : static double mannwhitneyu_utbln6n10(double s, ae_state *_state)
14430 : {
14431 : double x;
14432 : double tj;
14433 : double tj1;
14434 : double result;
14435 :
14436 :
14437 0 : result = (double)(0);
14438 0 : x = ae_minreal(2*(s-0.000000e+00)/3.253957e+00-1, 1.0, _state);
14439 0 : tj = (double)(1);
14440 0 : tj1 = x;
14441 0 : mannwhitneyu_ucheb(x, -3.764382e+00, &tj, &tj1, &result, _state);
14442 0 : mannwhitneyu_ucheb(x, -3.942366e+00, &tj, &tj1, &result, _state);
14443 0 : mannwhitneyu_ucheb(x, -9.939896e-01, &tj, &tj1, &result, _state);
14444 0 : mannwhitneyu_ucheb(x, -2.137812e-01, &tj, &tj1, &result, _state);
14445 0 : mannwhitneyu_ucheb(x, -6.720270e-02, &tj, &tj1, &result, _state);
14446 0 : mannwhitneyu_ucheb(x, -2.281070e-02, &tj, &tj1, &result, _state);
14447 0 : mannwhitneyu_ucheb(x, -5.901060e-03, &tj, &tj1, &result, _state);
14448 0 : mannwhitneyu_ucheb(x, 3.824937e-04, &tj, &tj1, &result, _state);
14449 0 : mannwhitneyu_ucheb(x, 2.802812e-03, &tj, &tj1, &result, _state);
14450 0 : mannwhitneyu_ucheb(x, 3.258132e-03, &tj, &tj1, &result, _state);
14451 0 : mannwhitneyu_ucheb(x, 3.233536e-03, &tj, &tj1, &result, _state);
14452 0 : mannwhitneyu_ucheb(x, 3.085530e-03, &tj, &tj1, &result, _state);
14453 0 : mannwhitneyu_ucheb(x, 3.212151e-03, &tj, &tj1, &result, _state);
14454 0 : mannwhitneyu_ucheb(x, 3.001329e-03, &tj, &tj1, &result, _state);
14455 0 : mannwhitneyu_ucheb(x, 2.226048e-03, &tj, &tj1, &result, _state);
14456 0 : mannwhitneyu_ucheb(x, 1.035298e-03, &tj, &tj1, &result, _state);
14457 0 : return result;
14458 : }
14459 :
14460 :
14461 : /*************************************************************************
14462 : Tail(S, 6, 11)
14463 : *************************************************************************/
14464 0 : static double mannwhitneyu_utbln6n11(double s, ae_state *_state)
14465 : {
14466 : double x;
14467 : double tj;
14468 : double tj1;
14469 : double result;
14470 :
14471 :
14472 0 : result = (double)(0);
14473 0 : x = ae_minreal(2*(s-0.000000e+00)/3.316625e+00-1, 1.0, _state);
14474 0 : tj = (double)(1);
14475 0 : tj1 = x;
14476 0 : mannwhitneyu_ucheb(x, -3.898597e+00, &tj, &tj1, &result, _state);
14477 0 : mannwhitneyu_ucheb(x, -4.125710e+00, &tj, &tj1, &result, _state);
14478 0 : mannwhitneyu_ucheb(x, -1.063297e+00, &tj, &tj1, &result, _state);
14479 0 : mannwhitneyu_ucheb(x, -2.396852e-01, &tj, &tj1, &result, _state);
14480 0 : mannwhitneyu_ucheb(x, -7.990126e-02, &tj, &tj1, &result, _state);
14481 0 : mannwhitneyu_ucheb(x, -2.927977e-02, &tj, &tj1, &result, _state);
14482 0 : mannwhitneyu_ucheb(x, -8.726500e-03, &tj, &tj1, &result, _state);
14483 0 : mannwhitneyu_ucheb(x, -5.858745e-04, &tj, &tj1, &result, _state);
14484 0 : mannwhitneyu_ucheb(x, 2.654590e-03, &tj, &tj1, &result, _state);
14485 0 : mannwhitneyu_ucheb(x, 3.217736e-03, &tj, &tj1, &result, _state);
14486 0 : mannwhitneyu_ucheb(x, 2.989770e-03, &tj, &tj1, &result, _state);
14487 0 : mannwhitneyu_ucheb(x, 2.768493e-03, &tj, &tj1, &result, _state);
14488 0 : mannwhitneyu_ucheb(x, 2.924364e-03, &tj, &tj1, &result, _state);
14489 0 : mannwhitneyu_ucheb(x, 3.140215e-03, &tj, &tj1, &result, _state);
14490 0 : mannwhitneyu_ucheb(x, 2.647914e-03, &tj, &tj1, &result, _state);
14491 0 : mannwhitneyu_ucheb(x, 1.924802e-03, &tj, &tj1, &result, _state);
14492 0 : return result;
14493 : }
14494 :
14495 :
14496 : /*************************************************************************
14497 : Tail(S, 6, 12)
14498 : *************************************************************************/
14499 0 : static double mannwhitneyu_utbln6n12(double s, ae_state *_state)
14500 : {
14501 : double x;
14502 : double tj;
14503 : double tj1;
14504 : double result;
14505 :
14506 :
14507 0 : result = (double)(0);
14508 0 : x = ae_minreal(2*(s-0.000000e+00)/3.371709e+00-1, 1.0, _state);
14509 0 : tj = (double)(1);
14510 0 : tj1 = x;
14511 0 : mannwhitneyu_ucheb(x, -4.020941e+00, &tj, &tj1, &result, _state);
14512 0 : mannwhitneyu_ucheb(x, -4.294250e+00, &tj, &tj1, &result, _state);
14513 0 : mannwhitneyu_ucheb(x, -1.128842e+00, &tj, &tj1, &result, _state);
14514 0 : mannwhitneyu_ucheb(x, -2.650389e-01, &tj, &tj1, &result, _state);
14515 0 : mannwhitneyu_ucheb(x, -9.248611e-02, &tj, &tj1, &result, _state);
14516 0 : mannwhitneyu_ucheb(x, -3.578510e-02, &tj, &tj1, &result, _state);
14517 0 : mannwhitneyu_ucheb(x, -1.162852e-02, &tj, &tj1, &result, _state);
14518 0 : mannwhitneyu_ucheb(x, -1.746982e-03, &tj, &tj1, &result, _state);
14519 0 : mannwhitneyu_ucheb(x, 2.454209e-03, &tj, &tj1, &result, _state);
14520 0 : mannwhitneyu_ucheb(x, 3.128042e-03, &tj, &tj1, &result, _state);
14521 0 : mannwhitneyu_ucheb(x, 2.936650e-03, &tj, &tj1, &result, _state);
14522 0 : mannwhitneyu_ucheb(x, 2.530794e-03, &tj, &tj1, &result, _state);
14523 0 : mannwhitneyu_ucheb(x, 2.665192e-03, &tj, &tj1, &result, _state);
14524 0 : mannwhitneyu_ucheb(x, 2.994144e-03, &tj, &tj1, &result, _state);
14525 0 : mannwhitneyu_ucheb(x, 2.662249e-03, &tj, &tj1, &result, _state);
14526 0 : mannwhitneyu_ucheb(x, 2.368541e-03, &tj, &tj1, &result, _state);
14527 0 : return result;
14528 : }
14529 :
14530 :
14531 : /*************************************************************************
14532 : Tail(S, 6, 13)
14533 : *************************************************************************/
14534 0 : static double mannwhitneyu_utbln6n13(double s, ae_state *_state)
14535 : {
14536 : double x;
14537 : double tj;
14538 : double tj1;
14539 : double result;
14540 :
14541 :
14542 0 : result = (double)(0);
14543 0 : x = ae_minreal(2*(s-0.000000e+00)/3.420526e+00-1, 1.0, _state);
14544 0 : tj = (double)(1);
14545 0 : tj1 = x;
14546 0 : mannwhitneyu_ucheb(x, -4.133167e+00, &tj, &tj1, &result, _state);
14547 0 : mannwhitneyu_ucheb(x, -4.450016e+00, &tj, &tj1, &result, _state);
14548 0 : mannwhitneyu_ucheb(x, -1.191088e+00, &tj, &tj1, &result, _state);
14549 0 : mannwhitneyu_ucheb(x, -2.898220e-01, &tj, &tj1, &result, _state);
14550 0 : mannwhitneyu_ucheb(x, -1.050249e-01, &tj, &tj1, &result, _state);
14551 0 : mannwhitneyu_ucheb(x, -4.226901e-02, &tj, &tj1, &result, _state);
14552 0 : mannwhitneyu_ucheb(x, -1.471113e-02, &tj, &tj1, &result, _state);
14553 0 : mannwhitneyu_ucheb(x, -3.007470e-03, &tj, &tj1, &result, _state);
14554 0 : mannwhitneyu_ucheb(x, 2.049420e-03, &tj, &tj1, &result, _state);
14555 0 : mannwhitneyu_ucheb(x, 3.059074e-03, &tj, &tj1, &result, _state);
14556 0 : mannwhitneyu_ucheb(x, 2.881249e-03, &tj, &tj1, &result, _state);
14557 0 : mannwhitneyu_ucheb(x, 2.452780e-03, &tj, &tj1, &result, _state);
14558 0 : mannwhitneyu_ucheb(x, 2.441805e-03, &tj, &tj1, &result, _state);
14559 0 : mannwhitneyu_ucheb(x, 2.787493e-03, &tj, &tj1, &result, _state);
14560 0 : mannwhitneyu_ucheb(x, 2.483957e-03, &tj, &tj1, &result, _state);
14561 0 : mannwhitneyu_ucheb(x, 2.481590e-03, &tj, &tj1, &result, _state);
14562 0 : return result;
14563 : }
14564 :
14565 :
14566 : /*************************************************************************
14567 : Tail(S, 6, 14)
14568 : *************************************************************************/
14569 0 : static double mannwhitneyu_utbln6n14(double s, ae_state *_state)
14570 : {
14571 : double x;
14572 : double tj;
14573 : double tj1;
14574 : double result;
14575 :
14576 :
14577 0 : result = (double)(0);
14578 0 : x = ae_minreal(2*(s-0.000000e+00)/3.450000e+00-1, 1.0, _state);
14579 0 : tj = (double)(1);
14580 0 : tj1 = x;
14581 0 : mannwhitneyu_ucheb(x, -4.201268e+00, &tj, &tj1, &result, _state);
14582 0 : mannwhitneyu_ucheb(x, -4.542568e+00, &tj, &tj1, &result, _state);
14583 0 : mannwhitneyu_ucheb(x, -1.226965e+00, &tj, &tj1, &result, _state);
14584 0 : mannwhitneyu_ucheb(x, -3.046029e-01, &tj, &tj1, &result, _state);
14585 0 : mannwhitneyu_ucheb(x, -1.136657e-01, &tj, &tj1, &result, _state);
14586 0 : mannwhitneyu_ucheb(x, -4.786757e-02, &tj, &tj1, &result, _state);
14587 0 : mannwhitneyu_ucheb(x, -1.843748e-02, &tj, &tj1, &result, _state);
14588 0 : mannwhitneyu_ucheb(x, -5.588022e-03, &tj, &tj1, &result, _state);
14589 0 : mannwhitneyu_ucheb(x, 2.253029e-04, &tj, &tj1, &result, _state);
14590 0 : mannwhitneyu_ucheb(x, 1.667188e-03, &tj, &tj1, &result, _state);
14591 0 : mannwhitneyu_ucheb(x, 1.788330e-03, &tj, &tj1, &result, _state);
14592 0 : mannwhitneyu_ucheb(x, 1.474545e-03, &tj, &tj1, &result, _state);
14593 0 : mannwhitneyu_ucheb(x, 1.540494e-03, &tj, &tj1, &result, _state);
14594 0 : mannwhitneyu_ucheb(x, 1.951188e-03, &tj, &tj1, &result, _state);
14595 0 : mannwhitneyu_ucheb(x, 1.863323e-03, &tj, &tj1, &result, _state);
14596 0 : mannwhitneyu_ucheb(x, 2.220904e-03, &tj, &tj1, &result, _state);
14597 0 : return result;
14598 : }
14599 :
14600 :
14601 : /*************************************************************************
14602 : Tail(S, 6, 15)
14603 : *************************************************************************/
14604 0 : static double mannwhitneyu_utbln6n15(double s, ae_state *_state)
14605 : {
14606 : double x;
14607 : double tj;
14608 : double tj1;
14609 : double result;
14610 :
14611 :
14612 0 : result = (double)(0);
14613 0 : x = ae_minreal(2*(s-0.000000e+00)/3.450000e+00-1, 1.0, _state);
14614 0 : tj = (double)(1);
14615 0 : tj1 = x;
14616 0 : mannwhitneyu_ucheb(x, -4.195689e+00, &tj, &tj1, &result, _state);
14617 0 : mannwhitneyu_ucheb(x, -4.526567e+00, &tj, &tj1, &result, _state);
14618 0 : mannwhitneyu_ucheb(x, -1.213617e+00, &tj, &tj1, &result, _state);
14619 0 : mannwhitneyu_ucheb(x, -2.975035e-01, &tj, &tj1, &result, _state);
14620 0 : mannwhitneyu_ucheb(x, -1.118480e-01, &tj, &tj1, &result, _state);
14621 0 : mannwhitneyu_ucheb(x, -4.859142e-02, &tj, &tj1, &result, _state);
14622 0 : mannwhitneyu_ucheb(x, -2.083312e-02, &tj, &tj1, &result, _state);
14623 0 : mannwhitneyu_ucheb(x, -8.298720e-03, &tj, &tj1, &result, _state);
14624 0 : mannwhitneyu_ucheb(x, -2.766708e-03, &tj, &tj1, &result, _state);
14625 0 : mannwhitneyu_ucheb(x, -1.026356e-03, &tj, &tj1, &result, _state);
14626 0 : mannwhitneyu_ucheb(x, -9.093113e-04, &tj, &tj1, &result, _state);
14627 0 : mannwhitneyu_ucheb(x, -1.135168e-03, &tj, &tj1, &result, _state);
14628 0 : mannwhitneyu_ucheb(x, -1.136376e-03, &tj, &tj1, &result, _state);
14629 0 : mannwhitneyu_ucheb(x, -8.190870e-04, &tj, &tj1, &result, _state);
14630 0 : mannwhitneyu_ucheb(x, -4.435972e-04, &tj, &tj1, &result, _state);
14631 0 : mannwhitneyu_ucheb(x, 1.413129e-04, &tj, &tj1, &result, _state);
14632 0 : return result;
14633 : }
14634 :
14635 :
14636 : /*************************************************************************
14637 : Tail(S, 6, 30)
14638 : *************************************************************************/
14639 0 : static double mannwhitneyu_utbln6n30(double s, ae_state *_state)
14640 : {
14641 : double x;
14642 : double tj;
14643 : double tj1;
14644 : double result;
14645 :
14646 :
14647 0 : result = (double)(0);
14648 0 : x = ae_minreal(2*(s-0.000000e+00)/3.450000e+00-1, 1.0, _state);
14649 0 : tj = (double)(1);
14650 0 : tj1 = x;
14651 0 : mannwhitneyu_ucheb(x, -4.166269e+00, &tj, &tj1, &result, _state);
14652 0 : mannwhitneyu_ucheb(x, -4.427399e+00, &tj, &tj1, &result, _state);
14653 0 : mannwhitneyu_ucheb(x, -1.118239e+00, &tj, &tj1, &result, _state);
14654 0 : mannwhitneyu_ucheb(x, -2.360847e-01, &tj, &tj1, &result, _state);
14655 0 : mannwhitneyu_ucheb(x, -7.745885e-02, &tj, &tj1, &result, _state);
14656 0 : mannwhitneyu_ucheb(x, -3.025041e-02, &tj, &tj1, &result, _state);
14657 0 : mannwhitneyu_ucheb(x, -1.187179e-02, &tj, &tj1, &result, _state);
14658 0 : mannwhitneyu_ucheb(x, -4.432089e-03, &tj, &tj1, &result, _state);
14659 0 : mannwhitneyu_ucheb(x, -1.408451e-03, &tj, &tj1, &result, _state);
14660 0 : mannwhitneyu_ucheb(x, -4.388774e-04, &tj, &tj1, &result, _state);
14661 0 : mannwhitneyu_ucheb(x, -2.795560e-04, &tj, &tj1, &result, _state);
14662 0 : mannwhitneyu_ucheb(x, -2.304136e-04, &tj, &tj1, &result, _state);
14663 0 : mannwhitneyu_ucheb(x, -1.258516e-04, &tj, &tj1, &result, _state);
14664 0 : mannwhitneyu_ucheb(x, -4.180236e-05, &tj, &tj1, &result, _state);
14665 0 : mannwhitneyu_ucheb(x, -4.388679e-06, &tj, &tj1, &result, _state);
14666 0 : mannwhitneyu_ucheb(x, 4.836027e-06, &tj, &tj1, &result, _state);
14667 0 : return result;
14668 : }
14669 :
14670 :
14671 : /*************************************************************************
14672 : Tail(S, 6, 100)
14673 : *************************************************************************/
14674 0 : static double mannwhitneyu_utbln6n100(double s, ae_state *_state)
14675 : {
14676 : double x;
14677 : double tj;
14678 : double tj1;
14679 : double result;
14680 :
14681 :
14682 0 : result = (double)(0);
14683 0 : x = ae_minreal(2*(s-0.000000e+00)/3.450000e+00-1, 1.0, _state);
14684 0 : tj = (double)(1);
14685 0 : tj1 = x;
14686 0 : mannwhitneyu_ucheb(x, -4.181350e+00, &tj, &tj1, &result, _state);
14687 0 : mannwhitneyu_ucheb(x, -4.417919e+00, &tj, &tj1, &result, _state);
14688 0 : mannwhitneyu_ucheb(x, -1.094201e+00, &tj, &tj1, &result, _state);
14689 0 : mannwhitneyu_ucheb(x, -2.195883e-01, &tj, &tj1, &result, _state);
14690 0 : mannwhitneyu_ucheb(x, -6.818937e-02, &tj, &tj1, &result, _state);
14691 0 : mannwhitneyu_ucheb(x, -2.514202e-02, &tj, &tj1, &result, _state);
14692 0 : mannwhitneyu_ucheb(x, -9.125047e-03, &tj, &tj1, &result, _state);
14693 0 : mannwhitneyu_ucheb(x, -3.022148e-03, &tj, &tj1, &result, _state);
14694 0 : mannwhitneyu_ucheb(x, -7.284181e-04, &tj, &tj1, &result, _state);
14695 0 : mannwhitneyu_ucheb(x, -1.157766e-04, &tj, &tj1, &result, _state);
14696 0 : mannwhitneyu_ucheb(x, -1.023752e-04, &tj, &tj1, &result, _state);
14697 0 : mannwhitneyu_ucheb(x, -1.127985e-04, &tj, &tj1, &result, _state);
14698 0 : mannwhitneyu_ucheb(x, -5.221690e-05, &tj, &tj1, &result, _state);
14699 0 : mannwhitneyu_ucheb(x, -3.516179e-06, &tj, &tj1, &result, _state);
14700 0 : mannwhitneyu_ucheb(x, 9.501398e-06, &tj, &tj1, &result, _state);
14701 0 : mannwhitneyu_ucheb(x, 9.380220e-06, &tj, &tj1, &result, _state);
14702 0 : return result;
14703 : }
14704 :
14705 :
14706 : /*************************************************************************
14707 : Tail(S, 7, 7)
14708 : *************************************************************************/
14709 0 : static double mannwhitneyu_utbln7n7(double s, ae_state *_state)
14710 : {
14711 : double x;
14712 : double tj;
14713 : double tj1;
14714 : double result;
14715 :
14716 :
14717 0 : result = (double)(0);
14718 0 : x = ae_minreal(2*(s-0.000000e+00)/3.130495e+00-1, 1.0, _state);
14719 0 : tj = (double)(1);
14720 0 : tj1 = x;
14721 0 : mannwhitneyu_ucheb(x, -3.501264e+00, &tj, &tj1, &result, _state);
14722 0 : mannwhitneyu_ucheb(x, -3.584790e+00, &tj, &tj1, &result, _state);
14723 0 : mannwhitneyu_ucheb(x, -8.577311e-01, &tj, &tj1, &result, _state);
14724 0 : mannwhitneyu_ucheb(x, -1.617002e-01, &tj, &tj1, &result, _state);
14725 0 : mannwhitneyu_ucheb(x, -4.145186e-02, &tj, &tj1, &result, _state);
14726 0 : mannwhitneyu_ucheb(x, -1.023462e-02, &tj, &tj1, &result, _state);
14727 0 : mannwhitneyu_ucheb(x, -1.408251e-03, &tj, &tj1, &result, _state);
14728 0 : mannwhitneyu_ucheb(x, 8.626515e-04, &tj, &tj1, &result, _state);
14729 0 : mannwhitneyu_ucheb(x, 2.072492e-03, &tj, &tj1, &result, _state);
14730 0 : mannwhitneyu_ucheb(x, 3.722926e-03, &tj, &tj1, &result, _state);
14731 0 : mannwhitneyu_ucheb(x, 5.095445e-03, &tj, &tj1, &result, _state);
14732 0 : mannwhitneyu_ucheb(x, 4.842602e-03, &tj, &tj1, &result, _state);
14733 0 : mannwhitneyu_ucheb(x, 2.751427e-03, &tj, &tj1, &result, _state);
14734 0 : mannwhitneyu_ucheb(x, 2.008927e-04, &tj, &tj1, &result, _state);
14735 0 : mannwhitneyu_ucheb(x, -9.892431e-04, &tj, &tj1, &result, _state);
14736 0 : mannwhitneyu_ucheb(x, -8.772386e-04, &tj, &tj1, &result, _state);
14737 0 : return result;
14738 : }
14739 :
14740 :
14741 : /*************************************************************************
14742 : Tail(S, 7, 8)
14743 : *************************************************************************/
14744 0 : static double mannwhitneyu_utbln7n8(double s, ae_state *_state)
14745 : {
14746 : double x;
14747 : double tj;
14748 : double tj1;
14749 : double result;
14750 :
14751 :
14752 0 : result = (double)(0);
14753 0 : x = ae_minreal(2*(s-0.000000e+00)/3.240370e+00-1, 1.0, _state);
14754 0 : tj = (double)(1);
14755 0 : tj1 = x;
14756 0 : mannwhitneyu_ucheb(x, -3.709965e+00, &tj, &tj1, &result, _state);
14757 0 : mannwhitneyu_ucheb(x, -3.862154e+00, &tj, &tj1, &result, _state);
14758 0 : mannwhitneyu_ucheb(x, -9.504541e-01, &tj, &tj1, &result, _state);
14759 0 : mannwhitneyu_ucheb(x, -1.900195e-01, &tj, &tj1, &result, _state);
14760 0 : mannwhitneyu_ucheb(x, -5.439995e-02, &tj, &tj1, &result, _state);
14761 0 : mannwhitneyu_ucheb(x, -1.678028e-02, &tj, &tj1, &result, _state);
14762 0 : mannwhitneyu_ucheb(x, -4.485540e-03, &tj, &tj1, &result, _state);
14763 0 : mannwhitneyu_ucheb(x, -4.437047e-04, &tj, &tj1, &result, _state);
14764 0 : mannwhitneyu_ucheb(x, 1.440092e-03, &tj, &tj1, &result, _state);
14765 0 : mannwhitneyu_ucheb(x, 3.114227e-03, &tj, &tj1, &result, _state);
14766 0 : mannwhitneyu_ucheb(x, 4.516569e-03, &tj, &tj1, &result, _state);
14767 0 : mannwhitneyu_ucheb(x, 4.829457e-03, &tj, &tj1, &result, _state);
14768 0 : mannwhitneyu_ucheb(x, 3.787550e-03, &tj, &tj1, &result, _state);
14769 0 : mannwhitneyu_ucheb(x, 1.761866e-03, &tj, &tj1, &result, _state);
14770 0 : mannwhitneyu_ucheb(x, 1.991911e-04, &tj, &tj1, &result, _state);
14771 0 : mannwhitneyu_ucheb(x, -4.533481e-04, &tj, &tj1, &result, _state);
14772 0 : return result;
14773 : }
14774 :
14775 :
14776 : /*************************************************************************
14777 : Tail(S, 7, 9)
14778 : *************************************************************************/
14779 0 : static double mannwhitneyu_utbln7n9(double s, ae_state *_state)
14780 : {
14781 : double x;
14782 : double tj;
14783 : double tj1;
14784 : double result;
14785 :
14786 :
14787 0 : result = (double)(0);
14788 0 : x = ae_minreal(2*(s-0.000000e+00)/3.334314e+00-1, 1.0, _state);
14789 0 : tj = (double)(1);
14790 0 : tj1 = x;
14791 0 : mannwhitneyu_ucheb(x, -3.896550e+00, &tj, &tj1, &result, _state);
14792 0 : mannwhitneyu_ucheb(x, -4.112671e+00, &tj, &tj1, &result, _state);
14793 0 : mannwhitneyu_ucheb(x, -1.037277e+00, &tj, &tj1, &result, _state);
14794 0 : mannwhitneyu_ucheb(x, -2.181695e-01, &tj, &tj1, &result, _state);
14795 0 : mannwhitneyu_ucheb(x, -6.765190e-02, &tj, &tj1, &result, _state);
14796 0 : mannwhitneyu_ucheb(x, -2.360116e-02, &tj, &tj1, &result, _state);
14797 0 : mannwhitneyu_ucheb(x, -7.695960e-03, &tj, &tj1, &result, _state);
14798 0 : mannwhitneyu_ucheb(x, -1.780578e-03, &tj, &tj1, &result, _state);
14799 0 : mannwhitneyu_ucheb(x, 8.963843e-04, &tj, &tj1, &result, _state);
14800 0 : mannwhitneyu_ucheb(x, 2.616148e-03, &tj, &tj1, &result, _state);
14801 0 : mannwhitneyu_ucheb(x, 3.852104e-03, &tj, &tj1, &result, _state);
14802 0 : mannwhitneyu_ucheb(x, 4.390744e-03, &tj, &tj1, &result, _state);
14803 0 : mannwhitneyu_ucheb(x, 4.014041e-03, &tj, &tj1, &result, _state);
14804 0 : mannwhitneyu_ucheb(x, 2.888101e-03, &tj, &tj1, &result, _state);
14805 0 : mannwhitneyu_ucheb(x, 1.467474e-03, &tj, &tj1, &result, _state);
14806 0 : mannwhitneyu_ucheb(x, 4.004611e-04, &tj, &tj1, &result, _state);
14807 0 : return result;
14808 : }
14809 :
14810 :
14811 : /*************************************************************************
14812 : Tail(S, 7, 10)
14813 : *************************************************************************/
14814 0 : static double mannwhitneyu_utbln7n10(double s, ae_state *_state)
14815 : {
14816 : double x;
14817 : double tj;
14818 : double tj1;
14819 : double result;
14820 :
14821 :
14822 0 : result = (double)(0);
14823 0 : x = ae_minreal(2*(s-0.000000e+00)/3.415650e+00-1, 1.0, _state);
14824 0 : tj = (double)(1);
14825 0 : tj1 = x;
14826 0 : mannwhitneyu_ucheb(x, -4.064844e+00, &tj, &tj1, &result, _state);
14827 0 : mannwhitneyu_ucheb(x, -4.340749e+00, &tj, &tj1, &result, _state);
14828 0 : mannwhitneyu_ucheb(x, -1.118888e+00, &tj, &tj1, &result, _state);
14829 0 : mannwhitneyu_ucheb(x, -2.459730e-01, &tj, &tj1, &result, _state);
14830 0 : mannwhitneyu_ucheb(x, -8.097781e-02, &tj, &tj1, &result, _state);
14831 0 : mannwhitneyu_ucheb(x, -3.057688e-02, &tj, &tj1, &result, _state);
14832 0 : mannwhitneyu_ucheb(x, -1.097406e-02, &tj, &tj1, &result, _state);
14833 0 : mannwhitneyu_ucheb(x, -3.209262e-03, &tj, &tj1, &result, _state);
14834 0 : mannwhitneyu_ucheb(x, 4.065641e-04, &tj, &tj1, &result, _state);
14835 0 : mannwhitneyu_ucheb(x, 2.196677e-03, &tj, &tj1, &result, _state);
14836 0 : mannwhitneyu_ucheb(x, 3.313994e-03, &tj, &tj1, &result, _state);
14837 0 : mannwhitneyu_ucheb(x, 3.827157e-03, &tj, &tj1, &result, _state);
14838 0 : mannwhitneyu_ucheb(x, 3.822284e-03, &tj, &tj1, &result, _state);
14839 0 : mannwhitneyu_ucheb(x, 3.389090e-03, &tj, &tj1, &result, _state);
14840 0 : mannwhitneyu_ucheb(x, 2.340850e-03, &tj, &tj1, &result, _state);
14841 0 : mannwhitneyu_ucheb(x, 1.395172e-03, &tj, &tj1, &result, _state);
14842 0 : return result;
14843 : }
14844 :
14845 :
14846 : /*************************************************************************
14847 : Tail(S, 7, 11)
14848 : *************************************************************************/
14849 0 : static double mannwhitneyu_utbln7n11(double s, ae_state *_state)
14850 : {
14851 : double x;
14852 : double tj;
14853 : double tj1;
14854 : double result;
14855 :
14856 :
14857 0 : result = (double)(0);
14858 0 : x = ae_minreal(2*(s-0.000000e+00)/3.486817e+00-1, 1.0, _state);
14859 0 : tj = (double)(1);
14860 0 : tj1 = x;
14861 0 : mannwhitneyu_ucheb(x, -4.217795e+00, &tj, &tj1, &result, _state);
14862 0 : mannwhitneyu_ucheb(x, -4.549783e+00, &tj, &tj1, &result, _state);
14863 0 : mannwhitneyu_ucheb(x, -1.195905e+00, &tj, &tj1, &result, _state);
14864 0 : mannwhitneyu_ucheb(x, -2.733093e-01, &tj, &tj1, &result, _state);
14865 0 : mannwhitneyu_ucheb(x, -9.428447e-02, &tj, &tj1, &result, _state);
14866 0 : mannwhitneyu_ucheb(x, -3.760093e-02, &tj, &tj1, &result, _state);
14867 0 : mannwhitneyu_ucheb(x, -1.431676e-02, &tj, &tj1, &result, _state);
14868 0 : mannwhitneyu_ucheb(x, -4.717152e-03, &tj, &tj1, &result, _state);
14869 0 : mannwhitneyu_ucheb(x, -1.032199e-04, &tj, &tj1, &result, _state);
14870 0 : mannwhitneyu_ucheb(x, 1.832423e-03, &tj, &tj1, &result, _state);
14871 0 : mannwhitneyu_ucheb(x, 2.905979e-03, &tj, &tj1, &result, _state);
14872 0 : mannwhitneyu_ucheb(x, 3.302799e-03, &tj, &tj1, &result, _state);
14873 0 : mannwhitneyu_ucheb(x, 3.464371e-03, &tj, &tj1, &result, _state);
14874 0 : mannwhitneyu_ucheb(x, 3.456211e-03, &tj, &tj1, &result, _state);
14875 0 : mannwhitneyu_ucheb(x, 2.736244e-03, &tj, &tj1, &result, _state);
14876 0 : mannwhitneyu_ucheb(x, 2.140712e-03, &tj, &tj1, &result, _state);
14877 0 : return result;
14878 : }
14879 :
14880 :
14881 : /*************************************************************************
14882 : Tail(S, 7, 12)
14883 : *************************************************************************/
14884 0 : static double mannwhitneyu_utbln7n12(double s, ae_state *_state)
14885 : {
14886 : double x;
14887 : double tj;
14888 : double tj1;
14889 : double result;
14890 :
14891 :
14892 0 : result = (double)(0);
14893 0 : x = ae_minreal(2*(s-0.000000e+00)/3.500000e+00-1, 1.0, _state);
14894 0 : tj = (double)(1);
14895 0 : tj1 = x;
14896 0 : mannwhitneyu_ucheb(x, -4.235822e+00, &tj, &tj1, &result, _state);
14897 0 : mannwhitneyu_ucheb(x, -4.564100e+00, &tj, &tj1, &result, _state);
14898 0 : mannwhitneyu_ucheb(x, -1.190813e+00, &tj, &tj1, &result, _state);
14899 0 : mannwhitneyu_ucheb(x, -2.686546e-01, &tj, &tj1, &result, _state);
14900 0 : mannwhitneyu_ucheb(x, -9.395083e-02, &tj, &tj1, &result, _state);
14901 0 : mannwhitneyu_ucheb(x, -3.967359e-02, &tj, &tj1, &result, _state);
14902 0 : mannwhitneyu_ucheb(x, -1.747096e-02, &tj, &tj1, &result, _state);
14903 0 : mannwhitneyu_ucheb(x, -8.304144e-03, &tj, &tj1, &result, _state);
14904 0 : mannwhitneyu_ucheb(x, -3.903198e-03, &tj, &tj1, &result, _state);
14905 0 : mannwhitneyu_ucheb(x, -2.134906e-03, &tj, &tj1, &result, _state);
14906 0 : mannwhitneyu_ucheb(x, -1.175035e-03, &tj, &tj1, &result, _state);
14907 0 : mannwhitneyu_ucheb(x, -7.266224e-04, &tj, &tj1, &result, _state);
14908 0 : mannwhitneyu_ucheb(x, -1.892931e-04, &tj, &tj1, &result, _state);
14909 0 : mannwhitneyu_ucheb(x, 5.604706e-04, &tj, &tj1, &result, _state);
14910 0 : mannwhitneyu_ucheb(x, 9.070459e-04, &tj, &tj1, &result, _state);
14911 0 : mannwhitneyu_ucheb(x, 1.427010e-03, &tj, &tj1, &result, _state);
14912 0 : return result;
14913 : }
14914 :
14915 :
14916 : /*************************************************************************
14917 : Tail(S, 7, 13)
14918 : *************************************************************************/
14919 0 : static double mannwhitneyu_utbln7n13(double s, ae_state *_state)
14920 : {
14921 : double x;
14922 : double tj;
14923 : double tj1;
14924 : double result;
14925 :
14926 :
14927 0 : result = (double)(0);
14928 0 : x = ae_minreal(2*(s-0.000000e+00)/3.500000e+00-1, 1.0, _state);
14929 0 : tj = (double)(1);
14930 0 : tj1 = x;
14931 0 : mannwhitneyu_ucheb(x, -4.222204e+00, &tj, &tj1, &result, _state);
14932 0 : mannwhitneyu_ucheb(x, -4.532300e+00, &tj, &tj1, &result, _state);
14933 0 : mannwhitneyu_ucheb(x, -1.164642e+00, &tj, &tj1, &result, _state);
14934 0 : mannwhitneyu_ucheb(x, -2.523768e-01, &tj, &tj1, &result, _state);
14935 0 : mannwhitneyu_ucheb(x, -8.531984e-02, &tj, &tj1, &result, _state);
14936 0 : mannwhitneyu_ucheb(x, -3.467857e-02, &tj, &tj1, &result, _state);
14937 0 : mannwhitneyu_ucheb(x, -1.483804e-02, &tj, &tj1, &result, _state);
14938 0 : mannwhitneyu_ucheb(x, -6.524136e-03, &tj, &tj1, &result, _state);
14939 0 : mannwhitneyu_ucheb(x, -3.077740e-03, &tj, &tj1, &result, _state);
14940 0 : mannwhitneyu_ucheb(x, -1.745218e-03, &tj, &tj1, &result, _state);
14941 0 : mannwhitneyu_ucheb(x, -1.602085e-03, &tj, &tj1, &result, _state);
14942 0 : mannwhitneyu_ucheb(x, -1.828831e-03, &tj, &tj1, &result, _state);
14943 0 : mannwhitneyu_ucheb(x, -1.994070e-03, &tj, &tj1, &result, _state);
14944 0 : mannwhitneyu_ucheb(x, -1.873879e-03, &tj, &tj1, &result, _state);
14945 0 : mannwhitneyu_ucheb(x, -1.341937e-03, &tj, &tj1, &result, _state);
14946 0 : mannwhitneyu_ucheb(x, -8.706444e-04, &tj, &tj1, &result, _state);
14947 0 : return result;
14948 : }
14949 :
14950 :
14951 : /*************************************************************************
14952 : Tail(S, 7, 14)
14953 : *************************************************************************/
14954 0 : static double mannwhitneyu_utbln7n14(double s, ae_state *_state)
14955 : {
14956 : double x;
14957 : double tj;
14958 : double tj1;
14959 : double result;
14960 :
14961 :
14962 0 : result = (double)(0);
14963 0 : x = ae_minreal(2*(s-0.000000e+00)/3.500000e+00-1, 1.0, _state);
14964 0 : tj = (double)(1);
14965 0 : tj1 = x;
14966 0 : mannwhitneyu_ucheb(x, -4.211763e+00, &tj, &tj1, &result, _state);
14967 0 : mannwhitneyu_ucheb(x, -4.507542e+00, &tj, &tj1, &result, _state);
14968 0 : mannwhitneyu_ucheb(x, -1.143640e+00, &tj, &tj1, &result, _state);
14969 0 : mannwhitneyu_ucheb(x, -2.395755e-01, &tj, &tj1, &result, _state);
14970 0 : mannwhitneyu_ucheb(x, -7.808020e-02, &tj, &tj1, &result, _state);
14971 0 : mannwhitneyu_ucheb(x, -3.044259e-02, &tj, &tj1, &result, _state);
14972 0 : mannwhitneyu_ucheb(x, -1.182308e-02, &tj, &tj1, &result, _state);
14973 0 : mannwhitneyu_ucheb(x, -4.057325e-03, &tj, &tj1, &result, _state);
14974 0 : mannwhitneyu_ucheb(x, -5.724255e-04, &tj, &tj1, &result, _state);
14975 0 : mannwhitneyu_ucheb(x, 8.303900e-04, &tj, &tj1, &result, _state);
14976 0 : mannwhitneyu_ucheb(x, 1.113148e-03, &tj, &tj1, &result, _state);
14977 0 : mannwhitneyu_ucheb(x, 8.102514e-04, &tj, &tj1, &result, _state);
14978 0 : mannwhitneyu_ucheb(x, 3.559442e-04, &tj, &tj1, &result, _state);
14979 0 : mannwhitneyu_ucheb(x, 4.634986e-05, &tj, &tj1, &result, _state);
14980 0 : mannwhitneyu_ucheb(x, -8.776476e-05, &tj, &tj1, &result, _state);
14981 0 : mannwhitneyu_ucheb(x, 1.054489e-05, &tj, &tj1, &result, _state);
14982 0 : return result;
14983 : }
14984 :
14985 :
14986 : /*************************************************************************
14987 : Tail(S, 7, 15)
14988 : *************************************************************************/
14989 0 : static double mannwhitneyu_utbln7n15(double s, ae_state *_state)
14990 : {
14991 : double x;
14992 : double tj;
14993 : double tj1;
14994 : double result;
14995 :
14996 :
14997 0 : result = (double)(0);
14998 0 : x = ae_minreal(2*(s-0.000000e+00)/3.500000e+00-1, 1.0, _state);
14999 0 : tj = (double)(1);
15000 0 : tj1 = x;
15001 0 : mannwhitneyu_ucheb(x, -4.204898e+00, &tj, &tj1, &result, _state);
15002 0 : mannwhitneyu_ucheb(x, -4.489960e+00, &tj, &tj1, &result, _state);
15003 0 : mannwhitneyu_ucheb(x, -1.129172e+00, &tj, &tj1, &result, _state);
15004 0 : mannwhitneyu_ucheb(x, -2.316741e-01, &tj, &tj1, &result, _state);
15005 0 : mannwhitneyu_ucheb(x, -7.506107e-02, &tj, &tj1, &result, _state);
15006 0 : mannwhitneyu_ucheb(x, -2.983676e-02, &tj, &tj1, &result, _state);
15007 0 : mannwhitneyu_ucheb(x, -1.258013e-02, &tj, &tj1, &result, _state);
15008 0 : mannwhitneyu_ucheb(x, -5.262515e-03, &tj, &tj1, &result, _state);
15009 0 : mannwhitneyu_ucheb(x, -1.984156e-03, &tj, &tj1, &result, _state);
15010 0 : mannwhitneyu_ucheb(x, -3.912108e-04, &tj, &tj1, &result, _state);
15011 0 : mannwhitneyu_ucheb(x, 8.974023e-05, &tj, &tj1, &result, _state);
15012 0 : mannwhitneyu_ucheb(x, 6.056195e-05, &tj, &tj1, &result, _state);
15013 0 : mannwhitneyu_ucheb(x, -2.090842e-04, &tj, &tj1, &result, _state);
15014 0 : mannwhitneyu_ucheb(x, -5.232620e-04, &tj, &tj1, &result, _state);
15015 0 : mannwhitneyu_ucheb(x, -5.816339e-04, &tj, &tj1, &result, _state);
15016 0 : mannwhitneyu_ucheb(x, -7.020421e-04, &tj, &tj1, &result, _state);
15017 0 : return result;
15018 : }
15019 :
15020 :
15021 : /*************************************************************************
15022 : Tail(S, 7, 30)
15023 : *************************************************************************/
15024 0 : static double mannwhitneyu_utbln7n30(double s, ae_state *_state)
15025 : {
15026 : double x;
15027 : double tj;
15028 : double tj1;
15029 : double result;
15030 :
15031 :
15032 0 : result = (double)(0);
15033 0 : x = ae_minreal(2*(s-0.000000e+00)/3.500000e+00-1, 1.0, _state);
15034 0 : tj = (double)(1);
15035 0 : tj1 = x;
15036 0 : mannwhitneyu_ucheb(x, -4.176536e+00, &tj, &tj1, &result, _state);
15037 0 : mannwhitneyu_ucheb(x, -4.398705e+00, &tj, &tj1, &result, _state);
15038 0 : mannwhitneyu_ucheb(x, -1.045481e+00, &tj, &tj1, &result, _state);
15039 0 : mannwhitneyu_ucheb(x, -1.821982e-01, &tj, &tj1, &result, _state);
15040 0 : mannwhitneyu_ucheb(x, -4.962304e-02, &tj, &tj1, &result, _state);
15041 0 : mannwhitneyu_ucheb(x, -1.698132e-02, &tj, &tj1, &result, _state);
15042 0 : mannwhitneyu_ucheb(x, -6.062667e-03, &tj, &tj1, &result, _state);
15043 0 : mannwhitneyu_ucheb(x, -2.282353e-03, &tj, &tj1, &result, _state);
15044 0 : mannwhitneyu_ucheb(x, -8.014836e-04, &tj, &tj1, &result, _state);
15045 0 : mannwhitneyu_ucheb(x, -2.035683e-04, &tj, &tj1, &result, _state);
15046 0 : mannwhitneyu_ucheb(x, -1.004137e-05, &tj, &tj1, &result, _state);
15047 0 : mannwhitneyu_ucheb(x, 3.801453e-06, &tj, &tj1, &result, _state);
15048 0 : mannwhitneyu_ucheb(x, -1.920705e-05, &tj, &tj1, &result, _state);
15049 0 : mannwhitneyu_ucheb(x, -2.518735e-05, &tj, &tj1, &result, _state);
15050 0 : mannwhitneyu_ucheb(x, -1.821501e-05, &tj, &tj1, &result, _state);
15051 0 : mannwhitneyu_ucheb(x, -1.801008e-05, &tj, &tj1, &result, _state);
15052 0 : return result;
15053 : }
15054 :
15055 :
15056 : /*************************************************************************
15057 : Tail(S, 7, 100)
15058 : *************************************************************************/
15059 0 : static double mannwhitneyu_utbln7n100(double s, ae_state *_state)
15060 : {
15061 : double x;
15062 : double tj;
15063 : double tj1;
15064 : double result;
15065 :
15066 :
15067 0 : result = (double)(0);
15068 0 : x = ae_minreal(2*(s-0.000000e+00)/3.500000e+00-1, 1.0, _state);
15069 0 : tj = (double)(1);
15070 0 : tj1 = x;
15071 0 : mannwhitneyu_ucheb(x, -4.188337e+00, &tj, &tj1, &result, _state);
15072 0 : mannwhitneyu_ucheb(x, -4.386949e+00, &tj, &tj1, &result, _state);
15073 0 : mannwhitneyu_ucheb(x, -1.022834e+00, &tj, &tj1, &result, _state);
15074 0 : mannwhitneyu_ucheb(x, -1.686517e-01, &tj, &tj1, &result, _state);
15075 0 : mannwhitneyu_ucheb(x, -4.323516e-02, &tj, &tj1, &result, _state);
15076 0 : mannwhitneyu_ucheb(x, -1.399392e-02, &tj, &tj1, &result, _state);
15077 0 : mannwhitneyu_ucheb(x, -4.644333e-03, &tj, &tj1, &result, _state);
15078 0 : mannwhitneyu_ucheb(x, -1.617044e-03, &tj, &tj1, &result, _state);
15079 0 : mannwhitneyu_ucheb(x, -5.031396e-04, &tj, &tj1, &result, _state);
15080 0 : mannwhitneyu_ucheb(x, -8.792066e-05, &tj, &tj1, &result, _state);
15081 0 : mannwhitneyu_ucheb(x, 2.675457e-05, &tj, &tj1, &result, _state);
15082 0 : mannwhitneyu_ucheb(x, 1.673416e-05, &tj, &tj1, &result, _state);
15083 0 : mannwhitneyu_ucheb(x, -6.258552e-06, &tj, &tj1, &result, _state);
15084 0 : mannwhitneyu_ucheb(x, -8.174214e-06, &tj, &tj1, &result, _state);
15085 0 : mannwhitneyu_ucheb(x, -3.073644e-06, &tj, &tj1, &result, _state);
15086 0 : mannwhitneyu_ucheb(x, -1.349958e-06, &tj, &tj1, &result, _state);
15087 0 : return result;
15088 : }
15089 :
15090 :
15091 : /*************************************************************************
15092 : Tail(S, 8, 8)
15093 : *************************************************************************/
15094 0 : static double mannwhitneyu_utbln8n8(double s, ae_state *_state)
15095 : {
15096 : double x;
15097 : double tj;
15098 : double tj1;
15099 : double result;
15100 :
15101 :
15102 0 : result = (double)(0);
15103 0 : x = ae_minreal(2*(s-0.000000e+00)/3.360672e+00-1, 1.0, _state);
15104 0 : tj = (double)(1);
15105 0 : tj1 = x;
15106 0 : mannwhitneyu_ucheb(x, -3.940217e+00, &tj, &tj1, &result, _state);
15107 0 : mannwhitneyu_ucheb(x, -4.168913e+00, &tj, &tj1, &result, _state);
15108 0 : mannwhitneyu_ucheb(x, -1.051485e+00, &tj, &tj1, &result, _state);
15109 0 : mannwhitneyu_ucheb(x, -2.195325e-01, &tj, &tj1, &result, _state);
15110 0 : mannwhitneyu_ucheb(x, -6.775196e-02, &tj, &tj1, &result, _state);
15111 0 : mannwhitneyu_ucheb(x, -2.385506e-02, &tj, &tj1, &result, _state);
15112 0 : mannwhitneyu_ucheb(x, -8.244902e-03, &tj, &tj1, &result, _state);
15113 0 : mannwhitneyu_ucheb(x, -2.525632e-03, &tj, &tj1, &result, _state);
15114 0 : mannwhitneyu_ucheb(x, 2.771275e-04, &tj, &tj1, &result, _state);
15115 0 : mannwhitneyu_ucheb(x, 2.332874e-03, &tj, &tj1, &result, _state);
15116 0 : mannwhitneyu_ucheb(x, 4.079599e-03, &tj, &tj1, &result, _state);
15117 0 : mannwhitneyu_ucheb(x, 4.882551e-03, &tj, &tj1, &result, _state);
15118 0 : mannwhitneyu_ucheb(x, 4.407944e-03, &tj, &tj1, &result, _state);
15119 0 : mannwhitneyu_ucheb(x, 2.769844e-03, &tj, &tj1, &result, _state);
15120 0 : mannwhitneyu_ucheb(x, 1.062433e-03, &tj, &tj1, &result, _state);
15121 0 : mannwhitneyu_ucheb(x, 5.872535e-05, &tj, &tj1, &result, _state);
15122 0 : return result;
15123 : }
15124 :
15125 :
15126 : /*************************************************************************
15127 : Tail(S, 8, 9)
15128 : *************************************************************************/
15129 0 : static double mannwhitneyu_utbln8n9(double s, ae_state *_state)
15130 : {
15131 : double x;
15132 : double tj;
15133 : double tj1;
15134 : double result;
15135 :
15136 :
15137 0 : result = (double)(0);
15138 0 : x = ae_minreal(2*(s-0.000000e+00)/3.464102e+00-1, 1.0, _state);
15139 0 : tj = (double)(1);
15140 0 : tj1 = x;
15141 0 : mannwhitneyu_ucheb(x, -4.147004e+00, &tj, &tj1, &result, _state);
15142 0 : mannwhitneyu_ucheb(x, -4.446939e+00, &tj, &tj1, &result, _state);
15143 0 : mannwhitneyu_ucheb(x, -1.146155e+00, &tj, &tj1, &result, _state);
15144 0 : mannwhitneyu_ucheb(x, -2.488561e-01, &tj, &tj1, &result, _state);
15145 0 : mannwhitneyu_ucheb(x, -8.144561e-02, &tj, &tj1, &result, _state);
15146 0 : mannwhitneyu_ucheb(x, -3.116917e-02, &tj, &tj1, &result, _state);
15147 0 : mannwhitneyu_ucheb(x, -1.205667e-02, &tj, &tj1, &result, _state);
15148 0 : mannwhitneyu_ucheb(x, -4.515661e-03, &tj, &tj1, &result, _state);
15149 0 : mannwhitneyu_ucheb(x, -7.618616e-04, &tj, &tj1, &result, _state);
15150 0 : mannwhitneyu_ucheb(x, 1.599011e-03, &tj, &tj1, &result, _state);
15151 0 : mannwhitneyu_ucheb(x, 3.457324e-03, &tj, &tj1, &result, _state);
15152 0 : mannwhitneyu_ucheb(x, 4.482917e-03, &tj, &tj1, &result, _state);
15153 0 : mannwhitneyu_ucheb(x, 4.488267e-03, &tj, &tj1, &result, _state);
15154 0 : mannwhitneyu_ucheb(x, 3.469823e-03, &tj, &tj1, &result, _state);
15155 0 : mannwhitneyu_ucheb(x, 1.957591e-03, &tj, &tj1, &result, _state);
15156 0 : mannwhitneyu_ucheb(x, 8.058326e-04, &tj, &tj1, &result, _state);
15157 0 : return result;
15158 : }
15159 :
15160 :
15161 : /*************************************************************************
15162 : Tail(S, 8, 10)
15163 : *************************************************************************/
15164 0 : static double mannwhitneyu_utbln8n10(double s, ae_state *_state)
15165 : {
15166 : double x;
15167 : double tj;
15168 : double tj1;
15169 : double result;
15170 :
15171 :
15172 0 : result = (double)(0);
15173 0 : x = ae_minreal(2*(s-0.000000e+00)/3.554093e+00-1, 1.0, _state);
15174 0 : tj = (double)(1);
15175 0 : tj1 = x;
15176 0 : mannwhitneyu_ucheb(x, -4.334282e+00, &tj, &tj1, &result, _state);
15177 0 : mannwhitneyu_ucheb(x, -4.700860e+00, &tj, &tj1, &result, _state);
15178 0 : mannwhitneyu_ucheb(x, -1.235253e+00, &tj, &tj1, &result, _state);
15179 0 : mannwhitneyu_ucheb(x, -2.778489e-01, &tj, &tj1, &result, _state);
15180 0 : mannwhitneyu_ucheb(x, -9.527324e-02, &tj, &tj1, &result, _state);
15181 0 : mannwhitneyu_ucheb(x, -3.862885e-02, &tj, &tj1, &result, _state);
15182 0 : mannwhitneyu_ucheb(x, -1.589781e-02, &tj, &tj1, &result, _state);
15183 0 : mannwhitneyu_ucheb(x, -6.507355e-03, &tj, &tj1, &result, _state);
15184 0 : mannwhitneyu_ucheb(x, -1.717526e-03, &tj, &tj1, &result, _state);
15185 0 : mannwhitneyu_ucheb(x, 9.215726e-04, &tj, &tj1, &result, _state);
15186 0 : mannwhitneyu_ucheb(x, 2.848696e-03, &tj, &tj1, &result, _state);
15187 0 : mannwhitneyu_ucheb(x, 3.918854e-03, &tj, &tj1, &result, _state);
15188 0 : mannwhitneyu_ucheb(x, 4.219614e-03, &tj, &tj1, &result, _state);
15189 0 : mannwhitneyu_ucheb(x, 3.753761e-03, &tj, &tj1, &result, _state);
15190 0 : mannwhitneyu_ucheb(x, 2.573688e-03, &tj, &tj1, &result, _state);
15191 0 : mannwhitneyu_ucheb(x, 1.602177e-03, &tj, &tj1, &result, _state);
15192 0 : return result;
15193 : }
15194 :
15195 :
15196 : /*************************************************************************
15197 : Tail(S, 8, 11)
15198 : *************************************************************************/
15199 0 : static double mannwhitneyu_utbln8n11(double s, ae_state *_state)
15200 : {
15201 : double x;
15202 : double tj;
15203 : double tj1;
15204 : double result;
15205 :
15206 :
15207 0 : result = (double)(0);
15208 0 : x = ae_minreal(2*(s-0.000000e+00)/3.600000e+00-1, 1.0, _state);
15209 0 : tj = (double)(1);
15210 0 : tj1 = x;
15211 0 : mannwhitneyu_ucheb(x, -4.421882e+00, &tj, &tj1, &result, _state);
15212 0 : mannwhitneyu_ucheb(x, -4.812457e+00, &tj, &tj1, &result, _state);
15213 0 : mannwhitneyu_ucheb(x, -1.266153e+00, &tj, &tj1, &result, _state);
15214 0 : mannwhitneyu_ucheb(x, -2.849344e-01, &tj, &tj1, &result, _state);
15215 0 : mannwhitneyu_ucheb(x, -9.971527e-02, &tj, &tj1, &result, _state);
15216 0 : mannwhitneyu_ucheb(x, -4.258944e-02, &tj, &tj1, &result, _state);
15217 0 : mannwhitneyu_ucheb(x, -1.944820e-02, &tj, &tj1, &result, _state);
15218 0 : mannwhitneyu_ucheb(x, -9.894685e-03, &tj, &tj1, &result, _state);
15219 0 : mannwhitneyu_ucheb(x, -5.031836e-03, &tj, &tj1, &result, _state);
15220 0 : mannwhitneyu_ucheb(x, -2.514330e-03, &tj, &tj1, &result, _state);
15221 0 : mannwhitneyu_ucheb(x, -6.351660e-04, &tj, &tj1, &result, _state);
15222 0 : mannwhitneyu_ucheb(x, 6.206748e-04, &tj, &tj1, &result, _state);
15223 0 : mannwhitneyu_ucheb(x, 1.492600e-03, &tj, &tj1, &result, _state);
15224 0 : mannwhitneyu_ucheb(x, 2.005338e-03, &tj, &tj1, &result, _state);
15225 0 : mannwhitneyu_ucheb(x, 1.780099e-03, &tj, &tj1, &result, _state);
15226 0 : mannwhitneyu_ucheb(x, 1.673599e-03, &tj, &tj1, &result, _state);
15227 0 : return result;
15228 : }
15229 :
15230 :
15231 : /*************************************************************************
15232 : Tail(S, 8, 12)
15233 : *************************************************************************/
15234 0 : static double mannwhitneyu_utbln8n12(double s, ae_state *_state)
15235 : {
15236 : double x;
15237 : double tj;
15238 : double tj1;
15239 : double result;
15240 :
15241 :
15242 0 : result = (double)(0);
15243 0 : x = ae_minreal(2*(s-0.000000e+00)/3.600000e+00-1, 1.0, _state);
15244 0 : tj = (double)(1);
15245 0 : tj1 = x;
15246 0 : mannwhitneyu_ucheb(x, -4.398211e+00, &tj, &tj1, &result, _state);
15247 0 : mannwhitneyu_ucheb(x, -4.762214e+00, &tj, &tj1, &result, _state);
15248 0 : mannwhitneyu_ucheb(x, -1.226296e+00, &tj, &tj1, &result, _state);
15249 0 : mannwhitneyu_ucheb(x, -2.603837e-01, &tj, &tj1, &result, _state);
15250 0 : mannwhitneyu_ucheb(x, -8.643223e-02, &tj, &tj1, &result, _state);
15251 0 : mannwhitneyu_ucheb(x, -3.502438e-02, &tj, &tj1, &result, _state);
15252 0 : mannwhitneyu_ucheb(x, -1.544574e-02, &tj, &tj1, &result, _state);
15253 0 : mannwhitneyu_ucheb(x, -7.647734e-03, &tj, &tj1, &result, _state);
15254 0 : mannwhitneyu_ucheb(x, -4.442259e-03, &tj, &tj1, &result, _state);
15255 0 : mannwhitneyu_ucheb(x, -3.011484e-03, &tj, &tj1, &result, _state);
15256 0 : mannwhitneyu_ucheb(x, -2.384758e-03, &tj, &tj1, &result, _state);
15257 0 : mannwhitneyu_ucheb(x, -1.998259e-03, &tj, &tj1, &result, _state);
15258 0 : mannwhitneyu_ucheb(x, -1.659985e-03, &tj, &tj1, &result, _state);
15259 0 : mannwhitneyu_ucheb(x, -1.331046e-03, &tj, &tj1, &result, _state);
15260 0 : mannwhitneyu_ucheb(x, -8.638478e-04, &tj, &tj1, &result, _state);
15261 0 : mannwhitneyu_ucheb(x, -6.056785e-04, &tj, &tj1, &result, _state);
15262 0 : return result;
15263 : }
15264 :
15265 :
15266 : /*************************************************************************
15267 : Tail(S, 8, 13)
15268 : *************************************************************************/
15269 0 : static double mannwhitneyu_utbln8n13(double s, ae_state *_state)
15270 : {
15271 : double x;
15272 : double tj;
15273 : double tj1;
15274 : double result;
15275 :
15276 :
15277 0 : result = (double)(0);
15278 0 : x = ae_minreal(2*(s-0.000000e+00)/3.600000e+00-1, 1.0, _state);
15279 0 : tj = (double)(1);
15280 0 : tj1 = x;
15281 0 : mannwhitneyu_ucheb(x, -4.380670e+00, &tj, &tj1, &result, _state);
15282 0 : mannwhitneyu_ucheb(x, -4.724511e+00, &tj, &tj1, &result, _state);
15283 0 : mannwhitneyu_ucheb(x, -1.195851e+00, &tj, &tj1, &result, _state);
15284 0 : mannwhitneyu_ucheb(x, -2.420511e-01, &tj, &tj1, &result, _state);
15285 0 : mannwhitneyu_ucheb(x, -7.609928e-02, &tj, &tj1, &result, _state);
15286 0 : mannwhitneyu_ucheb(x, -2.893999e-02, &tj, &tj1, &result, _state);
15287 0 : mannwhitneyu_ucheb(x, -1.115919e-02, &tj, &tj1, &result, _state);
15288 0 : mannwhitneyu_ucheb(x, -4.291410e-03, &tj, &tj1, &result, _state);
15289 0 : mannwhitneyu_ucheb(x, -1.339664e-03, &tj, &tj1, &result, _state);
15290 0 : mannwhitneyu_ucheb(x, -1.801548e-04, &tj, &tj1, &result, _state);
15291 0 : mannwhitneyu_ucheb(x, 2.534710e-04, &tj, &tj1, &result, _state);
15292 0 : mannwhitneyu_ucheb(x, 2.793250e-04, &tj, &tj1, &result, _state);
15293 0 : mannwhitneyu_ucheb(x, 1.806718e-04, &tj, &tj1, &result, _state);
15294 0 : mannwhitneyu_ucheb(x, 1.384624e-04, &tj, &tj1, &result, _state);
15295 0 : mannwhitneyu_ucheb(x, 1.120582e-04, &tj, &tj1, &result, _state);
15296 0 : mannwhitneyu_ucheb(x, 2.936453e-04, &tj, &tj1, &result, _state);
15297 0 : return result;
15298 : }
15299 :
15300 :
15301 : /*************************************************************************
15302 : Tail(S, 8, 14)
15303 : *************************************************************************/
15304 0 : static double mannwhitneyu_utbln8n14(double s, ae_state *_state)
15305 : {
15306 : double x;
15307 : double tj;
15308 : double tj1;
15309 : double result;
15310 :
15311 :
15312 0 : result = (double)(0);
15313 0 : x = ae_minreal(2*(s-0.000000e+00)/3.600000e+00-1, 1.0, _state);
15314 0 : tj = (double)(1);
15315 0 : tj1 = x;
15316 0 : mannwhitneyu_ucheb(x, -4.368494e+00, &tj, &tj1, &result, _state);
15317 0 : mannwhitneyu_ucheb(x, -4.697171e+00, &tj, &tj1, &result, _state);
15318 0 : mannwhitneyu_ucheb(x, -1.174440e+00, &tj, &tj1, &result, _state);
15319 0 : mannwhitneyu_ucheb(x, -2.300621e-01, &tj, &tj1, &result, _state);
15320 0 : mannwhitneyu_ucheb(x, -7.087393e-02, &tj, &tj1, &result, _state);
15321 0 : mannwhitneyu_ucheb(x, -2.685826e-02, &tj, &tj1, &result, _state);
15322 0 : mannwhitneyu_ucheb(x, -1.085254e-02, &tj, &tj1, &result, _state);
15323 0 : mannwhitneyu_ucheb(x, -4.525658e-03, &tj, &tj1, &result, _state);
15324 0 : mannwhitneyu_ucheb(x, -1.966647e-03, &tj, &tj1, &result, _state);
15325 0 : mannwhitneyu_ucheb(x, -7.453388e-04, &tj, &tj1, &result, _state);
15326 0 : mannwhitneyu_ucheb(x, -3.826066e-04, &tj, &tj1, &result, _state);
15327 0 : mannwhitneyu_ucheb(x, -3.501958e-04, &tj, &tj1, &result, _state);
15328 0 : mannwhitneyu_ucheb(x, -5.336297e-04, &tj, &tj1, &result, _state);
15329 0 : mannwhitneyu_ucheb(x, -8.251972e-04, &tj, &tj1, &result, _state);
15330 0 : mannwhitneyu_ucheb(x, -8.118456e-04, &tj, &tj1, &result, _state);
15331 0 : mannwhitneyu_ucheb(x, -9.415959e-04, &tj, &tj1, &result, _state);
15332 0 : return result;
15333 : }
15334 :
15335 :
15336 : /*************************************************************************
15337 : Tail(S, 8, 15)
15338 : *************************************************************************/
15339 0 : static double mannwhitneyu_utbln8n15(double s, ae_state *_state)
15340 : {
15341 : double x;
15342 : double tj;
15343 : double tj1;
15344 : double result;
15345 :
15346 :
15347 0 : result = (double)(0);
15348 0 : x = ae_minreal(2*(s-0.000000e+00)/3.600000e+00-1, 1.0, _state);
15349 0 : tj = (double)(1);
15350 0 : tj1 = x;
15351 0 : mannwhitneyu_ucheb(x, -4.358397e+00, &tj, &tj1, &result, _state);
15352 0 : mannwhitneyu_ucheb(x, -4.674485e+00, &tj, &tj1, &result, _state);
15353 0 : mannwhitneyu_ucheb(x, -1.155941e+00, &tj, &tj1, &result, _state);
15354 0 : mannwhitneyu_ucheb(x, -2.195780e-01, &tj, &tj1, &result, _state);
15355 0 : mannwhitneyu_ucheb(x, -6.544830e-02, &tj, &tj1, &result, _state);
15356 0 : mannwhitneyu_ucheb(x, -2.426183e-02, &tj, &tj1, &result, _state);
15357 0 : mannwhitneyu_ucheb(x, -9.309902e-03, &tj, &tj1, &result, _state);
15358 0 : mannwhitneyu_ucheb(x, -3.650956e-03, &tj, &tj1, &result, _state);
15359 0 : mannwhitneyu_ucheb(x, -1.068874e-03, &tj, &tj1, &result, _state);
15360 0 : mannwhitneyu_ucheb(x, 1.538544e-04, &tj, &tj1, &result, _state);
15361 0 : mannwhitneyu_ucheb(x, 8.192525e-04, &tj, &tj1, &result, _state);
15362 0 : mannwhitneyu_ucheb(x, 1.073905e-03, &tj, &tj1, &result, _state);
15363 0 : mannwhitneyu_ucheb(x, 1.079673e-03, &tj, &tj1, &result, _state);
15364 0 : mannwhitneyu_ucheb(x, 9.423572e-04, &tj, &tj1, &result, _state);
15365 0 : mannwhitneyu_ucheb(x, 6.579647e-04, &tj, &tj1, &result, _state);
15366 0 : mannwhitneyu_ucheb(x, 4.765904e-04, &tj, &tj1, &result, _state);
15367 0 : return result;
15368 : }
15369 :
15370 :
15371 : /*************************************************************************
15372 : Tail(S, 8, 30)
15373 : *************************************************************************/
15374 0 : static double mannwhitneyu_utbln8n30(double s, ae_state *_state)
15375 : {
15376 : double x;
15377 : double tj;
15378 : double tj1;
15379 : double result;
15380 :
15381 :
15382 0 : result = (double)(0);
15383 0 : x = ae_minreal(2*(s-0.000000e+00)/3.600000e+00-1, 1.0, _state);
15384 0 : tj = (double)(1);
15385 0 : tj1 = x;
15386 0 : mannwhitneyu_ucheb(x, -4.318823e+00, &tj, &tj1, &result, _state);
15387 0 : mannwhitneyu_ucheb(x, -4.567159e+00, &tj, &tj1, &result, _state);
15388 0 : mannwhitneyu_ucheb(x, -1.064864e+00, &tj, &tj1, &result, _state);
15389 0 : mannwhitneyu_ucheb(x, -1.688413e-01, &tj, &tj1, &result, _state);
15390 0 : mannwhitneyu_ucheb(x, -4.153712e-02, &tj, &tj1, &result, _state);
15391 0 : mannwhitneyu_ucheb(x, -1.309389e-02, &tj, &tj1, &result, _state);
15392 0 : mannwhitneyu_ucheb(x, -4.226861e-03, &tj, &tj1, &result, _state);
15393 0 : mannwhitneyu_ucheb(x, -1.523815e-03, &tj, &tj1, &result, _state);
15394 0 : mannwhitneyu_ucheb(x, -5.780987e-04, &tj, &tj1, &result, _state);
15395 0 : mannwhitneyu_ucheb(x, -2.166866e-04, &tj, &tj1, &result, _state);
15396 0 : mannwhitneyu_ucheb(x, -6.922431e-05, &tj, &tj1, &result, _state);
15397 0 : mannwhitneyu_ucheb(x, -1.466397e-05, &tj, &tj1, &result, _state);
15398 0 : mannwhitneyu_ucheb(x, -5.690036e-06, &tj, &tj1, &result, _state);
15399 0 : mannwhitneyu_ucheb(x, -1.008185e-05, &tj, &tj1, &result, _state);
15400 0 : mannwhitneyu_ucheb(x, -9.271903e-06, &tj, &tj1, &result, _state);
15401 0 : mannwhitneyu_ucheb(x, -7.534751e-06, &tj, &tj1, &result, _state);
15402 0 : return result;
15403 : }
15404 :
15405 :
15406 : /*************************************************************************
15407 : Tail(S, 8, 100)
15408 : *************************************************************************/
15409 0 : static double mannwhitneyu_utbln8n100(double s, ae_state *_state)
15410 : {
15411 : double x;
15412 : double tj;
15413 : double tj1;
15414 : double result;
15415 :
15416 :
15417 0 : result = (double)(0);
15418 0 : x = ae_minreal(2*(s-0.000000e+00)/3.600000e+00-1, 1.0, _state);
15419 0 : tj = (double)(1);
15420 0 : tj1 = x;
15421 0 : mannwhitneyu_ucheb(x, -4.324531e+00, &tj, &tj1, &result, _state);
15422 0 : mannwhitneyu_ucheb(x, -4.547071e+00, &tj, &tj1, &result, _state);
15423 0 : mannwhitneyu_ucheb(x, -1.038129e+00, &tj, &tj1, &result, _state);
15424 0 : mannwhitneyu_ucheb(x, -1.541549e-01, &tj, &tj1, &result, _state);
15425 0 : mannwhitneyu_ucheb(x, -3.525605e-02, &tj, &tj1, &result, _state);
15426 0 : mannwhitneyu_ucheb(x, -1.044992e-02, &tj, &tj1, &result, _state);
15427 0 : mannwhitneyu_ucheb(x, -3.085713e-03, &tj, &tj1, &result, _state);
15428 0 : mannwhitneyu_ucheb(x, -1.017871e-03, &tj, &tj1, &result, _state);
15429 0 : mannwhitneyu_ucheb(x, -3.459226e-04, &tj, &tj1, &result, _state);
15430 0 : mannwhitneyu_ucheb(x, -1.092064e-04, &tj, &tj1, &result, _state);
15431 0 : mannwhitneyu_ucheb(x, -2.024349e-05, &tj, &tj1, &result, _state);
15432 0 : mannwhitneyu_ucheb(x, 7.366347e-06, &tj, &tj1, &result, _state);
15433 0 : mannwhitneyu_ucheb(x, 6.385637e-06, &tj, &tj1, &result, _state);
15434 0 : mannwhitneyu_ucheb(x, 8.321722e-08, &tj, &tj1, &result, _state);
15435 0 : mannwhitneyu_ucheb(x, -1.439286e-06, &tj, &tj1, &result, _state);
15436 0 : mannwhitneyu_ucheb(x, -3.058079e-07, &tj, &tj1, &result, _state);
15437 0 : return result;
15438 : }
15439 :
15440 :
15441 : /*************************************************************************
15442 : Tail(S, 9, 9)
15443 : *************************************************************************/
15444 0 : static double mannwhitneyu_utbln9n9(double s, ae_state *_state)
15445 : {
15446 : double x;
15447 : double tj;
15448 : double tj1;
15449 : double result;
15450 :
15451 :
15452 0 : result = (double)(0);
15453 0 : x = ae_minreal(2*(s-0.000000e+00)/3.576237e+00-1, 1.0, _state);
15454 0 : tj = (double)(1);
15455 0 : tj1 = x;
15456 0 : mannwhitneyu_ucheb(x, -4.372857e+00, &tj, &tj1, &result, _state);
15457 0 : mannwhitneyu_ucheb(x, -4.750859e+00, &tj, &tj1, &result, _state);
15458 0 : mannwhitneyu_ucheb(x, -1.248233e+00, &tj, &tj1, &result, _state);
15459 0 : mannwhitneyu_ucheb(x, -2.792868e-01, &tj, &tj1, &result, _state);
15460 0 : mannwhitneyu_ucheb(x, -9.559372e-02, &tj, &tj1, &result, _state);
15461 0 : mannwhitneyu_ucheb(x, -3.894941e-02, &tj, &tj1, &result, _state);
15462 0 : mannwhitneyu_ucheb(x, -1.643256e-02, &tj, &tj1, &result, _state);
15463 0 : mannwhitneyu_ucheb(x, -7.091370e-03, &tj, &tj1, &result, _state);
15464 0 : mannwhitneyu_ucheb(x, -2.285034e-03, &tj, &tj1, &result, _state);
15465 0 : mannwhitneyu_ucheb(x, 6.112997e-04, &tj, &tj1, &result, _state);
15466 0 : mannwhitneyu_ucheb(x, 2.806229e-03, &tj, &tj1, &result, _state);
15467 0 : mannwhitneyu_ucheb(x, 4.150741e-03, &tj, &tj1, &result, _state);
15468 0 : mannwhitneyu_ucheb(x, 4.509825e-03, &tj, &tj1, &result, _state);
15469 0 : mannwhitneyu_ucheb(x, 3.891051e-03, &tj, &tj1, &result, _state);
15470 0 : mannwhitneyu_ucheb(x, 2.485013e-03, &tj, &tj1, &result, _state);
15471 0 : mannwhitneyu_ucheb(x, 1.343653e-03, &tj, &tj1, &result, _state);
15472 0 : return result;
15473 : }
15474 :
15475 :
15476 : /*************************************************************************
15477 : Tail(S, 9, 10)
15478 : *************************************************************************/
15479 0 : static double mannwhitneyu_utbln9n10(double s, ae_state *_state)
15480 : {
15481 : double x;
15482 : double tj;
15483 : double tj1;
15484 : double result;
15485 :
15486 :
15487 0 : result = (double)(0);
15488 0 : x = ae_minreal(2*(s-0.000000e+00)/3.650000e+00-1, 1.0, _state);
15489 0 : tj = (double)(1);
15490 0 : tj1 = x;
15491 0 : mannwhitneyu_ucheb(x, -4.516726e+00, &tj, &tj1, &result, _state);
15492 0 : mannwhitneyu_ucheb(x, -4.939333e+00, &tj, &tj1, &result, _state);
15493 0 : mannwhitneyu_ucheb(x, -1.305046e+00, &tj, &tj1, &result, _state);
15494 0 : mannwhitneyu_ucheb(x, -2.935326e-01, &tj, &tj1, &result, _state);
15495 0 : mannwhitneyu_ucheb(x, -1.029141e-01, &tj, &tj1, &result, _state);
15496 0 : mannwhitneyu_ucheb(x, -4.420592e-02, &tj, &tj1, &result, _state);
15497 0 : mannwhitneyu_ucheb(x, -2.053140e-02, &tj, &tj1, &result, _state);
15498 0 : mannwhitneyu_ucheb(x, -1.065930e-02, &tj, &tj1, &result, _state);
15499 0 : mannwhitneyu_ucheb(x, -5.523581e-03, &tj, &tj1, &result, _state);
15500 0 : mannwhitneyu_ucheb(x, -2.544888e-03, &tj, &tj1, &result, _state);
15501 0 : mannwhitneyu_ucheb(x, -1.813741e-04, &tj, &tj1, &result, _state);
15502 0 : mannwhitneyu_ucheb(x, 1.510631e-03, &tj, &tj1, &result, _state);
15503 0 : mannwhitneyu_ucheb(x, 2.536057e-03, &tj, &tj1, &result, _state);
15504 0 : mannwhitneyu_ucheb(x, 2.833815e-03, &tj, &tj1, &result, _state);
15505 0 : mannwhitneyu_ucheb(x, 2.189692e-03, &tj, &tj1, &result, _state);
15506 0 : mannwhitneyu_ucheb(x, 1.615050e-03, &tj, &tj1, &result, _state);
15507 0 : return result;
15508 : }
15509 :
15510 :
15511 : /*************************************************************************
15512 : Tail(S, 9, 11)
15513 : *************************************************************************/
15514 0 : static double mannwhitneyu_utbln9n11(double s, ae_state *_state)
15515 : {
15516 : double x;
15517 : double tj;
15518 : double tj1;
15519 : double result;
15520 :
15521 :
15522 0 : result = (double)(0);
15523 0 : x = ae_minreal(2*(s-0.000000e+00)/3.650000e+00-1, 1.0, _state);
15524 0 : tj = (double)(1);
15525 0 : tj1 = x;
15526 0 : mannwhitneyu_ucheb(x, -4.481308e+00, &tj, &tj1, &result, _state);
15527 0 : mannwhitneyu_ucheb(x, -4.867483e+00, &tj, &tj1, &result, _state);
15528 0 : mannwhitneyu_ucheb(x, -1.249072e+00, &tj, &tj1, &result, _state);
15529 0 : mannwhitneyu_ucheb(x, -2.591790e-01, &tj, &tj1, &result, _state);
15530 0 : mannwhitneyu_ucheb(x, -8.400128e-02, &tj, &tj1, &result, _state);
15531 0 : mannwhitneyu_ucheb(x, -3.341992e-02, &tj, &tj1, &result, _state);
15532 0 : mannwhitneyu_ucheb(x, -1.463680e-02, &tj, &tj1, &result, _state);
15533 0 : mannwhitneyu_ucheb(x, -7.487211e-03, &tj, &tj1, &result, _state);
15534 0 : mannwhitneyu_ucheb(x, -4.671196e-03, &tj, &tj1, &result, _state);
15535 0 : mannwhitneyu_ucheb(x, -3.343472e-03, &tj, &tj1, &result, _state);
15536 0 : mannwhitneyu_ucheb(x, -2.544146e-03, &tj, &tj1, &result, _state);
15537 0 : mannwhitneyu_ucheb(x, -1.802335e-03, &tj, &tj1, &result, _state);
15538 0 : mannwhitneyu_ucheb(x, -1.117084e-03, &tj, &tj1, &result, _state);
15539 0 : mannwhitneyu_ucheb(x, -6.217443e-04, &tj, &tj1, &result, _state);
15540 0 : mannwhitneyu_ucheb(x, -2.858766e-04, &tj, &tj1, &result, _state);
15541 0 : mannwhitneyu_ucheb(x, -3.193687e-04, &tj, &tj1, &result, _state);
15542 0 : return result;
15543 : }
15544 :
15545 :
15546 : /*************************************************************************
15547 : Tail(S, 9, 12)
15548 : *************************************************************************/
15549 0 : static double mannwhitneyu_utbln9n12(double s, ae_state *_state)
15550 : {
15551 : double x;
15552 : double tj;
15553 : double tj1;
15554 : double result;
15555 :
15556 :
15557 0 : result = (double)(0);
15558 0 : x = ae_minreal(2*(s-0.000000e+00)/3.650000e+00-1, 1.0, _state);
15559 0 : tj = (double)(1);
15560 0 : tj1 = x;
15561 0 : mannwhitneyu_ucheb(x, -4.456776e+00, &tj, &tj1, &result, _state);
15562 0 : mannwhitneyu_ucheb(x, -4.817037e+00, &tj, &tj1, &result, _state);
15563 0 : mannwhitneyu_ucheb(x, -1.209788e+00, &tj, &tj1, &result, _state);
15564 0 : mannwhitneyu_ucheb(x, -2.362108e-01, &tj, &tj1, &result, _state);
15565 0 : mannwhitneyu_ucheb(x, -7.171356e-02, &tj, &tj1, &result, _state);
15566 0 : mannwhitneyu_ucheb(x, -2.661557e-02, &tj, &tj1, &result, _state);
15567 0 : mannwhitneyu_ucheb(x, -1.026141e-02, &tj, &tj1, &result, _state);
15568 0 : mannwhitneyu_ucheb(x, -4.361908e-03, &tj, &tj1, &result, _state);
15569 0 : mannwhitneyu_ucheb(x, -2.093885e-03, &tj, &tj1, &result, _state);
15570 0 : mannwhitneyu_ucheb(x, -1.298389e-03, &tj, &tj1, &result, _state);
15571 0 : mannwhitneyu_ucheb(x, -9.663603e-04, &tj, &tj1, &result, _state);
15572 0 : mannwhitneyu_ucheb(x, -7.768522e-04, &tj, &tj1, &result, _state);
15573 0 : mannwhitneyu_ucheb(x, -5.579015e-04, &tj, &tj1, &result, _state);
15574 0 : mannwhitneyu_ucheb(x, -2.868677e-04, &tj, &tj1, &result, _state);
15575 0 : mannwhitneyu_ucheb(x, -7.440652e-05, &tj, &tj1, &result, _state);
15576 0 : mannwhitneyu_ucheb(x, 1.523037e-04, &tj, &tj1, &result, _state);
15577 0 : return result;
15578 : }
15579 :
15580 :
15581 : /*************************************************************************
15582 : Tail(S, 9, 13)
15583 : *************************************************************************/
15584 0 : static double mannwhitneyu_utbln9n13(double s, ae_state *_state)
15585 : {
15586 : double x;
15587 : double tj;
15588 : double tj1;
15589 : double result;
15590 :
15591 :
15592 0 : result = (double)(0);
15593 0 : x = ae_minreal(2*(s-0.000000e+00)/3.650000e+00-1, 1.0, _state);
15594 0 : tj = (double)(1);
15595 0 : tj1 = x;
15596 0 : mannwhitneyu_ucheb(x, -4.438840e+00, &tj, &tj1, &result, _state);
15597 0 : mannwhitneyu_ucheb(x, -4.779308e+00, &tj, &tj1, &result, _state);
15598 0 : mannwhitneyu_ucheb(x, -1.180614e+00, &tj, &tj1, &result, _state);
15599 0 : mannwhitneyu_ucheb(x, -2.196489e-01, &tj, &tj1, &result, _state);
15600 0 : mannwhitneyu_ucheb(x, -6.346621e-02, &tj, &tj1, &result, _state);
15601 0 : mannwhitneyu_ucheb(x, -2.234857e-02, &tj, &tj1, &result, _state);
15602 0 : mannwhitneyu_ucheb(x, -7.796211e-03, &tj, &tj1, &result, _state);
15603 0 : mannwhitneyu_ucheb(x, -2.575715e-03, &tj, &tj1, &result, _state);
15604 0 : mannwhitneyu_ucheb(x, -5.525647e-04, &tj, &tj1, &result, _state);
15605 0 : mannwhitneyu_ucheb(x, 1.964651e-04, &tj, &tj1, &result, _state);
15606 0 : mannwhitneyu_ucheb(x, 4.275235e-04, &tj, &tj1, &result, _state);
15607 0 : mannwhitneyu_ucheb(x, 4.299124e-04, &tj, &tj1, &result, _state);
15608 0 : mannwhitneyu_ucheb(x, 3.397416e-04, &tj, &tj1, &result, _state);
15609 0 : mannwhitneyu_ucheb(x, 2.295781e-04, &tj, &tj1, &result, _state);
15610 0 : mannwhitneyu_ucheb(x, 1.237619e-04, &tj, &tj1, &result, _state);
15611 0 : mannwhitneyu_ucheb(x, 7.269692e-05, &tj, &tj1, &result, _state);
15612 0 : return result;
15613 : }
15614 :
15615 :
15616 : /*************************************************************************
15617 : Tail(S, 9, 14)
15618 : *************************************************************************/
15619 0 : static double mannwhitneyu_utbln9n14(double s, ae_state *_state)
15620 : {
15621 : double x;
15622 : double tj;
15623 : double tj1;
15624 : double result;
15625 :
15626 :
15627 0 : result = (double)(0);
15628 0 : x = ae_minreal(2*(s-0.000000e+00)/3.650000e+00-1, 1.0, _state);
15629 0 : tj = (double)(1);
15630 0 : tj1 = x;
15631 0 : mannwhitneyu_ucheb(x, -4.425981e+00, &tj, &tj1, &result, _state);
15632 0 : mannwhitneyu_ucheb(x, -4.751545e+00, &tj, &tj1, &result, _state);
15633 0 : mannwhitneyu_ucheb(x, -1.159543e+00, &tj, &tj1, &result, _state);
15634 0 : mannwhitneyu_ucheb(x, -2.086570e-01, &tj, &tj1, &result, _state);
15635 0 : mannwhitneyu_ucheb(x, -5.917446e-02, &tj, &tj1, &result, _state);
15636 0 : mannwhitneyu_ucheb(x, -2.120112e-02, &tj, &tj1, &result, _state);
15637 0 : mannwhitneyu_ucheb(x, -8.175519e-03, &tj, &tj1, &result, _state);
15638 0 : mannwhitneyu_ucheb(x, -3.515473e-03, &tj, &tj1, &result, _state);
15639 0 : mannwhitneyu_ucheb(x, -1.727772e-03, &tj, &tj1, &result, _state);
15640 0 : mannwhitneyu_ucheb(x, -9.070629e-04, &tj, &tj1, &result, _state);
15641 0 : mannwhitneyu_ucheb(x, -5.677569e-04, &tj, &tj1, &result, _state);
15642 0 : mannwhitneyu_ucheb(x, -3.876953e-04, &tj, &tj1, &result, _state);
15643 0 : mannwhitneyu_ucheb(x, -3.233502e-04, &tj, &tj1, &result, _state);
15644 0 : mannwhitneyu_ucheb(x, -3.508182e-04, &tj, &tj1, &result, _state);
15645 0 : mannwhitneyu_ucheb(x, -3.120389e-04, &tj, &tj1, &result, _state);
15646 0 : mannwhitneyu_ucheb(x, -3.847212e-04, &tj, &tj1, &result, _state);
15647 0 : return result;
15648 : }
15649 :
15650 :
15651 : /*************************************************************************
15652 : Tail(S, 9, 15)
15653 : *************************************************************************/
15654 0 : static double mannwhitneyu_utbln9n15(double s, ae_state *_state)
15655 : {
15656 : double x;
15657 : double tj;
15658 : double tj1;
15659 : double result;
15660 :
15661 :
15662 0 : result = (double)(0);
15663 0 : x = ae_minreal(2*(s-0.000000e+00)/3.650000e+00-1, 1.0, _state);
15664 0 : tj = (double)(1);
15665 0 : tj1 = x;
15666 0 : mannwhitneyu_ucheb(x, -4.414952e+00, &tj, &tj1, &result, _state);
15667 0 : mannwhitneyu_ucheb(x, -4.727612e+00, &tj, &tj1, &result, _state);
15668 0 : mannwhitneyu_ucheb(x, -1.140634e+00, &tj, &tj1, &result, _state);
15669 0 : mannwhitneyu_ucheb(x, -1.981231e-01, &tj, &tj1, &result, _state);
15670 0 : mannwhitneyu_ucheb(x, -5.382635e-02, &tj, &tj1, &result, _state);
15671 0 : mannwhitneyu_ucheb(x, -1.853575e-02, &tj, &tj1, &result, _state);
15672 0 : mannwhitneyu_ucheb(x, -6.571051e-03, &tj, &tj1, &result, _state);
15673 0 : mannwhitneyu_ucheb(x, -2.567625e-03, &tj, &tj1, &result, _state);
15674 0 : mannwhitneyu_ucheb(x, -9.214197e-04, &tj, &tj1, &result, _state);
15675 0 : mannwhitneyu_ucheb(x, -2.448700e-04, &tj, &tj1, &result, _state);
15676 0 : mannwhitneyu_ucheb(x, 1.712669e-04, &tj, &tj1, &result, _state);
15677 0 : mannwhitneyu_ucheb(x, 4.015050e-04, &tj, &tj1, &result, _state);
15678 0 : mannwhitneyu_ucheb(x, 5.438610e-04, &tj, &tj1, &result, _state);
15679 0 : mannwhitneyu_ucheb(x, 6.301363e-04, &tj, &tj1, &result, _state);
15680 0 : mannwhitneyu_ucheb(x, 5.309386e-04, &tj, &tj1, &result, _state);
15681 0 : mannwhitneyu_ucheb(x, 5.164772e-04, &tj, &tj1, &result, _state);
15682 0 : return result;
15683 : }
15684 :
15685 :
15686 : /*************************************************************************
15687 : Tail(S, 9, 30)
15688 : *************************************************************************/
15689 0 : static double mannwhitneyu_utbln9n30(double s, ae_state *_state)
15690 : {
15691 : double x;
15692 : double tj;
15693 : double tj1;
15694 : double result;
15695 :
15696 :
15697 0 : result = (double)(0);
15698 0 : x = ae_minreal(2*(s-0.000000e+00)/3.650000e+00-1, 1.0, _state);
15699 0 : tj = (double)(1);
15700 0 : tj1 = x;
15701 0 : mannwhitneyu_ucheb(x, -4.370720e+00, &tj, &tj1, &result, _state);
15702 0 : mannwhitneyu_ucheb(x, -4.615712e+00, &tj, &tj1, &result, _state);
15703 0 : mannwhitneyu_ucheb(x, -1.050023e+00, &tj, &tj1, &result, _state);
15704 0 : mannwhitneyu_ucheb(x, -1.504775e-01, &tj, &tj1, &result, _state);
15705 0 : mannwhitneyu_ucheb(x, -3.318265e-02, &tj, &tj1, &result, _state);
15706 0 : mannwhitneyu_ucheb(x, -9.646826e-03, &tj, &tj1, &result, _state);
15707 0 : mannwhitneyu_ucheb(x, -2.741492e-03, &tj, &tj1, &result, _state);
15708 0 : mannwhitneyu_ucheb(x, -8.735360e-04, &tj, &tj1, &result, _state);
15709 0 : mannwhitneyu_ucheb(x, -2.966911e-04, &tj, &tj1, &result, _state);
15710 0 : mannwhitneyu_ucheb(x, -1.100738e-04, &tj, &tj1, &result, _state);
15711 0 : mannwhitneyu_ucheb(x, -4.348991e-05, &tj, &tj1, &result, _state);
15712 0 : mannwhitneyu_ucheb(x, -1.527687e-05, &tj, &tj1, &result, _state);
15713 0 : mannwhitneyu_ucheb(x, -2.917286e-06, &tj, &tj1, &result, _state);
15714 0 : mannwhitneyu_ucheb(x, 3.397466e-07, &tj, &tj1, &result, _state);
15715 0 : mannwhitneyu_ucheb(x, -2.360175e-07, &tj, &tj1, &result, _state);
15716 0 : mannwhitneyu_ucheb(x, -9.892252e-07, &tj, &tj1, &result, _state);
15717 0 : return result;
15718 : }
15719 :
15720 :
15721 : /*************************************************************************
15722 : Tail(S, 9, 100)
15723 : *************************************************************************/
15724 0 : static double mannwhitneyu_utbln9n100(double s, ae_state *_state)
15725 : {
15726 : double x;
15727 : double tj;
15728 : double tj1;
15729 : double result;
15730 :
15731 :
15732 0 : result = (double)(0);
15733 0 : x = ae_minreal(2*(s-0.000000e+00)/3.650000e+00-1, 1.0, _state);
15734 0 : tj = (double)(1);
15735 0 : tj1 = x;
15736 0 : mannwhitneyu_ucheb(x, -4.372506e+00, &tj, &tj1, &result, _state);
15737 0 : mannwhitneyu_ucheb(x, -4.590966e+00, &tj, &tj1, &result, _state);
15738 0 : mannwhitneyu_ucheb(x, -1.021758e+00, &tj, &tj1, &result, _state);
15739 0 : mannwhitneyu_ucheb(x, -1.359849e-01, &tj, &tj1, &result, _state);
15740 0 : mannwhitneyu_ucheb(x, -2.755519e-02, &tj, &tj1, &result, _state);
15741 0 : mannwhitneyu_ucheb(x, -7.533166e-03, &tj, &tj1, &result, _state);
15742 0 : mannwhitneyu_ucheb(x, -1.936659e-03, &tj, &tj1, &result, _state);
15743 0 : mannwhitneyu_ucheb(x, -5.634913e-04, &tj, &tj1, &result, _state);
15744 0 : mannwhitneyu_ucheb(x, -1.730053e-04, &tj, &tj1, &result, _state);
15745 0 : mannwhitneyu_ucheb(x, -5.791845e-05, &tj, &tj1, &result, _state);
15746 0 : mannwhitneyu_ucheb(x, -2.030682e-05, &tj, &tj1, &result, _state);
15747 0 : mannwhitneyu_ucheb(x, -5.228663e-06, &tj, &tj1, &result, _state);
15748 0 : mannwhitneyu_ucheb(x, 8.631175e-07, &tj, &tj1, &result, _state);
15749 0 : mannwhitneyu_ucheb(x, 1.636749e-06, &tj, &tj1, &result, _state);
15750 0 : mannwhitneyu_ucheb(x, 4.404599e-07, &tj, &tj1, &result, _state);
15751 0 : mannwhitneyu_ucheb(x, -2.789872e-07, &tj, &tj1, &result, _state);
15752 0 : return result;
15753 : }
15754 :
15755 :
15756 : /*************************************************************************
15757 : Tail(S, 10, 10)
15758 : *************************************************************************/
15759 0 : static double mannwhitneyu_utbln10n10(double s, ae_state *_state)
15760 : {
15761 : double x;
15762 : double tj;
15763 : double tj1;
15764 : double result;
15765 :
15766 :
15767 0 : result = (double)(0);
15768 0 : x = ae_minreal(2*(s-0.000000e+00)/3.650000e+00-1, 1.0, _state);
15769 0 : tj = (double)(1);
15770 0 : tj1 = x;
15771 0 : mannwhitneyu_ucheb(x, -4.468831e+00, &tj, &tj1, &result, _state);
15772 0 : mannwhitneyu_ucheb(x, -4.844398e+00, &tj, &tj1, &result, _state);
15773 0 : mannwhitneyu_ucheb(x, -1.231728e+00, &tj, &tj1, &result, _state);
15774 0 : mannwhitneyu_ucheb(x, -2.486073e-01, &tj, &tj1, &result, _state);
15775 0 : mannwhitneyu_ucheb(x, -7.781321e-02, &tj, &tj1, &result, _state);
15776 0 : mannwhitneyu_ucheb(x, -2.971425e-02, &tj, &tj1, &result, _state);
15777 0 : mannwhitneyu_ucheb(x, -1.215371e-02, &tj, &tj1, &result, _state);
15778 0 : mannwhitneyu_ucheb(x, -5.828451e-03, &tj, &tj1, &result, _state);
15779 0 : mannwhitneyu_ucheb(x, -3.419872e-03, &tj, &tj1, &result, _state);
15780 0 : mannwhitneyu_ucheb(x, -2.430165e-03, &tj, &tj1, &result, _state);
15781 0 : mannwhitneyu_ucheb(x, -1.740363e-03, &tj, &tj1, &result, _state);
15782 0 : mannwhitneyu_ucheb(x, -1.049211e-03, &tj, &tj1, &result, _state);
15783 0 : mannwhitneyu_ucheb(x, -3.269371e-04, &tj, &tj1, &result, _state);
15784 0 : mannwhitneyu_ucheb(x, 2.211393e-04, &tj, &tj1, &result, _state);
15785 0 : mannwhitneyu_ucheb(x, 4.232314e-04, &tj, &tj1, &result, _state);
15786 0 : mannwhitneyu_ucheb(x, 3.016081e-04, &tj, &tj1, &result, _state);
15787 0 : return result;
15788 : }
15789 :
15790 :
15791 : /*************************************************************************
15792 : Tail(S, 10, 11)
15793 : *************************************************************************/
15794 0 : static double mannwhitneyu_utbln10n11(double s, ae_state *_state)
15795 : {
15796 : double x;
15797 : double tj;
15798 : double tj1;
15799 : double result;
15800 :
15801 :
15802 0 : result = (double)(0);
15803 0 : x = ae_minreal(2*(s-0.000000e+00)/3.650000e+00-1, 1.0, _state);
15804 0 : tj = (double)(1);
15805 0 : tj1 = x;
15806 0 : mannwhitneyu_ucheb(x, -4.437998e+00, &tj, &tj1, &result, _state);
15807 0 : mannwhitneyu_ucheb(x, -4.782296e+00, &tj, &tj1, &result, _state);
15808 0 : mannwhitneyu_ucheb(x, -1.184732e+00, &tj, &tj1, &result, _state);
15809 0 : mannwhitneyu_ucheb(x, -2.219585e-01, &tj, &tj1, &result, _state);
15810 0 : mannwhitneyu_ucheb(x, -6.457012e-02, &tj, &tj1, &result, _state);
15811 0 : mannwhitneyu_ucheb(x, -2.296008e-02, &tj, &tj1, &result, _state);
15812 0 : mannwhitneyu_ucheb(x, -8.481501e-03, &tj, &tj1, &result, _state);
15813 0 : mannwhitneyu_ucheb(x, -3.527940e-03, &tj, &tj1, &result, _state);
15814 0 : mannwhitneyu_ucheb(x, -1.953426e-03, &tj, &tj1, &result, _state);
15815 0 : mannwhitneyu_ucheb(x, -1.563840e-03, &tj, &tj1, &result, _state);
15816 0 : mannwhitneyu_ucheb(x, -1.574403e-03, &tj, &tj1, &result, _state);
15817 0 : mannwhitneyu_ucheb(x, -1.535775e-03, &tj, &tj1, &result, _state);
15818 0 : mannwhitneyu_ucheb(x, -1.338037e-03, &tj, &tj1, &result, _state);
15819 0 : mannwhitneyu_ucheb(x, -1.002654e-03, &tj, &tj1, &result, _state);
15820 0 : mannwhitneyu_ucheb(x, -5.852676e-04, &tj, &tj1, &result, _state);
15821 0 : mannwhitneyu_ucheb(x, -3.318132e-04, &tj, &tj1, &result, _state);
15822 0 : return result;
15823 : }
15824 :
15825 :
15826 : /*************************************************************************
15827 : Tail(S, 10, 12)
15828 : *************************************************************************/
15829 0 : static double mannwhitneyu_utbln10n12(double s, ae_state *_state)
15830 : {
15831 : double x;
15832 : double tj;
15833 : double tj1;
15834 : double result;
15835 :
15836 :
15837 0 : result = (double)(0);
15838 0 : x = ae_minreal(2*(s-0.000000e+00)/3.650000e+00-1, 1.0, _state);
15839 0 : tj = (double)(1);
15840 0 : tj1 = x;
15841 0 : mannwhitneyu_ucheb(x, -4.416082e+00, &tj, &tj1, &result, _state);
15842 0 : mannwhitneyu_ucheb(x, -4.737458e+00, &tj, &tj1, &result, _state);
15843 0 : mannwhitneyu_ucheb(x, -1.150952e+00, &tj, &tj1, &result, _state);
15844 0 : mannwhitneyu_ucheb(x, -2.036884e-01, &tj, &tj1, &result, _state);
15845 0 : mannwhitneyu_ucheb(x, -5.609030e-02, &tj, &tj1, &result, _state);
15846 0 : mannwhitneyu_ucheb(x, -1.908684e-02, &tj, &tj1, &result, _state);
15847 0 : mannwhitneyu_ucheb(x, -6.439666e-03, &tj, &tj1, &result, _state);
15848 0 : mannwhitneyu_ucheb(x, -2.162647e-03, &tj, &tj1, &result, _state);
15849 0 : mannwhitneyu_ucheb(x, -6.451601e-04, &tj, &tj1, &result, _state);
15850 0 : mannwhitneyu_ucheb(x, -2.148757e-04, &tj, &tj1, &result, _state);
15851 0 : mannwhitneyu_ucheb(x, -1.803981e-04, &tj, &tj1, &result, _state);
15852 0 : mannwhitneyu_ucheb(x, -2.731621e-04, &tj, &tj1, &result, _state);
15853 0 : mannwhitneyu_ucheb(x, -3.346903e-04, &tj, &tj1, &result, _state);
15854 0 : mannwhitneyu_ucheb(x, -3.013151e-04, &tj, &tj1, &result, _state);
15855 0 : mannwhitneyu_ucheb(x, -1.956148e-04, &tj, &tj1, &result, _state);
15856 0 : mannwhitneyu_ucheb(x, -2.438381e-05, &tj, &tj1, &result, _state);
15857 0 : return result;
15858 : }
15859 :
15860 :
15861 : /*************************************************************************
15862 : Tail(S, 10, 13)
15863 : *************************************************************************/
15864 0 : static double mannwhitneyu_utbln10n13(double s, ae_state *_state)
15865 : {
15866 : double x;
15867 : double tj;
15868 : double tj1;
15869 : double result;
15870 :
15871 :
15872 0 : result = (double)(0);
15873 0 : x = ae_minreal(2*(s-0.000000e+00)/3.650000e+00-1, 1.0, _state);
15874 0 : tj = (double)(1);
15875 0 : tj1 = x;
15876 0 : mannwhitneyu_ucheb(x, -4.399480e+00, &tj, &tj1, &result, _state);
15877 0 : mannwhitneyu_ucheb(x, -4.702863e+00, &tj, &tj1, &result, _state);
15878 0 : mannwhitneyu_ucheb(x, -1.124829e+00, &tj, &tj1, &result, _state);
15879 0 : mannwhitneyu_ucheb(x, -1.897428e-01, &tj, &tj1, &result, _state);
15880 0 : mannwhitneyu_ucheb(x, -4.979802e-02, &tj, &tj1, &result, _state);
15881 0 : mannwhitneyu_ucheb(x, -1.634368e-02, &tj, &tj1, &result, _state);
15882 0 : mannwhitneyu_ucheb(x, -5.180461e-03, &tj, &tj1, &result, _state);
15883 0 : mannwhitneyu_ucheb(x, -1.484926e-03, &tj, &tj1, &result, _state);
15884 0 : mannwhitneyu_ucheb(x, -7.864376e-05, &tj, &tj1, &result, _state);
15885 0 : mannwhitneyu_ucheb(x, 4.186576e-04, &tj, &tj1, &result, _state);
15886 0 : mannwhitneyu_ucheb(x, 5.886925e-04, &tj, &tj1, &result, _state);
15887 0 : mannwhitneyu_ucheb(x, 5.836828e-04, &tj, &tj1, &result, _state);
15888 0 : mannwhitneyu_ucheb(x, 5.074756e-04, &tj, &tj1, &result, _state);
15889 0 : mannwhitneyu_ucheb(x, 4.209547e-04, &tj, &tj1, &result, _state);
15890 0 : mannwhitneyu_ucheb(x, 2.883266e-04, &tj, &tj1, &result, _state);
15891 0 : mannwhitneyu_ucheb(x, 2.380143e-04, &tj, &tj1, &result, _state);
15892 0 : return result;
15893 : }
15894 :
15895 :
15896 : /*************************************************************************
15897 : Tail(S, 10, 14)
15898 : *************************************************************************/
15899 0 : static double mannwhitneyu_utbln10n14(double s, ae_state *_state)
15900 : {
15901 : double x;
15902 : double tj;
15903 : double tj1;
15904 : double result;
15905 :
15906 :
15907 0 : result = (double)(0);
15908 0 : x = ae_minreal(2*(s-0.000000e+00)/3.650000e+00-1, 1.0, _state);
15909 0 : tj = (double)(1);
15910 0 : tj1 = x;
15911 0 : mannwhitneyu_ucheb(x, -4.386924e+00, &tj, &tj1, &result, _state);
15912 0 : mannwhitneyu_ucheb(x, -4.676124e+00, &tj, &tj1, &result, _state);
15913 0 : mannwhitneyu_ucheb(x, -1.104740e+00, &tj, &tj1, &result, _state);
15914 0 : mannwhitneyu_ucheb(x, -1.793826e-01, &tj, &tj1, &result, _state);
15915 0 : mannwhitneyu_ucheb(x, -4.558886e-02, &tj, &tj1, &result, _state);
15916 0 : mannwhitneyu_ucheb(x, -1.492462e-02, &tj, &tj1, &result, _state);
15917 0 : mannwhitneyu_ucheb(x, -5.052903e-03, &tj, &tj1, &result, _state);
15918 0 : mannwhitneyu_ucheb(x, -1.917782e-03, &tj, &tj1, &result, _state);
15919 0 : mannwhitneyu_ucheb(x, -7.878696e-04, &tj, &tj1, &result, _state);
15920 0 : mannwhitneyu_ucheb(x, -3.576046e-04, &tj, &tj1, &result, _state);
15921 0 : mannwhitneyu_ucheb(x, -1.764551e-04, &tj, &tj1, &result, _state);
15922 0 : mannwhitneyu_ucheb(x, -9.288778e-05, &tj, &tj1, &result, _state);
15923 0 : mannwhitneyu_ucheb(x, -4.757658e-05, &tj, &tj1, &result, _state);
15924 0 : mannwhitneyu_ucheb(x, -2.299101e-05, &tj, &tj1, &result, _state);
15925 0 : mannwhitneyu_ucheb(x, -9.265197e-06, &tj, &tj1, &result, _state);
15926 0 : mannwhitneyu_ucheb(x, -2.384503e-07, &tj, &tj1, &result, _state);
15927 0 : return result;
15928 : }
15929 :
15930 :
15931 : /*************************************************************************
15932 : Tail(S, 10, 15)
15933 : *************************************************************************/
15934 0 : static double mannwhitneyu_utbln10n15(double s, ae_state *_state)
15935 : {
15936 : double x;
15937 : double tj;
15938 : double tj1;
15939 : double result;
15940 :
15941 :
15942 0 : result = (double)(0);
15943 0 : x = ae_minreal(2*(s-0.000000e+00)/3.650000e+00-1, 1.0, _state);
15944 0 : tj = (double)(1);
15945 0 : tj1 = x;
15946 0 : mannwhitneyu_ucheb(x, -4.376846e+00, &tj, &tj1, &result, _state);
15947 0 : mannwhitneyu_ucheb(x, -4.654247e+00, &tj, &tj1, &result, _state);
15948 0 : mannwhitneyu_ucheb(x, -1.088083e+00, &tj, &tj1, &result, _state);
15949 0 : mannwhitneyu_ucheb(x, -1.705945e-01, &tj, &tj1, &result, _state);
15950 0 : mannwhitneyu_ucheb(x, -4.169677e-02, &tj, &tj1, &result, _state);
15951 0 : mannwhitneyu_ucheb(x, -1.317213e-02, &tj, &tj1, &result, _state);
15952 0 : mannwhitneyu_ucheb(x, -4.264836e-03, &tj, &tj1, &result, _state);
15953 0 : mannwhitneyu_ucheb(x, -1.548024e-03, &tj, &tj1, &result, _state);
15954 0 : mannwhitneyu_ucheb(x, -6.633910e-04, &tj, &tj1, &result, _state);
15955 0 : mannwhitneyu_ucheb(x, -3.505621e-04, &tj, &tj1, &result, _state);
15956 0 : mannwhitneyu_ucheb(x, -2.658588e-04, &tj, &tj1, &result, _state);
15957 0 : mannwhitneyu_ucheb(x, -2.320254e-04, &tj, &tj1, &result, _state);
15958 0 : mannwhitneyu_ucheb(x, -2.175277e-04, &tj, &tj1, &result, _state);
15959 0 : mannwhitneyu_ucheb(x, -2.122317e-04, &tj, &tj1, &result, _state);
15960 0 : mannwhitneyu_ucheb(x, -1.675688e-04, &tj, &tj1, &result, _state);
15961 0 : mannwhitneyu_ucheb(x, -1.661363e-04, &tj, &tj1, &result, _state);
15962 0 : return result;
15963 : }
15964 :
15965 :
15966 : /*************************************************************************
15967 : Tail(S, 10, 30)
15968 : *************************************************************************/
15969 0 : static double mannwhitneyu_utbln10n30(double s, ae_state *_state)
15970 : {
15971 : double x;
15972 : double tj;
15973 : double tj1;
15974 : double result;
15975 :
15976 :
15977 0 : result = (double)(0);
15978 0 : x = ae_minreal(2*(s-0.000000e+00)/3.650000e+00-1, 1.0, _state);
15979 0 : tj = (double)(1);
15980 0 : tj1 = x;
15981 0 : mannwhitneyu_ucheb(x, -4.333977e+00, &tj, &tj1, &result, _state);
15982 0 : mannwhitneyu_ucheb(x, -4.548099e+00, &tj, &tj1, &result, _state);
15983 0 : mannwhitneyu_ucheb(x, -1.004444e+00, &tj, &tj1, &result, _state);
15984 0 : mannwhitneyu_ucheb(x, -1.291014e-01, &tj, &tj1, &result, _state);
15985 0 : mannwhitneyu_ucheb(x, -2.523674e-02, &tj, &tj1, &result, _state);
15986 0 : mannwhitneyu_ucheb(x, -6.828211e-03, &tj, &tj1, &result, _state);
15987 0 : mannwhitneyu_ucheb(x, -1.716917e-03, &tj, &tj1, &result, _state);
15988 0 : mannwhitneyu_ucheb(x, -4.894256e-04, &tj, &tj1, &result, _state);
15989 0 : mannwhitneyu_ucheb(x, -1.433371e-04, &tj, &tj1, &result, _state);
15990 0 : mannwhitneyu_ucheb(x, -4.522675e-05, &tj, &tj1, &result, _state);
15991 0 : mannwhitneyu_ucheb(x, -1.764192e-05, &tj, &tj1, &result, _state);
15992 0 : mannwhitneyu_ucheb(x, -9.140235e-06, &tj, &tj1, &result, _state);
15993 0 : mannwhitneyu_ucheb(x, -5.629230e-06, &tj, &tj1, &result, _state);
15994 0 : mannwhitneyu_ucheb(x, -3.541895e-06, &tj, &tj1, &result, _state);
15995 0 : mannwhitneyu_ucheb(x, -1.944946e-06, &tj, &tj1, &result, _state);
15996 0 : mannwhitneyu_ucheb(x, -1.726360e-06, &tj, &tj1, &result, _state);
15997 0 : return result;
15998 : }
15999 :
16000 :
16001 : /*************************************************************************
16002 : Tail(S, 10, 100)
16003 : *************************************************************************/
16004 0 : static double mannwhitneyu_utbln10n100(double s, ae_state *_state)
16005 : {
16006 : double x;
16007 : double tj;
16008 : double tj1;
16009 : double result;
16010 :
16011 :
16012 0 : result = (double)(0);
16013 0 : x = ae_minreal(2*(s-0.000000e+00)/3.650000e+00-1, 1.0, _state);
16014 0 : tj = (double)(1);
16015 0 : tj1 = x;
16016 0 : mannwhitneyu_ucheb(x, -4.334008e+00, &tj, &tj1, &result, _state);
16017 0 : mannwhitneyu_ucheb(x, -4.522316e+00, &tj, &tj1, &result, _state);
16018 0 : mannwhitneyu_ucheb(x, -9.769627e-01, &tj, &tj1, &result, _state);
16019 0 : mannwhitneyu_ucheb(x, -1.158110e-01, &tj, &tj1, &result, _state);
16020 0 : mannwhitneyu_ucheb(x, -2.053650e-02, &tj, &tj1, &result, _state);
16021 0 : mannwhitneyu_ucheb(x, -5.242235e-03, &tj, &tj1, &result, _state);
16022 0 : mannwhitneyu_ucheb(x, -1.173571e-03, &tj, &tj1, &result, _state);
16023 0 : mannwhitneyu_ucheb(x, -3.033661e-04, &tj, &tj1, &result, _state);
16024 0 : mannwhitneyu_ucheb(x, -7.824732e-05, &tj, &tj1, &result, _state);
16025 0 : mannwhitneyu_ucheb(x, -2.084420e-05, &tj, &tj1, &result, _state);
16026 0 : mannwhitneyu_ucheb(x, -6.610036e-06, &tj, &tj1, &result, _state);
16027 0 : mannwhitneyu_ucheb(x, -2.728155e-06, &tj, &tj1, &result, _state);
16028 0 : mannwhitneyu_ucheb(x, -1.217130e-06, &tj, &tj1, &result, _state);
16029 0 : mannwhitneyu_ucheb(x, -2.340966e-07, &tj, &tj1, &result, _state);
16030 0 : mannwhitneyu_ucheb(x, 2.001235e-07, &tj, &tj1, &result, _state);
16031 0 : mannwhitneyu_ucheb(x, 1.694052e-07, &tj, &tj1, &result, _state);
16032 0 : return result;
16033 : }
16034 :
16035 :
16036 : /*************************************************************************
16037 : Tail(S, 11, 11)
16038 : *************************************************************************/
16039 0 : static double mannwhitneyu_utbln11n11(double s, ae_state *_state)
16040 : {
16041 : double x;
16042 : double tj;
16043 : double tj1;
16044 : double result;
16045 :
16046 :
16047 0 : result = (double)(0);
16048 0 : x = ae_minreal(2*(s-0.000000e+00)/3.700000e+00-1, 1.0, _state);
16049 0 : tj = (double)(1);
16050 0 : tj1 = x;
16051 0 : mannwhitneyu_ucheb(x, -4.519760e+00, &tj, &tj1, &result, _state);
16052 0 : mannwhitneyu_ucheb(x, -4.880694e+00, &tj, &tj1, &result, _state);
16053 0 : mannwhitneyu_ucheb(x, -1.200698e+00, &tj, &tj1, &result, _state);
16054 0 : mannwhitneyu_ucheb(x, -2.174092e-01, &tj, &tj1, &result, _state);
16055 0 : mannwhitneyu_ucheb(x, -6.072304e-02, &tj, &tj1, &result, _state);
16056 0 : mannwhitneyu_ucheb(x, -2.054773e-02, &tj, &tj1, &result, _state);
16057 0 : mannwhitneyu_ucheb(x, -6.506613e-03, &tj, &tj1, &result, _state);
16058 0 : mannwhitneyu_ucheb(x, -1.813942e-03, &tj, &tj1, &result, _state);
16059 0 : mannwhitneyu_ucheb(x, -1.223644e-04, &tj, &tj1, &result, _state);
16060 0 : mannwhitneyu_ucheb(x, 2.417416e-04, &tj, &tj1, &result, _state);
16061 0 : mannwhitneyu_ucheb(x, 2.499166e-04, &tj, &tj1, &result, _state);
16062 0 : mannwhitneyu_ucheb(x, 1.194332e-04, &tj, &tj1, &result, _state);
16063 0 : mannwhitneyu_ucheb(x, 7.369096e-05, &tj, &tj1, &result, _state);
16064 0 : mannwhitneyu_ucheb(x, 1.968590e-04, &tj, &tj1, &result, _state);
16065 0 : mannwhitneyu_ucheb(x, 2.630532e-04, &tj, &tj1, &result, _state);
16066 0 : mannwhitneyu_ucheb(x, 5.061000e-04, &tj, &tj1, &result, _state);
16067 0 : return result;
16068 : }
16069 :
16070 :
16071 : /*************************************************************************
16072 : Tail(S, 11, 12)
16073 : *************************************************************************/
16074 0 : static double mannwhitneyu_utbln11n12(double s, ae_state *_state)
16075 : {
16076 : double x;
16077 : double tj;
16078 : double tj1;
16079 : double result;
16080 :
16081 :
16082 0 : result = (double)(0);
16083 0 : x = ae_minreal(2*(s-0.000000e+00)/3.700000e+00-1, 1.0, _state);
16084 0 : tj = (double)(1);
16085 0 : tj1 = x;
16086 0 : mannwhitneyu_ucheb(x, -4.495790e+00, &tj, &tj1, &result, _state);
16087 0 : mannwhitneyu_ucheb(x, -4.832622e+00, &tj, &tj1, &result, _state);
16088 0 : mannwhitneyu_ucheb(x, -1.165420e+00, &tj, &tj1, &result, _state);
16089 0 : mannwhitneyu_ucheb(x, -1.987306e-01, &tj, &tj1, &result, _state);
16090 0 : mannwhitneyu_ucheb(x, -5.265621e-02, &tj, &tj1, &result, _state);
16091 0 : mannwhitneyu_ucheb(x, -1.723537e-02, &tj, &tj1, &result, _state);
16092 0 : mannwhitneyu_ucheb(x, -5.347406e-03, &tj, &tj1, &result, _state);
16093 0 : mannwhitneyu_ucheb(x, -1.353464e-03, &tj, &tj1, &result, _state);
16094 0 : mannwhitneyu_ucheb(x, 6.613369e-05, &tj, &tj1, &result, _state);
16095 0 : mannwhitneyu_ucheb(x, 5.102522e-04, &tj, &tj1, &result, _state);
16096 0 : mannwhitneyu_ucheb(x, 5.237709e-04, &tj, &tj1, &result, _state);
16097 0 : mannwhitneyu_ucheb(x, 3.665652e-04, &tj, &tj1, &result, _state);
16098 0 : mannwhitneyu_ucheb(x, 1.626903e-04, &tj, &tj1, &result, _state);
16099 0 : mannwhitneyu_ucheb(x, -1.167518e-05, &tj, &tj1, &result, _state);
16100 0 : mannwhitneyu_ucheb(x, -8.564455e-05, &tj, &tj1, &result, _state);
16101 0 : mannwhitneyu_ucheb(x, -1.047320e-04, &tj, &tj1, &result, _state);
16102 0 : return result;
16103 : }
16104 :
16105 :
16106 : /*************************************************************************
16107 : Tail(S, 11, 13)
16108 : *************************************************************************/
16109 0 : static double mannwhitneyu_utbln11n13(double s, ae_state *_state)
16110 : {
16111 : double x;
16112 : double tj;
16113 : double tj1;
16114 : double result;
16115 :
16116 :
16117 0 : result = (double)(0);
16118 0 : x = ae_minreal(2*(s-0.000000e+00)/3.700000e+00-1, 1.0, _state);
16119 0 : tj = (double)(1);
16120 0 : tj1 = x;
16121 0 : mannwhitneyu_ucheb(x, -4.477880e+00, &tj, &tj1, &result, _state);
16122 0 : mannwhitneyu_ucheb(x, -4.796242e+00, &tj, &tj1, &result, _state);
16123 0 : mannwhitneyu_ucheb(x, -1.138769e+00, &tj, &tj1, &result, _state);
16124 0 : mannwhitneyu_ucheb(x, -1.851739e-01, &tj, &tj1, &result, _state);
16125 0 : mannwhitneyu_ucheb(x, -4.722104e-02, &tj, &tj1, &result, _state);
16126 0 : mannwhitneyu_ucheb(x, -1.548304e-02, &tj, &tj1, &result, _state);
16127 0 : mannwhitneyu_ucheb(x, -5.176683e-03, &tj, &tj1, &result, _state);
16128 0 : mannwhitneyu_ucheb(x, -1.817895e-03, &tj, &tj1, &result, _state);
16129 0 : mannwhitneyu_ucheb(x, -5.842451e-04, &tj, &tj1, &result, _state);
16130 0 : mannwhitneyu_ucheb(x, -8.935870e-05, &tj, &tj1, &result, _state);
16131 0 : mannwhitneyu_ucheb(x, 8.421777e-05, &tj, &tj1, &result, _state);
16132 0 : mannwhitneyu_ucheb(x, 1.238831e-04, &tj, &tj1, &result, _state);
16133 0 : mannwhitneyu_ucheb(x, 8.867026e-05, &tj, &tj1, &result, _state);
16134 0 : mannwhitneyu_ucheb(x, 1.458255e-05, &tj, &tj1, &result, _state);
16135 0 : mannwhitneyu_ucheb(x, -3.306259e-05, &tj, &tj1, &result, _state);
16136 0 : mannwhitneyu_ucheb(x, -8.961487e-05, &tj, &tj1, &result, _state);
16137 0 : return result;
16138 : }
16139 :
16140 :
16141 : /*************************************************************************
16142 : Tail(S, 11, 14)
16143 : *************************************************************************/
16144 0 : static double mannwhitneyu_utbln11n14(double s, ae_state *_state)
16145 : {
16146 : double x;
16147 : double tj;
16148 : double tj1;
16149 : double result;
16150 :
16151 :
16152 0 : result = (double)(0);
16153 0 : x = ae_minreal(2*(s-0.000000e+00)/3.700000e+00-1, 1.0, _state);
16154 0 : tj = (double)(1);
16155 0 : tj1 = x;
16156 0 : mannwhitneyu_ucheb(x, -4.463683e+00, &tj, &tj1, &result, _state);
16157 0 : mannwhitneyu_ucheb(x, -4.766969e+00, &tj, &tj1, &result, _state);
16158 0 : mannwhitneyu_ucheb(x, -1.117082e+00, &tj, &tj1, &result, _state);
16159 0 : mannwhitneyu_ucheb(x, -1.739574e-01, &tj, &tj1, &result, _state);
16160 0 : mannwhitneyu_ucheb(x, -4.238865e-02, &tj, &tj1, &result, _state);
16161 0 : mannwhitneyu_ucheb(x, -1.350306e-02, &tj, &tj1, &result, _state);
16162 0 : mannwhitneyu_ucheb(x, -4.425871e-03, &tj, &tj1, &result, _state);
16163 0 : mannwhitneyu_ucheb(x, -1.640172e-03, &tj, &tj1, &result, _state);
16164 0 : mannwhitneyu_ucheb(x, -6.660633e-04, &tj, &tj1, &result, _state);
16165 0 : mannwhitneyu_ucheb(x, -2.879883e-04, &tj, &tj1, &result, _state);
16166 0 : mannwhitneyu_ucheb(x, -1.349658e-04, &tj, &tj1, &result, _state);
16167 0 : mannwhitneyu_ucheb(x, -6.271795e-05, &tj, &tj1, &result, _state);
16168 0 : mannwhitneyu_ucheb(x, -3.304544e-05, &tj, &tj1, &result, _state);
16169 0 : mannwhitneyu_ucheb(x, -3.024201e-05, &tj, &tj1, &result, _state);
16170 0 : mannwhitneyu_ucheb(x, -2.816867e-05, &tj, &tj1, &result, _state);
16171 0 : mannwhitneyu_ucheb(x, -4.596787e-05, &tj, &tj1, &result, _state);
16172 0 : return result;
16173 : }
16174 :
16175 :
16176 : /*************************************************************************
16177 : Tail(S, 11, 15)
16178 : *************************************************************************/
16179 0 : static double mannwhitneyu_utbln11n15(double s, ae_state *_state)
16180 : {
16181 : double x;
16182 : double tj;
16183 : double tj1;
16184 : double result;
16185 :
16186 :
16187 0 : result = (double)(0);
16188 0 : x = ae_minreal(2*(s-0.000000e+00)/3.700000e+00-1, 1.0, _state);
16189 0 : tj = (double)(1);
16190 0 : tj1 = x;
16191 0 : mannwhitneyu_ucheb(x, -4.452526e+00, &tj, &tj1, &result, _state);
16192 0 : mannwhitneyu_ucheb(x, -4.743570e+00, &tj, &tj1, &result, _state);
16193 0 : mannwhitneyu_ucheb(x, -1.099705e+00, &tj, &tj1, &result, _state);
16194 0 : mannwhitneyu_ucheb(x, -1.650612e-01, &tj, &tj1, &result, _state);
16195 0 : mannwhitneyu_ucheb(x, -3.858285e-02, &tj, &tj1, &result, _state);
16196 0 : mannwhitneyu_ucheb(x, -1.187036e-02, &tj, &tj1, &result, _state);
16197 0 : mannwhitneyu_ucheb(x, -3.689241e-03, &tj, &tj1, &result, _state);
16198 0 : mannwhitneyu_ucheb(x, -1.294360e-03, &tj, &tj1, &result, _state);
16199 0 : mannwhitneyu_ucheb(x, -5.072623e-04, &tj, &tj1, &result, _state);
16200 0 : mannwhitneyu_ucheb(x, -2.278008e-04, &tj, &tj1, &result, _state);
16201 0 : mannwhitneyu_ucheb(x, -1.322382e-04, &tj, &tj1, &result, _state);
16202 0 : mannwhitneyu_ucheb(x, -9.131558e-05, &tj, &tj1, &result, _state);
16203 0 : mannwhitneyu_ucheb(x, -7.305669e-05, &tj, &tj1, &result, _state);
16204 0 : mannwhitneyu_ucheb(x, -6.825627e-05, &tj, &tj1, &result, _state);
16205 0 : mannwhitneyu_ucheb(x, -5.332689e-05, &tj, &tj1, &result, _state);
16206 0 : mannwhitneyu_ucheb(x, -6.120973e-05, &tj, &tj1, &result, _state);
16207 0 : return result;
16208 : }
16209 :
16210 :
16211 : /*************************************************************************
16212 : Tail(S, 11, 30)
16213 : *************************************************************************/
16214 0 : static double mannwhitneyu_utbln11n30(double s, ae_state *_state)
16215 : {
16216 : double x;
16217 : double tj;
16218 : double tj1;
16219 : double result;
16220 :
16221 :
16222 0 : result = (double)(0);
16223 0 : x = ae_minreal(2*(s-0.000000e+00)/3.700000e+00-1, 1.0, _state);
16224 0 : tj = (double)(1);
16225 0 : tj1 = x;
16226 0 : mannwhitneyu_ucheb(x, -4.402621e+00, &tj, &tj1, &result, _state);
16227 0 : mannwhitneyu_ucheb(x, -4.627440e+00, &tj, &tj1, &result, _state);
16228 0 : mannwhitneyu_ucheb(x, -1.011333e+00, &tj, &tj1, &result, _state);
16229 0 : mannwhitneyu_ucheb(x, -1.224126e-01, &tj, &tj1, &result, _state);
16230 0 : mannwhitneyu_ucheb(x, -2.232856e-02, &tj, &tj1, &result, _state);
16231 0 : mannwhitneyu_ucheb(x, -5.859347e-03, &tj, &tj1, &result, _state);
16232 0 : mannwhitneyu_ucheb(x, -1.377381e-03, &tj, &tj1, &result, _state);
16233 0 : mannwhitneyu_ucheb(x, -3.756709e-04, &tj, &tj1, &result, _state);
16234 0 : mannwhitneyu_ucheb(x, -1.033230e-04, &tj, &tj1, &result, _state);
16235 0 : mannwhitneyu_ucheb(x, -2.875472e-05, &tj, &tj1, &result, _state);
16236 0 : mannwhitneyu_ucheb(x, -8.608399e-06, &tj, &tj1, &result, _state);
16237 0 : mannwhitneyu_ucheb(x, -3.102943e-06, &tj, &tj1, &result, _state);
16238 0 : mannwhitneyu_ucheb(x, -1.740693e-06, &tj, &tj1, &result, _state);
16239 0 : mannwhitneyu_ucheb(x, -1.343139e-06, &tj, &tj1, &result, _state);
16240 0 : mannwhitneyu_ucheb(x, -9.196878e-07, &tj, &tj1, &result, _state);
16241 0 : mannwhitneyu_ucheb(x, -6.658062e-07, &tj, &tj1, &result, _state);
16242 0 : return result;
16243 : }
16244 :
16245 :
16246 : /*************************************************************************
16247 : Tail(S, 11, 100)
16248 : *************************************************************************/
16249 0 : static double mannwhitneyu_utbln11n100(double s, ae_state *_state)
16250 : {
16251 : double x;
16252 : double tj;
16253 : double tj1;
16254 : double result;
16255 :
16256 :
16257 0 : result = (double)(0);
16258 0 : x = ae_minreal(2*(s-0.000000e+00)/3.700000e+00-1, 1.0, _state);
16259 0 : tj = (double)(1);
16260 0 : tj1 = x;
16261 0 : mannwhitneyu_ucheb(x, -4.398795e+00, &tj, &tj1, &result, _state);
16262 0 : mannwhitneyu_ucheb(x, -4.596486e+00, &tj, &tj1, &result, _state);
16263 0 : mannwhitneyu_ucheb(x, -9.814761e-01, &tj, &tj1, &result, _state);
16264 0 : mannwhitneyu_ucheb(x, -1.085187e-01, &tj, &tj1, &result, _state);
16265 0 : mannwhitneyu_ucheb(x, -1.766529e-02, &tj, &tj1, &result, _state);
16266 0 : mannwhitneyu_ucheb(x, -4.379425e-03, &tj, &tj1, &result, _state);
16267 0 : mannwhitneyu_ucheb(x, -8.986351e-04, &tj, &tj1, &result, _state);
16268 0 : mannwhitneyu_ucheb(x, -2.214705e-04, &tj, &tj1, &result, _state);
16269 0 : mannwhitneyu_ucheb(x, -5.360075e-05, &tj, &tj1, &result, _state);
16270 0 : mannwhitneyu_ucheb(x, -1.260869e-05, &tj, &tj1, &result, _state);
16271 0 : mannwhitneyu_ucheb(x, -3.033307e-06, &tj, &tj1, &result, _state);
16272 0 : mannwhitneyu_ucheb(x, -7.727087e-07, &tj, &tj1, &result, _state);
16273 0 : mannwhitneyu_ucheb(x, -3.393883e-07, &tj, &tj1, &result, _state);
16274 0 : mannwhitneyu_ucheb(x, -2.242989e-07, &tj, &tj1, &result, _state);
16275 0 : mannwhitneyu_ucheb(x, -1.111928e-07, &tj, &tj1, &result, _state);
16276 0 : mannwhitneyu_ucheb(x, 3.898823e-09, &tj, &tj1, &result, _state);
16277 0 : return result;
16278 : }
16279 :
16280 :
16281 : /*************************************************************************
16282 : Tail(S, 12, 12)
16283 : *************************************************************************/
16284 0 : static double mannwhitneyu_utbln12n12(double s, ae_state *_state)
16285 : {
16286 : double x;
16287 : double tj;
16288 : double tj1;
16289 : double result;
16290 :
16291 :
16292 0 : result = (double)(0);
16293 0 : x = ae_minreal(2*(s-0.000000e+00)/3.700000e+00-1, 1.0, _state);
16294 0 : tj = (double)(1);
16295 0 : tj1 = x;
16296 0 : mannwhitneyu_ucheb(x, -4.472616e+00, &tj, &tj1, &result, _state);
16297 0 : mannwhitneyu_ucheb(x, -4.786627e+00, &tj, &tj1, &result, _state);
16298 0 : mannwhitneyu_ucheb(x, -1.132099e+00, &tj, &tj1, &result, _state);
16299 0 : mannwhitneyu_ucheb(x, -1.817523e-01, &tj, &tj1, &result, _state);
16300 0 : mannwhitneyu_ucheb(x, -4.570179e-02, &tj, &tj1, &result, _state);
16301 0 : mannwhitneyu_ucheb(x, -1.479511e-02, &tj, &tj1, &result, _state);
16302 0 : mannwhitneyu_ucheb(x, -4.799492e-03, &tj, &tj1, &result, _state);
16303 0 : mannwhitneyu_ucheb(x, -1.565350e-03, &tj, &tj1, &result, _state);
16304 0 : mannwhitneyu_ucheb(x, -3.530139e-04, &tj, &tj1, &result, _state);
16305 0 : mannwhitneyu_ucheb(x, 1.380132e-04, &tj, &tj1, &result, _state);
16306 0 : mannwhitneyu_ucheb(x, 3.242761e-04, &tj, &tj1, &result, _state);
16307 0 : mannwhitneyu_ucheb(x, 3.576269e-04, &tj, &tj1, &result, _state);
16308 0 : mannwhitneyu_ucheb(x, 3.018771e-04, &tj, &tj1, &result, _state);
16309 0 : mannwhitneyu_ucheb(x, 1.933911e-04, &tj, &tj1, &result, _state);
16310 0 : mannwhitneyu_ucheb(x, 9.002799e-05, &tj, &tj1, &result, _state);
16311 0 : mannwhitneyu_ucheb(x, -2.022048e-06, &tj, &tj1, &result, _state);
16312 0 : return result;
16313 : }
16314 :
16315 :
16316 : /*************************************************************************
16317 : Tail(S, 12, 13)
16318 : *************************************************************************/
16319 0 : static double mannwhitneyu_utbln12n13(double s, ae_state *_state)
16320 : {
16321 : double x;
16322 : double tj;
16323 : double tj1;
16324 : double result;
16325 :
16326 :
16327 0 : result = (double)(0);
16328 0 : x = ae_minreal(2*(s-0.000000e+00)/3.700000e+00-1, 1.0, _state);
16329 0 : tj = (double)(1);
16330 0 : tj1 = x;
16331 0 : mannwhitneyu_ucheb(x, -4.454800e+00, &tj, &tj1, &result, _state);
16332 0 : mannwhitneyu_ucheb(x, -4.750794e+00, &tj, &tj1, &result, _state);
16333 0 : mannwhitneyu_ucheb(x, -1.105988e+00, &tj, &tj1, &result, _state);
16334 0 : mannwhitneyu_ucheb(x, -1.684754e-01, &tj, &tj1, &result, _state);
16335 0 : mannwhitneyu_ucheb(x, -4.011826e-02, &tj, &tj1, &result, _state);
16336 0 : mannwhitneyu_ucheb(x, -1.262579e-02, &tj, &tj1, &result, _state);
16337 0 : mannwhitneyu_ucheb(x, -4.044492e-03, &tj, &tj1, &result, _state);
16338 0 : mannwhitneyu_ucheb(x, -1.478741e-03, &tj, &tj1, &result, _state);
16339 0 : mannwhitneyu_ucheb(x, -5.322165e-04, &tj, &tj1, &result, _state);
16340 0 : mannwhitneyu_ucheb(x, -1.621104e-04, &tj, &tj1, &result, _state);
16341 0 : mannwhitneyu_ucheb(x, 4.068753e-05, &tj, &tj1, &result, _state);
16342 0 : mannwhitneyu_ucheb(x, 1.468396e-04, &tj, &tj1, &result, _state);
16343 0 : mannwhitneyu_ucheb(x, 2.056235e-04, &tj, &tj1, &result, _state);
16344 0 : mannwhitneyu_ucheb(x, 2.327375e-04, &tj, &tj1, &result, _state);
16345 0 : mannwhitneyu_ucheb(x, 1.914877e-04, &tj, &tj1, &result, _state);
16346 0 : mannwhitneyu_ucheb(x, 1.784191e-04, &tj, &tj1, &result, _state);
16347 0 : return result;
16348 : }
16349 :
16350 :
16351 : /*************************************************************************
16352 : Tail(S, 12, 14)
16353 : *************************************************************************/
16354 0 : static double mannwhitneyu_utbln12n14(double s, ae_state *_state)
16355 : {
16356 : double x;
16357 : double tj;
16358 : double tj1;
16359 : double result;
16360 :
16361 :
16362 0 : result = (double)(0);
16363 0 : x = ae_minreal(2*(s-0.000000e+00)/3.700000e+00-1, 1.0, _state);
16364 0 : tj = (double)(1);
16365 0 : tj1 = x;
16366 0 : mannwhitneyu_ucheb(x, -4.440910e+00, &tj, &tj1, &result, _state);
16367 0 : mannwhitneyu_ucheb(x, -4.722404e+00, &tj, &tj1, &result, _state);
16368 0 : mannwhitneyu_ucheb(x, -1.085254e+00, &tj, &tj1, &result, _state);
16369 0 : mannwhitneyu_ucheb(x, -1.579439e-01, &tj, &tj1, &result, _state);
16370 0 : mannwhitneyu_ucheb(x, -3.563738e-02, &tj, &tj1, &result, _state);
16371 0 : mannwhitneyu_ucheb(x, -1.066730e-02, &tj, &tj1, &result, _state);
16372 0 : mannwhitneyu_ucheb(x, -3.129346e-03, &tj, &tj1, &result, _state);
16373 0 : mannwhitneyu_ucheb(x, -1.014531e-03, &tj, &tj1, &result, _state);
16374 0 : mannwhitneyu_ucheb(x, -3.129679e-04, &tj, &tj1, &result, _state);
16375 0 : mannwhitneyu_ucheb(x, -8.000909e-05, &tj, &tj1, &result, _state);
16376 0 : mannwhitneyu_ucheb(x, 1.996174e-05, &tj, &tj1, &result, _state);
16377 0 : mannwhitneyu_ucheb(x, 6.377924e-05, &tj, &tj1, &result, _state);
16378 0 : mannwhitneyu_ucheb(x, 8.936304e-05, &tj, &tj1, &result, _state);
16379 0 : mannwhitneyu_ucheb(x, 1.051098e-04, &tj, &tj1, &result, _state);
16380 0 : mannwhitneyu_ucheb(x, 9.025820e-05, &tj, &tj1, &result, _state);
16381 0 : mannwhitneyu_ucheb(x, 8.730585e-05, &tj, &tj1, &result, _state);
16382 0 : return result;
16383 : }
16384 :
16385 :
16386 : /*************************************************************************
16387 : Tail(S, 12, 15)
16388 : *************************************************************************/
16389 0 : static double mannwhitneyu_utbln12n15(double s, ae_state *_state)
16390 : {
16391 : double x;
16392 : double tj;
16393 : double tj1;
16394 : double result;
16395 :
16396 :
16397 0 : result = (double)(0);
16398 0 : x = ae_minreal(2*(s-0.000000e+00)/3.700000e+00-1, 1.0, _state);
16399 0 : tj = (double)(1);
16400 0 : tj1 = x;
16401 0 : mannwhitneyu_ucheb(x, -4.430123e+00, &tj, &tj1, &result, _state);
16402 0 : mannwhitneyu_ucheb(x, -4.700008e+00, &tj, &tj1, &result, _state);
16403 0 : mannwhitneyu_ucheb(x, -1.068971e+00, &tj, &tj1, &result, _state);
16404 0 : mannwhitneyu_ucheb(x, -1.499725e-01, &tj, &tj1, &result, _state);
16405 0 : mannwhitneyu_ucheb(x, -3.250897e-02, &tj, &tj1, &result, _state);
16406 0 : mannwhitneyu_ucheb(x, -9.473145e-03, &tj, &tj1, &result, _state);
16407 0 : mannwhitneyu_ucheb(x, -2.680008e-03, &tj, &tj1, &result, _state);
16408 0 : mannwhitneyu_ucheb(x, -8.483350e-04, &tj, &tj1, &result, _state);
16409 0 : mannwhitneyu_ucheb(x, -2.766992e-04, &tj, &tj1, &result, _state);
16410 0 : mannwhitneyu_ucheb(x, -9.891081e-05, &tj, &tj1, &result, _state);
16411 0 : mannwhitneyu_ucheb(x, -4.015140e-05, &tj, &tj1, &result, _state);
16412 0 : mannwhitneyu_ucheb(x, -1.977756e-05, &tj, &tj1, &result, _state);
16413 0 : mannwhitneyu_ucheb(x, -8.707414e-06, &tj, &tj1, &result, _state);
16414 0 : mannwhitneyu_ucheb(x, 1.114786e-06, &tj, &tj1, &result, _state);
16415 0 : mannwhitneyu_ucheb(x, 6.238865e-06, &tj, &tj1, &result, _state);
16416 0 : mannwhitneyu_ucheb(x, 1.381445e-05, &tj, &tj1, &result, _state);
16417 0 : return result;
16418 : }
16419 :
16420 :
16421 : /*************************************************************************
16422 : Tail(S, 12, 30)
16423 : *************************************************************************/
16424 0 : static double mannwhitneyu_utbln12n30(double s, ae_state *_state)
16425 : {
16426 : double x;
16427 : double tj;
16428 : double tj1;
16429 : double result;
16430 :
16431 :
16432 0 : result = (double)(0);
16433 0 : x = ae_minreal(2*(s-0.000000e+00)/3.700000e+00-1, 1.0, _state);
16434 0 : tj = (double)(1);
16435 0 : tj1 = x;
16436 0 : mannwhitneyu_ucheb(x, -4.380023e+00, &tj, &tj1, &result, _state);
16437 0 : mannwhitneyu_ucheb(x, -4.585782e+00, &tj, &tj1, &result, _state);
16438 0 : mannwhitneyu_ucheb(x, -9.838583e-01, &tj, &tj1, &result, _state);
16439 0 : mannwhitneyu_ucheb(x, -1.103394e-01, &tj, &tj1, &result, _state);
16440 0 : mannwhitneyu_ucheb(x, -1.834015e-02, &tj, &tj1, &result, _state);
16441 0 : mannwhitneyu_ucheb(x, -4.635212e-03, &tj, &tj1, &result, _state);
16442 0 : mannwhitneyu_ucheb(x, -9.948212e-04, &tj, &tj1, &result, _state);
16443 0 : mannwhitneyu_ucheb(x, -2.574169e-04, &tj, &tj1, &result, _state);
16444 0 : mannwhitneyu_ucheb(x, -6.747980e-05, &tj, &tj1, &result, _state);
16445 0 : mannwhitneyu_ucheb(x, -1.833672e-05, &tj, &tj1, &result, _state);
16446 0 : mannwhitneyu_ucheb(x, -5.722433e-06, &tj, &tj1, &result, _state);
16447 0 : mannwhitneyu_ucheb(x, -2.181038e-06, &tj, &tj1, &result, _state);
16448 0 : mannwhitneyu_ucheb(x, -1.206473e-06, &tj, &tj1, &result, _state);
16449 0 : mannwhitneyu_ucheb(x, -9.716003e-07, &tj, &tj1, &result, _state);
16450 0 : mannwhitneyu_ucheb(x, -7.476434e-07, &tj, &tj1, &result, _state);
16451 0 : mannwhitneyu_ucheb(x, -7.217700e-07, &tj, &tj1, &result, _state);
16452 0 : return result;
16453 : }
16454 :
16455 :
16456 : /*************************************************************************
16457 : Tail(S, 12, 100)
16458 : *************************************************************************/
16459 0 : static double mannwhitneyu_utbln12n100(double s, ae_state *_state)
16460 : {
16461 : double x;
16462 : double tj;
16463 : double tj1;
16464 : double result;
16465 :
16466 :
16467 0 : result = (double)(0);
16468 0 : x = ae_minreal(2*(s-0.000000e+00)/3.700000e+00-1, 1.0, _state);
16469 0 : tj = (double)(1);
16470 0 : tj1 = x;
16471 0 : mannwhitneyu_ucheb(x, -4.374567e+00, &tj, &tj1, &result, _state);
16472 0 : mannwhitneyu_ucheb(x, -4.553481e+00, &tj, &tj1, &result, _state);
16473 0 : mannwhitneyu_ucheb(x, -9.541334e-01, &tj, &tj1, &result, _state);
16474 0 : mannwhitneyu_ucheb(x, -9.701907e-02, &tj, &tj1, &result, _state);
16475 0 : mannwhitneyu_ucheb(x, -1.414757e-02, &tj, &tj1, &result, _state);
16476 0 : mannwhitneyu_ucheb(x, -3.404103e-03, &tj, &tj1, &result, _state);
16477 0 : mannwhitneyu_ucheb(x, -6.234388e-04, &tj, &tj1, &result, _state);
16478 0 : mannwhitneyu_ucheb(x, -1.453762e-04, &tj, &tj1, &result, _state);
16479 0 : mannwhitneyu_ucheb(x, -3.311060e-05, &tj, &tj1, &result, _state);
16480 0 : mannwhitneyu_ucheb(x, -7.317501e-06, &tj, &tj1, &result, _state);
16481 0 : mannwhitneyu_ucheb(x, -1.713888e-06, &tj, &tj1, &result, _state);
16482 0 : mannwhitneyu_ucheb(x, -3.309583e-07, &tj, &tj1, &result, _state);
16483 0 : mannwhitneyu_ucheb(x, -4.019804e-08, &tj, &tj1, &result, _state);
16484 0 : mannwhitneyu_ucheb(x, 1.224829e-09, &tj, &tj1, &result, _state);
16485 0 : mannwhitneyu_ucheb(x, -1.349019e-08, &tj, &tj1, &result, _state);
16486 0 : mannwhitneyu_ucheb(x, -1.893302e-08, &tj, &tj1, &result, _state);
16487 0 : return result;
16488 : }
16489 :
16490 :
16491 : /*************************************************************************
16492 : Tail(S, 13, 13)
16493 : *************************************************************************/
16494 0 : static double mannwhitneyu_utbln13n13(double s, ae_state *_state)
16495 : {
16496 : double x;
16497 : double tj;
16498 : double tj1;
16499 : double result;
16500 :
16501 :
16502 0 : result = (double)(0);
16503 0 : x = ae_minreal(2*(s-0.000000e+00)/3.750000e+00-1, 1.0, _state);
16504 0 : tj = (double)(1);
16505 0 : tj1 = x;
16506 0 : mannwhitneyu_ucheb(x, -4.541046e+00, &tj, &tj1, &result, _state);
16507 0 : mannwhitneyu_ucheb(x, -4.859047e+00, &tj, &tj1, &result, _state);
16508 0 : mannwhitneyu_ucheb(x, -1.130164e+00, &tj, &tj1, &result, _state);
16509 0 : mannwhitneyu_ucheb(x, -1.689719e-01, &tj, &tj1, &result, _state);
16510 0 : mannwhitneyu_ucheb(x, -3.950693e-02, &tj, &tj1, &result, _state);
16511 0 : mannwhitneyu_ucheb(x, -1.231455e-02, &tj, &tj1, &result, _state);
16512 0 : mannwhitneyu_ucheb(x, -3.976550e-03, &tj, &tj1, &result, _state);
16513 0 : mannwhitneyu_ucheb(x, -1.538455e-03, &tj, &tj1, &result, _state);
16514 0 : mannwhitneyu_ucheb(x, -7.245603e-04, &tj, &tj1, &result, _state);
16515 0 : mannwhitneyu_ucheb(x, -4.142647e-04, &tj, &tj1, &result, _state);
16516 0 : mannwhitneyu_ucheb(x, -2.831434e-04, &tj, &tj1, &result, _state);
16517 0 : mannwhitneyu_ucheb(x, -2.032483e-04, &tj, &tj1, &result, _state);
16518 0 : mannwhitneyu_ucheb(x, -1.488405e-04, &tj, &tj1, &result, _state);
16519 0 : mannwhitneyu_ucheb(x, -1.156927e-04, &tj, &tj1, &result, _state);
16520 0 : mannwhitneyu_ucheb(x, -7.949279e-05, &tj, &tj1, &result, _state);
16521 0 : mannwhitneyu_ucheb(x, -7.532700e-05, &tj, &tj1, &result, _state);
16522 0 : return result;
16523 : }
16524 :
16525 :
16526 : /*************************************************************************
16527 : Tail(S, 13, 14)
16528 : *************************************************************************/
16529 0 : static double mannwhitneyu_utbln13n14(double s, ae_state *_state)
16530 : {
16531 : double x;
16532 : double tj;
16533 : double tj1;
16534 : double result;
16535 :
16536 :
16537 0 : result = (double)(0);
16538 0 : x = ae_minreal(2*(s-0.000000e+00)/3.750000e+00-1, 1.0, _state);
16539 0 : tj = (double)(1);
16540 0 : tj1 = x;
16541 0 : mannwhitneyu_ucheb(x, -4.525655e+00, &tj, &tj1, &result, _state);
16542 0 : mannwhitneyu_ucheb(x, -4.828341e+00, &tj, &tj1, &result, _state);
16543 0 : mannwhitneyu_ucheb(x, -1.108110e+00, &tj, &tj1, &result, _state);
16544 0 : mannwhitneyu_ucheb(x, -1.579552e-01, &tj, &tj1, &result, _state);
16545 0 : mannwhitneyu_ucheb(x, -3.488307e-02, &tj, &tj1, &result, _state);
16546 0 : mannwhitneyu_ucheb(x, -1.032328e-02, &tj, &tj1, &result, _state);
16547 0 : mannwhitneyu_ucheb(x, -2.988741e-03, &tj, &tj1, &result, _state);
16548 0 : mannwhitneyu_ucheb(x, -9.766394e-04, &tj, &tj1, &result, _state);
16549 0 : mannwhitneyu_ucheb(x, -3.388950e-04, &tj, &tj1, &result, _state);
16550 0 : mannwhitneyu_ucheb(x, -1.338179e-04, &tj, &tj1, &result, _state);
16551 0 : mannwhitneyu_ucheb(x, -6.133440e-05, &tj, &tj1, &result, _state);
16552 0 : mannwhitneyu_ucheb(x, -3.023518e-05, &tj, &tj1, &result, _state);
16553 0 : mannwhitneyu_ucheb(x, -1.110570e-05, &tj, &tj1, &result, _state);
16554 0 : mannwhitneyu_ucheb(x, 4.202332e-06, &tj, &tj1, &result, _state);
16555 0 : mannwhitneyu_ucheb(x, 1.056132e-05, &tj, &tj1, &result, _state);
16556 0 : mannwhitneyu_ucheb(x, 1.536323e-05, &tj, &tj1, &result, _state);
16557 0 : return result;
16558 : }
16559 :
16560 :
16561 : /*************************************************************************
16562 : Tail(S, 13, 15)
16563 : *************************************************************************/
16564 0 : static double mannwhitneyu_utbln13n15(double s, ae_state *_state)
16565 : {
16566 : double x;
16567 : double tj;
16568 : double tj1;
16569 : double result;
16570 :
16571 :
16572 0 : result = (double)(0);
16573 0 : x = ae_minreal(2*(s-0.000000e+00)/3.750000e+00-1, 1.0, _state);
16574 0 : tj = (double)(1);
16575 0 : tj1 = x;
16576 0 : mannwhitneyu_ucheb(x, -4.513585e+00, &tj, &tj1, &result, _state);
16577 0 : mannwhitneyu_ucheb(x, -4.803952e+00, &tj, &tj1, &result, _state);
16578 0 : mannwhitneyu_ucheb(x, -1.090686e+00, &tj, &tj1, &result, _state);
16579 0 : mannwhitneyu_ucheb(x, -1.495310e-01, &tj, &tj1, &result, _state);
16580 0 : mannwhitneyu_ucheb(x, -3.160314e-02, &tj, &tj1, &result, _state);
16581 0 : mannwhitneyu_ucheb(x, -9.073124e-03, &tj, &tj1, &result, _state);
16582 0 : mannwhitneyu_ucheb(x, -2.480313e-03, &tj, &tj1, &result, _state);
16583 0 : mannwhitneyu_ucheb(x, -7.478239e-04, &tj, &tj1, &result, _state);
16584 0 : mannwhitneyu_ucheb(x, -2.140914e-04, &tj, &tj1, &result, _state);
16585 0 : mannwhitneyu_ucheb(x, -5.311541e-05, &tj, &tj1, &result, _state);
16586 0 : mannwhitneyu_ucheb(x, -2.677105e-06, &tj, &tj1, &result, _state);
16587 0 : mannwhitneyu_ucheb(x, 1.115464e-05, &tj, &tj1, &result, _state);
16588 0 : mannwhitneyu_ucheb(x, 1.578563e-05, &tj, &tj1, &result, _state);
16589 0 : mannwhitneyu_ucheb(x, 2.044604e-05, &tj, &tj1, &result, _state);
16590 0 : mannwhitneyu_ucheb(x, 1.888939e-05, &tj, &tj1, &result, _state);
16591 0 : mannwhitneyu_ucheb(x, 2.395644e-05, &tj, &tj1, &result, _state);
16592 0 : return result;
16593 : }
16594 :
16595 :
16596 : /*************************************************************************
16597 : Tail(S, 13, 30)
16598 : *************************************************************************/
16599 0 : static double mannwhitneyu_utbln13n30(double s, ae_state *_state)
16600 : {
16601 : double x;
16602 : double tj;
16603 : double tj1;
16604 : double result;
16605 :
16606 :
16607 0 : result = (double)(0);
16608 0 : x = ae_minreal(2*(s-0.000000e+00)/3.750000e+00-1, 1.0, _state);
16609 0 : tj = (double)(1);
16610 0 : tj1 = x;
16611 0 : mannwhitneyu_ucheb(x, -4.455999e+00, &tj, &tj1, &result, _state);
16612 0 : mannwhitneyu_ucheb(x, -4.678434e+00, &tj, &tj1, &result, _state);
16613 0 : mannwhitneyu_ucheb(x, -9.995491e-01, &tj, &tj1, &result, _state);
16614 0 : mannwhitneyu_ucheb(x, -1.078100e-01, &tj, &tj1, &result, _state);
16615 0 : mannwhitneyu_ucheb(x, -1.705220e-02, &tj, &tj1, &result, _state);
16616 0 : mannwhitneyu_ucheb(x, -4.258739e-03, &tj, &tj1, &result, _state);
16617 0 : mannwhitneyu_ucheb(x, -8.671526e-04, &tj, &tj1, &result, _state);
16618 0 : mannwhitneyu_ucheb(x, -2.185458e-04, &tj, &tj1, &result, _state);
16619 0 : mannwhitneyu_ucheb(x, -5.507764e-05, &tj, &tj1, &result, _state);
16620 0 : mannwhitneyu_ucheb(x, -1.411446e-05, &tj, &tj1, &result, _state);
16621 0 : mannwhitneyu_ucheb(x, -4.044355e-06, &tj, &tj1, &result, _state);
16622 0 : mannwhitneyu_ucheb(x, -1.285765e-06, &tj, &tj1, &result, _state);
16623 0 : mannwhitneyu_ucheb(x, -5.345282e-07, &tj, &tj1, &result, _state);
16624 0 : mannwhitneyu_ucheb(x, -3.066940e-07, &tj, &tj1, &result, _state);
16625 0 : mannwhitneyu_ucheb(x, -1.962037e-07, &tj, &tj1, &result, _state);
16626 0 : mannwhitneyu_ucheb(x, -1.723644e-07, &tj, &tj1, &result, _state);
16627 0 : return result;
16628 : }
16629 :
16630 :
16631 : /*************************************************************************
16632 : Tail(S, 13, 100)
16633 : *************************************************************************/
16634 0 : static double mannwhitneyu_utbln13n100(double s, ae_state *_state)
16635 : {
16636 : double x;
16637 : double tj;
16638 : double tj1;
16639 : double result;
16640 :
16641 :
16642 0 : result = (double)(0);
16643 0 : x = ae_minreal(2*(s-0.000000e+00)/3.750000e+00-1, 1.0, _state);
16644 0 : tj = (double)(1);
16645 0 : tj1 = x;
16646 0 : mannwhitneyu_ucheb(x, -4.446787e+00, &tj, &tj1, &result, _state);
16647 0 : mannwhitneyu_ucheb(x, -4.640804e+00, &tj, &tj1, &result, _state);
16648 0 : mannwhitneyu_ucheb(x, -9.671552e-01, &tj, &tj1, &result, _state);
16649 0 : mannwhitneyu_ucheb(x, -9.364990e-02, &tj, &tj1, &result, _state);
16650 0 : mannwhitneyu_ucheb(x, -1.274444e-02, &tj, &tj1, &result, _state);
16651 0 : mannwhitneyu_ucheb(x, -3.047440e-03, &tj, &tj1, &result, _state);
16652 0 : mannwhitneyu_ucheb(x, -5.161439e-04, &tj, &tj1, &result, _state);
16653 0 : mannwhitneyu_ucheb(x, -1.171729e-04, &tj, &tj1, &result, _state);
16654 0 : mannwhitneyu_ucheb(x, -2.562171e-05, &tj, &tj1, &result, _state);
16655 0 : mannwhitneyu_ucheb(x, -5.359762e-06, &tj, &tj1, &result, _state);
16656 0 : mannwhitneyu_ucheb(x, -1.275494e-06, &tj, &tj1, &result, _state);
16657 0 : mannwhitneyu_ucheb(x, -2.747635e-07, &tj, &tj1, &result, _state);
16658 0 : mannwhitneyu_ucheb(x, -5.700292e-08, &tj, &tj1, &result, _state);
16659 0 : mannwhitneyu_ucheb(x, -2.565559e-09, &tj, &tj1, &result, _state);
16660 0 : mannwhitneyu_ucheb(x, 5.005396e-09, &tj, &tj1, &result, _state);
16661 0 : mannwhitneyu_ucheb(x, 3.335794e-09, &tj, &tj1, &result, _state);
16662 0 : return result;
16663 : }
16664 :
16665 :
16666 : /*************************************************************************
16667 : Tail(S, 14, 14)
16668 : *************************************************************************/
16669 0 : static double mannwhitneyu_utbln14n14(double s, ae_state *_state)
16670 : {
16671 : double x;
16672 : double tj;
16673 : double tj1;
16674 : double result;
16675 :
16676 :
16677 0 : result = (double)(0);
16678 0 : x = ae_minreal(2*(s-0.000000e+00)/3.750000e+00-1, 1.0, _state);
16679 0 : tj = (double)(1);
16680 0 : tj1 = x;
16681 0 : mannwhitneyu_ucheb(x, -4.510624e+00, &tj, &tj1, &result, _state);
16682 0 : mannwhitneyu_ucheb(x, -4.798584e+00, &tj, &tj1, &result, _state);
16683 0 : mannwhitneyu_ucheb(x, -1.087107e+00, &tj, &tj1, &result, _state);
16684 0 : mannwhitneyu_ucheb(x, -1.478532e-01, &tj, &tj1, &result, _state);
16685 0 : mannwhitneyu_ucheb(x, -3.098050e-02, &tj, &tj1, &result, _state);
16686 0 : mannwhitneyu_ucheb(x, -8.855986e-03, &tj, &tj1, &result, _state);
16687 0 : mannwhitneyu_ucheb(x, -2.409083e-03, &tj, &tj1, &result, _state);
16688 0 : mannwhitneyu_ucheb(x, -7.299536e-04, &tj, &tj1, &result, _state);
16689 0 : mannwhitneyu_ucheb(x, -2.176177e-04, &tj, &tj1, &result, _state);
16690 0 : mannwhitneyu_ucheb(x, -6.479417e-05, &tj, &tj1, &result, _state);
16691 0 : mannwhitneyu_ucheb(x, -1.812761e-05, &tj, &tj1, &result, _state);
16692 0 : mannwhitneyu_ucheb(x, -5.225872e-06, &tj, &tj1, &result, _state);
16693 0 : mannwhitneyu_ucheb(x, 4.516521e-07, &tj, &tj1, &result, _state);
16694 0 : mannwhitneyu_ucheb(x, 6.730551e-06, &tj, &tj1, &result, _state);
16695 0 : mannwhitneyu_ucheb(x, 9.237563e-06, &tj, &tj1, &result, _state);
16696 0 : mannwhitneyu_ucheb(x, 1.611820e-05, &tj, &tj1, &result, _state);
16697 0 : return result;
16698 : }
16699 :
16700 :
16701 : /*************************************************************************
16702 : Tail(S, 14, 15)
16703 : *************************************************************************/
16704 0 : static double mannwhitneyu_utbln14n15(double s, ae_state *_state)
16705 : {
16706 : double x;
16707 : double tj;
16708 : double tj1;
16709 : double result;
16710 :
16711 :
16712 0 : result = (double)(0);
16713 0 : x = ae_minreal(2*(s-0.000000e+00)/3.750000e+00-1, 1.0, _state);
16714 0 : tj = (double)(1);
16715 0 : tj1 = x;
16716 0 : mannwhitneyu_ucheb(x, -4.498681e+00, &tj, &tj1, &result, _state);
16717 0 : mannwhitneyu_ucheb(x, -4.774668e+00, &tj, &tj1, &result, _state);
16718 0 : mannwhitneyu_ucheb(x, -1.070267e+00, &tj, &tj1, &result, _state);
16719 0 : mannwhitneyu_ucheb(x, -1.399348e-01, &tj, &tj1, &result, _state);
16720 0 : mannwhitneyu_ucheb(x, -2.807239e-02, &tj, &tj1, &result, _state);
16721 0 : mannwhitneyu_ucheb(x, -7.845763e-03, &tj, &tj1, &result, _state);
16722 0 : mannwhitneyu_ucheb(x, -2.071773e-03, &tj, &tj1, &result, _state);
16723 0 : mannwhitneyu_ucheb(x, -6.261698e-04, &tj, &tj1, &result, _state);
16724 0 : mannwhitneyu_ucheb(x, -2.011695e-04, &tj, &tj1, &result, _state);
16725 0 : mannwhitneyu_ucheb(x, -7.305946e-05, &tj, &tj1, &result, _state);
16726 0 : mannwhitneyu_ucheb(x, -3.879295e-05, &tj, &tj1, &result, _state);
16727 0 : mannwhitneyu_ucheb(x, -2.999439e-05, &tj, &tj1, &result, _state);
16728 0 : mannwhitneyu_ucheb(x, -2.904438e-05, &tj, &tj1, &result, _state);
16729 0 : mannwhitneyu_ucheb(x, -2.944986e-05, &tj, &tj1, &result, _state);
16730 0 : mannwhitneyu_ucheb(x, -2.373908e-05, &tj, &tj1, &result, _state);
16731 0 : mannwhitneyu_ucheb(x, -2.140794e-05, &tj, &tj1, &result, _state);
16732 0 : return result;
16733 : }
16734 :
16735 :
16736 : /*************************************************************************
16737 : Tail(S, 14, 30)
16738 : *************************************************************************/
16739 0 : static double mannwhitneyu_utbln14n30(double s, ae_state *_state)
16740 : {
16741 : double x;
16742 : double tj;
16743 : double tj1;
16744 : double result;
16745 :
16746 :
16747 0 : result = (double)(0);
16748 0 : x = ae_minreal(2*(s-0.000000e+00)/3.750000e+00-1, 1.0, _state);
16749 0 : tj = (double)(1);
16750 0 : tj1 = x;
16751 0 : mannwhitneyu_ucheb(x, -4.440378e+00, &tj, &tj1, &result, _state);
16752 0 : mannwhitneyu_ucheb(x, -4.649587e+00, &tj, &tj1, &result, _state);
16753 0 : mannwhitneyu_ucheb(x, -9.807829e-01, &tj, &tj1, &result, _state);
16754 0 : mannwhitneyu_ucheb(x, -9.989753e-02, &tj, &tj1, &result, _state);
16755 0 : mannwhitneyu_ucheb(x, -1.463646e-02, &tj, &tj1, &result, _state);
16756 0 : mannwhitneyu_ucheb(x, -3.586580e-03, &tj, &tj1, &result, _state);
16757 0 : mannwhitneyu_ucheb(x, -6.745917e-04, &tj, &tj1, &result, _state);
16758 0 : mannwhitneyu_ucheb(x, -1.635398e-04, &tj, &tj1, &result, _state);
16759 0 : mannwhitneyu_ucheb(x, -3.923172e-05, &tj, &tj1, &result, _state);
16760 0 : mannwhitneyu_ucheb(x, -9.446699e-06, &tj, &tj1, &result, _state);
16761 0 : mannwhitneyu_ucheb(x, -2.613892e-06, &tj, &tj1, &result, _state);
16762 0 : mannwhitneyu_ucheb(x, -8.214073e-07, &tj, &tj1, &result, _state);
16763 0 : mannwhitneyu_ucheb(x, -3.651683e-07, &tj, &tj1, &result, _state);
16764 0 : mannwhitneyu_ucheb(x, -2.272777e-07, &tj, &tj1, &result, _state);
16765 0 : mannwhitneyu_ucheb(x, -1.464988e-07, &tj, &tj1, &result, _state);
16766 0 : mannwhitneyu_ucheb(x, -1.109803e-07, &tj, &tj1, &result, _state);
16767 0 : return result;
16768 : }
16769 :
16770 :
16771 : /*************************************************************************
16772 : Tail(S, 14, 100)
16773 : *************************************************************************/
16774 0 : static double mannwhitneyu_utbln14n100(double s, ae_state *_state)
16775 : {
16776 : double x;
16777 : double tj;
16778 : double tj1;
16779 : double result;
16780 :
16781 :
16782 0 : result = (double)(0);
16783 0 : x = ae_minreal(2*(s-0.000000e+00)/3.750000e+00-1, 1.0, _state);
16784 0 : tj = (double)(1);
16785 0 : tj1 = x;
16786 0 : mannwhitneyu_ucheb(x, -4.429701e+00, &tj, &tj1, &result, _state);
16787 0 : mannwhitneyu_ucheb(x, -4.610577e+00, &tj, &tj1, &result, _state);
16788 0 : mannwhitneyu_ucheb(x, -9.482675e-01, &tj, &tj1, &result, _state);
16789 0 : mannwhitneyu_ucheb(x, -8.605550e-02, &tj, &tj1, &result, _state);
16790 0 : mannwhitneyu_ucheb(x, -1.062151e-02, &tj, &tj1, &result, _state);
16791 0 : mannwhitneyu_ucheb(x, -2.525154e-03, &tj, &tj1, &result, _state);
16792 0 : mannwhitneyu_ucheb(x, -3.835983e-04, &tj, &tj1, &result, _state);
16793 0 : mannwhitneyu_ucheb(x, -8.411440e-05, &tj, &tj1, &result, _state);
16794 0 : mannwhitneyu_ucheb(x, -1.744901e-05, &tj, &tj1, &result, _state);
16795 0 : mannwhitneyu_ucheb(x, -3.318850e-06, &tj, &tj1, &result, _state);
16796 0 : mannwhitneyu_ucheb(x, -7.692100e-07, &tj, &tj1, &result, _state);
16797 0 : mannwhitneyu_ucheb(x, -1.536270e-07, &tj, &tj1, &result, _state);
16798 0 : mannwhitneyu_ucheb(x, -3.705888e-08, &tj, &tj1, &result, _state);
16799 0 : mannwhitneyu_ucheb(x, -7.999599e-09, &tj, &tj1, &result, _state);
16800 0 : mannwhitneyu_ucheb(x, -2.908395e-09, &tj, &tj1, &result, _state);
16801 0 : mannwhitneyu_ucheb(x, 1.546923e-09, &tj, &tj1, &result, _state);
16802 0 : return result;
16803 : }
16804 :
16805 :
16806 : /*************************************************************************
16807 : Tail(S, N1, N2)
16808 : *************************************************************************/
16809 0 : static double mannwhitneyu_usigma(double s,
16810 : ae_int_t n1,
16811 : ae_int_t n2,
16812 : ae_state *_state)
16813 : {
16814 : double f0;
16815 : double f1;
16816 : double f2;
16817 : double f3;
16818 : double f4;
16819 : double s0;
16820 : double s1;
16821 : double s2;
16822 : double s3;
16823 : double s4;
16824 : double result;
16825 :
16826 :
16827 0 : result = (double)(0);
16828 :
16829 : /*
16830 : * N1=5, N2 = 5, 6, 7, ...
16831 : */
16832 0 : if( ae_minint(n1, n2, _state)==5 )
16833 : {
16834 0 : if( ae_maxint(n1, n2, _state)==5 )
16835 : {
16836 0 : result = mannwhitneyu_utbln5n5(s, _state);
16837 : }
16838 0 : if( ae_maxint(n1, n2, _state)==6 )
16839 : {
16840 0 : result = mannwhitneyu_utbln5n6(s, _state);
16841 : }
16842 0 : if( ae_maxint(n1, n2, _state)==7 )
16843 : {
16844 0 : result = mannwhitneyu_utbln5n7(s, _state);
16845 : }
16846 0 : if( ae_maxint(n1, n2, _state)==8 )
16847 : {
16848 0 : result = mannwhitneyu_utbln5n8(s, _state);
16849 : }
16850 0 : if( ae_maxint(n1, n2, _state)==9 )
16851 : {
16852 0 : result = mannwhitneyu_utbln5n9(s, _state);
16853 : }
16854 0 : if( ae_maxint(n1, n2, _state)==10 )
16855 : {
16856 0 : result = mannwhitneyu_utbln5n10(s, _state);
16857 : }
16858 0 : if( ae_maxint(n1, n2, _state)==11 )
16859 : {
16860 0 : result = mannwhitneyu_utbln5n11(s, _state);
16861 : }
16862 0 : if( ae_maxint(n1, n2, _state)==12 )
16863 : {
16864 0 : result = mannwhitneyu_utbln5n12(s, _state);
16865 : }
16866 0 : if( ae_maxint(n1, n2, _state)==13 )
16867 : {
16868 0 : result = mannwhitneyu_utbln5n13(s, _state);
16869 : }
16870 0 : if( ae_maxint(n1, n2, _state)==14 )
16871 : {
16872 0 : result = mannwhitneyu_utbln5n14(s, _state);
16873 : }
16874 0 : if( ae_maxint(n1, n2, _state)==15 )
16875 : {
16876 0 : result = mannwhitneyu_utbln5n15(s, _state);
16877 : }
16878 0 : if( ae_maxint(n1, n2, _state)==16 )
16879 : {
16880 0 : result = mannwhitneyu_utbln5n16(s, _state);
16881 : }
16882 0 : if( ae_maxint(n1, n2, _state)==17 )
16883 : {
16884 0 : result = mannwhitneyu_utbln5n17(s, _state);
16885 : }
16886 0 : if( ae_maxint(n1, n2, _state)==18 )
16887 : {
16888 0 : result = mannwhitneyu_utbln5n18(s, _state);
16889 : }
16890 0 : if( ae_maxint(n1, n2, _state)==19 )
16891 : {
16892 0 : result = mannwhitneyu_utbln5n19(s, _state);
16893 : }
16894 0 : if( ae_maxint(n1, n2, _state)==20 )
16895 : {
16896 0 : result = mannwhitneyu_utbln5n20(s, _state);
16897 : }
16898 0 : if( ae_maxint(n1, n2, _state)==21 )
16899 : {
16900 0 : result = mannwhitneyu_utbln5n21(s, _state);
16901 : }
16902 0 : if( ae_maxint(n1, n2, _state)==22 )
16903 : {
16904 0 : result = mannwhitneyu_utbln5n22(s, _state);
16905 : }
16906 0 : if( ae_maxint(n1, n2, _state)==23 )
16907 : {
16908 0 : result = mannwhitneyu_utbln5n23(s, _state);
16909 : }
16910 0 : if( ae_maxint(n1, n2, _state)==24 )
16911 : {
16912 0 : result = mannwhitneyu_utbln5n24(s, _state);
16913 : }
16914 0 : if( ae_maxint(n1, n2, _state)==25 )
16915 : {
16916 0 : result = mannwhitneyu_utbln5n25(s, _state);
16917 : }
16918 0 : if( ae_maxint(n1, n2, _state)==26 )
16919 : {
16920 0 : result = mannwhitneyu_utbln5n26(s, _state);
16921 : }
16922 0 : if( ae_maxint(n1, n2, _state)==27 )
16923 : {
16924 0 : result = mannwhitneyu_utbln5n27(s, _state);
16925 : }
16926 0 : if( ae_maxint(n1, n2, _state)==28 )
16927 : {
16928 0 : result = mannwhitneyu_utbln5n28(s, _state);
16929 : }
16930 0 : if( ae_maxint(n1, n2, _state)==29 )
16931 : {
16932 0 : result = mannwhitneyu_utbln5n29(s, _state);
16933 : }
16934 0 : if( ae_maxint(n1, n2, _state)>29 )
16935 : {
16936 0 : f0 = mannwhitneyu_utbln5n15(s, _state);
16937 0 : f1 = mannwhitneyu_utbln5n30(s, _state);
16938 0 : f2 = mannwhitneyu_utbln5n100(s, _state);
16939 0 : result = mannwhitneyu_uninterpolate(f0, f1, f2, ae_maxint(n1, n2, _state), _state);
16940 : }
16941 0 : return result;
16942 : }
16943 :
16944 : /*
16945 : * N1=6, N2 = 6, 7, 8, ...
16946 : */
16947 0 : if( ae_minint(n1, n2, _state)==6 )
16948 : {
16949 0 : if( ae_maxint(n1, n2, _state)==6 )
16950 : {
16951 0 : result = mannwhitneyu_utbln6n6(s, _state);
16952 : }
16953 0 : if( ae_maxint(n1, n2, _state)==7 )
16954 : {
16955 0 : result = mannwhitneyu_utbln6n7(s, _state);
16956 : }
16957 0 : if( ae_maxint(n1, n2, _state)==8 )
16958 : {
16959 0 : result = mannwhitneyu_utbln6n8(s, _state);
16960 : }
16961 0 : if( ae_maxint(n1, n2, _state)==9 )
16962 : {
16963 0 : result = mannwhitneyu_utbln6n9(s, _state);
16964 : }
16965 0 : if( ae_maxint(n1, n2, _state)==10 )
16966 : {
16967 0 : result = mannwhitneyu_utbln6n10(s, _state);
16968 : }
16969 0 : if( ae_maxint(n1, n2, _state)==11 )
16970 : {
16971 0 : result = mannwhitneyu_utbln6n11(s, _state);
16972 : }
16973 0 : if( ae_maxint(n1, n2, _state)==12 )
16974 : {
16975 0 : result = mannwhitneyu_utbln6n12(s, _state);
16976 : }
16977 0 : if( ae_maxint(n1, n2, _state)==13 )
16978 : {
16979 0 : result = mannwhitneyu_utbln6n13(s, _state);
16980 : }
16981 0 : if( ae_maxint(n1, n2, _state)==14 )
16982 : {
16983 0 : result = mannwhitneyu_utbln6n14(s, _state);
16984 : }
16985 0 : if( ae_maxint(n1, n2, _state)==15 )
16986 : {
16987 0 : result = mannwhitneyu_utbln6n15(s, _state);
16988 : }
16989 0 : if( ae_maxint(n1, n2, _state)>15 )
16990 : {
16991 0 : f0 = mannwhitneyu_utbln6n15(s, _state);
16992 0 : f1 = mannwhitneyu_utbln6n30(s, _state);
16993 0 : f2 = mannwhitneyu_utbln6n100(s, _state);
16994 0 : result = mannwhitneyu_uninterpolate(f0, f1, f2, ae_maxint(n1, n2, _state), _state);
16995 : }
16996 0 : return result;
16997 : }
16998 :
16999 : /*
17000 : * N1=7, N2 = 7, 8, ...
17001 : */
17002 0 : if( ae_minint(n1, n2, _state)==7 )
17003 : {
17004 0 : if( ae_maxint(n1, n2, _state)==7 )
17005 : {
17006 0 : result = mannwhitneyu_utbln7n7(s, _state);
17007 : }
17008 0 : if( ae_maxint(n1, n2, _state)==8 )
17009 : {
17010 0 : result = mannwhitneyu_utbln7n8(s, _state);
17011 : }
17012 0 : if( ae_maxint(n1, n2, _state)==9 )
17013 : {
17014 0 : result = mannwhitneyu_utbln7n9(s, _state);
17015 : }
17016 0 : if( ae_maxint(n1, n2, _state)==10 )
17017 : {
17018 0 : result = mannwhitneyu_utbln7n10(s, _state);
17019 : }
17020 0 : if( ae_maxint(n1, n2, _state)==11 )
17021 : {
17022 0 : result = mannwhitneyu_utbln7n11(s, _state);
17023 : }
17024 0 : if( ae_maxint(n1, n2, _state)==12 )
17025 : {
17026 0 : result = mannwhitneyu_utbln7n12(s, _state);
17027 : }
17028 0 : if( ae_maxint(n1, n2, _state)==13 )
17029 : {
17030 0 : result = mannwhitneyu_utbln7n13(s, _state);
17031 : }
17032 0 : if( ae_maxint(n1, n2, _state)==14 )
17033 : {
17034 0 : result = mannwhitneyu_utbln7n14(s, _state);
17035 : }
17036 0 : if( ae_maxint(n1, n2, _state)==15 )
17037 : {
17038 0 : result = mannwhitneyu_utbln7n15(s, _state);
17039 : }
17040 0 : if( ae_maxint(n1, n2, _state)>15 )
17041 : {
17042 0 : f0 = mannwhitneyu_utbln7n15(s, _state);
17043 0 : f1 = mannwhitneyu_utbln7n30(s, _state);
17044 0 : f2 = mannwhitneyu_utbln7n100(s, _state);
17045 0 : result = mannwhitneyu_uninterpolate(f0, f1, f2, ae_maxint(n1, n2, _state), _state);
17046 : }
17047 0 : return result;
17048 : }
17049 :
17050 : /*
17051 : * N1=8, N2 = 8, 9, 10, ...
17052 : */
17053 0 : if( ae_minint(n1, n2, _state)==8 )
17054 : {
17055 0 : if( ae_maxint(n1, n2, _state)==8 )
17056 : {
17057 0 : result = mannwhitneyu_utbln8n8(s, _state);
17058 : }
17059 0 : if( ae_maxint(n1, n2, _state)==9 )
17060 : {
17061 0 : result = mannwhitneyu_utbln8n9(s, _state);
17062 : }
17063 0 : if( ae_maxint(n1, n2, _state)==10 )
17064 : {
17065 0 : result = mannwhitneyu_utbln8n10(s, _state);
17066 : }
17067 0 : if( ae_maxint(n1, n2, _state)==11 )
17068 : {
17069 0 : result = mannwhitneyu_utbln8n11(s, _state);
17070 : }
17071 0 : if( ae_maxint(n1, n2, _state)==12 )
17072 : {
17073 0 : result = mannwhitneyu_utbln8n12(s, _state);
17074 : }
17075 0 : if( ae_maxint(n1, n2, _state)==13 )
17076 : {
17077 0 : result = mannwhitneyu_utbln8n13(s, _state);
17078 : }
17079 0 : if( ae_maxint(n1, n2, _state)==14 )
17080 : {
17081 0 : result = mannwhitneyu_utbln8n14(s, _state);
17082 : }
17083 0 : if( ae_maxint(n1, n2, _state)==15 )
17084 : {
17085 0 : result = mannwhitneyu_utbln8n15(s, _state);
17086 : }
17087 0 : if( ae_maxint(n1, n2, _state)>15 )
17088 : {
17089 0 : f0 = mannwhitneyu_utbln8n15(s, _state);
17090 0 : f1 = mannwhitneyu_utbln8n30(s, _state);
17091 0 : f2 = mannwhitneyu_utbln8n100(s, _state);
17092 0 : result = mannwhitneyu_uninterpolate(f0, f1, f2, ae_maxint(n1, n2, _state), _state);
17093 : }
17094 0 : return result;
17095 : }
17096 :
17097 : /*
17098 : * N1=9, N2 = 9, 10, ...
17099 : */
17100 0 : if( ae_minint(n1, n2, _state)==9 )
17101 : {
17102 0 : if( ae_maxint(n1, n2, _state)==9 )
17103 : {
17104 0 : result = mannwhitneyu_utbln9n9(s, _state);
17105 : }
17106 0 : if( ae_maxint(n1, n2, _state)==10 )
17107 : {
17108 0 : result = mannwhitneyu_utbln9n10(s, _state);
17109 : }
17110 0 : if( ae_maxint(n1, n2, _state)==11 )
17111 : {
17112 0 : result = mannwhitneyu_utbln9n11(s, _state);
17113 : }
17114 0 : if( ae_maxint(n1, n2, _state)==12 )
17115 : {
17116 0 : result = mannwhitneyu_utbln9n12(s, _state);
17117 : }
17118 0 : if( ae_maxint(n1, n2, _state)==13 )
17119 : {
17120 0 : result = mannwhitneyu_utbln9n13(s, _state);
17121 : }
17122 0 : if( ae_maxint(n1, n2, _state)==14 )
17123 : {
17124 0 : result = mannwhitneyu_utbln9n14(s, _state);
17125 : }
17126 0 : if( ae_maxint(n1, n2, _state)==15 )
17127 : {
17128 0 : result = mannwhitneyu_utbln9n15(s, _state);
17129 : }
17130 0 : if( ae_maxint(n1, n2, _state)>15 )
17131 : {
17132 0 : f0 = mannwhitneyu_utbln9n15(s, _state);
17133 0 : f1 = mannwhitneyu_utbln9n30(s, _state);
17134 0 : f2 = mannwhitneyu_utbln9n100(s, _state);
17135 0 : result = mannwhitneyu_uninterpolate(f0, f1, f2, ae_maxint(n1, n2, _state), _state);
17136 : }
17137 0 : return result;
17138 : }
17139 :
17140 : /*
17141 : * N1=10, N2 = 10, 11, ...
17142 : */
17143 0 : if( ae_minint(n1, n2, _state)==10 )
17144 : {
17145 0 : if( ae_maxint(n1, n2, _state)==10 )
17146 : {
17147 0 : result = mannwhitneyu_utbln10n10(s, _state);
17148 : }
17149 0 : if( ae_maxint(n1, n2, _state)==11 )
17150 : {
17151 0 : result = mannwhitneyu_utbln10n11(s, _state);
17152 : }
17153 0 : if( ae_maxint(n1, n2, _state)==12 )
17154 : {
17155 0 : result = mannwhitneyu_utbln10n12(s, _state);
17156 : }
17157 0 : if( ae_maxint(n1, n2, _state)==13 )
17158 : {
17159 0 : result = mannwhitneyu_utbln10n13(s, _state);
17160 : }
17161 0 : if( ae_maxint(n1, n2, _state)==14 )
17162 : {
17163 0 : result = mannwhitneyu_utbln10n14(s, _state);
17164 : }
17165 0 : if( ae_maxint(n1, n2, _state)==15 )
17166 : {
17167 0 : result = mannwhitneyu_utbln10n15(s, _state);
17168 : }
17169 0 : if( ae_maxint(n1, n2, _state)>15 )
17170 : {
17171 0 : f0 = mannwhitneyu_utbln10n15(s, _state);
17172 0 : f1 = mannwhitneyu_utbln10n30(s, _state);
17173 0 : f2 = mannwhitneyu_utbln10n100(s, _state);
17174 0 : result = mannwhitneyu_uninterpolate(f0, f1, f2, ae_maxint(n1, n2, _state), _state);
17175 : }
17176 0 : return result;
17177 : }
17178 :
17179 : /*
17180 : * N1=11, N2 = 11, 12, ...
17181 : */
17182 0 : if( ae_minint(n1, n2, _state)==11 )
17183 : {
17184 0 : if( ae_maxint(n1, n2, _state)==11 )
17185 : {
17186 0 : result = mannwhitneyu_utbln11n11(s, _state);
17187 : }
17188 0 : if( ae_maxint(n1, n2, _state)==12 )
17189 : {
17190 0 : result = mannwhitneyu_utbln11n12(s, _state);
17191 : }
17192 0 : if( ae_maxint(n1, n2, _state)==13 )
17193 : {
17194 0 : result = mannwhitneyu_utbln11n13(s, _state);
17195 : }
17196 0 : if( ae_maxint(n1, n2, _state)==14 )
17197 : {
17198 0 : result = mannwhitneyu_utbln11n14(s, _state);
17199 : }
17200 0 : if( ae_maxint(n1, n2, _state)==15 )
17201 : {
17202 0 : result = mannwhitneyu_utbln11n15(s, _state);
17203 : }
17204 0 : if( ae_maxint(n1, n2, _state)>15 )
17205 : {
17206 0 : f0 = mannwhitneyu_utbln11n15(s, _state);
17207 0 : f1 = mannwhitneyu_utbln11n30(s, _state);
17208 0 : f2 = mannwhitneyu_utbln11n100(s, _state);
17209 0 : result = mannwhitneyu_uninterpolate(f0, f1, f2, ae_maxint(n1, n2, _state), _state);
17210 : }
17211 0 : return result;
17212 : }
17213 :
17214 : /*
17215 : * N1=12, N2 = 12, 13, ...
17216 : */
17217 0 : if( ae_minint(n1, n2, _state)==12 )
17218 : {
17219 0 : if( ae_maxint(n1, n2, _state)==12 )
17220 : {
17221 0 : result = mannwhitneyu_utbln12n12(s, _state);
17222 : }
17223 0 : if( ae_maxint(n1, n2, _state)==13 )
17224 : {
17225 0 : result = mannwhitneyu_utbln12n13(s, _state);
17226 : }
17227 0 : if( ae_maxint(n1, n2, _state)==14 )
17228 : {
17229 0 : result = mannwhitneyu_utbln12n14(s, _state);
17230 : }
17231 0 : if( ae_maxint(n1, n2, _state)==15 )
17232 : {
17233 0 : result = mannwhitneyu_utbln12n15(s, _state);
17234 : }
17235 0 : if( ae_maxint(n1, n2, _state)>15 )
17236 : {
17237 0 : f0 = mannwhitneyu_utbln12n15(s, _state);
17238 0 : f1 = mannwhitneyu_utbln12n30(s, _state);
17239 0 : f2 = mannwhitneyu_utbln12n100(s, _state);
17240 0 : result = mannwhitneyu_uninterpolate(f0, f1, f2, ae_maxint(n1, n2, _state), _state);
17241 : }
17242 0 : return result;
17243 : }
17244 :
17245 : /*
17246 : * N1=13, N2 = 13, 14, ...
17247 : */
17248 0 : if( ae_minint(n1, n2, _state)==13 )
17249 : {
17250 0 : if( ae_maxint(n1, n2, _state)==13 )
17251 : {
17252 0 : result = mannwhitneyu_utbln13n13(s, _state);
17253 : }
17254 0 : if( ae_maxint(n1, n2, _state)==14 )
17255 : {
17256 0 : result = mannwhitneyu_utbln13n14(s, _state);
17257 : }
17258 0 : if( ae_maxint(n1, n2, _state)==15 )
17259 : {
17260 0 : result = mannwhitneyu_utbln13n15(s, _state);
17261 : }
17262 0 : if( ae_maxint(n1, n2, _state)>15 )
17263 : {
17264 0 : f0 = mannwhitneyu_utbln13n15(s, _state);
17265 0 : f1 = mannwhitneyu_utbln13n30(s, _state);
17266 0 : f2 = mannwhitneyu_utbln13n100(s, _state);
17267 0 : result = mannwhitneyu_uninterpolate(f0, f1, f2, ae_maxint(n1, n2, _state), _state);
17268 : }
17269 0 : return result;
17270 : }
17271 :
17272 : /*
17273 : * N1=14, N2 = 14, 15, ...
17274 : */
17275 0 : if( ae_minint(n1, n2, _state)==14 )
17276 : {
17277 0 : if( ae_maxint(n1, n2, _state)==14 )
17278 : {
17279 0 : result = mannwhitneyu_utbln14n14(s, _state);
17280 : }
17281 0 : if( ae_maxint(n1, n2, _state)==15 )
17282 : {
17283 0 : result = mannwhitneyu_utbln14n15(s, _state);
17284 : }
17285 0 : if( ae_maxint(n1, n2, _state)>15 )
17286 : {
17287 0 : f0 = mannwhitneyu_utbln14n15(s, _state);
17288 0 : f1 = mannwhitneyu_utbln14n30(s, _state);
17289 0 : f2 = mannwhitneyu_utbln14n100(s, _state);
17290 0 : result = mannwhitneyu_uninterpolate(f0, f1, f2, ae_maxint(n1, n2, _state), _state);
17291 : }
17292 0 : return result;
17293 : }
17294 :
17295 : /*
17296 : * N1 >= 15, N2 >= 15
17297 : */
17298 0 : if( ae_fp_greater(s,(double)(4)) )
17299 : {
17300 0 : s = (double)(4);
17301 : }
17302 0 : if( ae_fp_less(s,(double)(3)) )
17303 : {
17304 0 : s0 = 0.000000e+00;
17305 0 : f0 = mannwhitneyu_usigma000(n1, n2, _state);
17306 0 : s1 = 7.500000e-01;
17307 0 : f1 = mannwhitneyu_usigma075(n1, n2, _state);
17308 0 : s2 = 1.500000e+00;
17309 0 : f2 = mannwhitneyu_usigma150(n1, n2, _state);
17310 0 : s3 = 2.250000e+00;
17311 0 : f3 = mannwhitneyu_usigma225(n1, n2, _state);
17312 0 : s4 = 3.000000e+00;
17313 0 : f4 = mannwhitneyu_usigma300(n1, n2, _state);
17314 0 : f1 = ((s-s0)*f1-(s-s1)*f0)/(s1-s0);
17315 0 : f2 = ((s-s0)*f2-(s-s2)*f0)/(s2-s0);
17316 0 : f3 = ((s-s0)*f3-(s-s3)*f0)/(s3-s0);
17317 0 : f4 = ((s-s0)*f4-(s-s4)*f0)/(s4-s0);
17318 0 : f2 = ((s-s1)*f2-(s-s2)*f1)/(s2-s1);
17319 0 : f3 = ((s-s1)*f3-(s-s3)*f1)/(s3-s1);
17320 0 : f4 = ((s-s1)*f4-(s-s4)*f1)/(s4-s1);
17321 0 : f3 = ((s-s2)*f3-(s-s3)*f2)/(s3-s2);
17322 0 : f4 = ((s-s2)*f4-(s-s4)*f2)/(s4-s2);
17323 0 : f4 = ((s-s3)*f4-(s-s4)*f3)/(s4-s3);
17324 0 : result = f4;
17325 : }
17326 : else
17327 : {
17328 0 : s0 = 3.000000e+00;
17329 0 : f0 = mannwhitneyu_usigma300(n1, n2, _state);
17330 0 : s1 = 3.333333e+00;
17331 0 : f1 = mannwhitneyu_usigma333(n1, n2, _state);
17332 0 : s2 = 3.666667e+00;
17333 0 : f2 = mannwhitneyu_usigma367(n1, n2, _state);
17334 0 : s3 = 4.000000e+00;
17335 0 : f3 = mannwhitneyu_usigma400(n1, n2, _state);
17336 0 : f1 = ((s-s0)*f1-(s-s1)*f0)/(s1-s0);
17337 0 : f2 = ((s-s0)*f2-(s-s2)*f0)/(s2-s0);
17338 0 : f3 = ((s-s0)*f3-(s-s3)*f0)/(s3-s0);
17339 0 : f2 = ((s-s1)*f2-(s-s2)*f1)/(s2-s1);
17340 0 : f3 = ((s-s1)*f3-(s-s3)*f1)/(s3-s1);
17341 0 : f3 = ((s-s2)*f3-(s-s3)*f2)/(s3-s2);
17342 0 : result = f3;
17343 : }
17344 0 : return result;
17345 : }
17346 :
17347 :
17348 : #endif
17349 : #if defined(AE_COMPILE_JARQUEBERA) || !defined(AE_PARTIAL_BUILD)
17350 :
17351 :
17352 : /*************************************************************************
17353 : Jarque-Bera test
17354 :
17355 : This test checks hypotheses about the fact that a given sample X is a
17356 : sample of normal random variable.
17357 :
17358 : Requirements:
17359 : * the number of elements in the sample is not less than 5.
17360 :
17361 : Input parameters:
17362 : X - sample. Array whose index goes from 0 to N-1.
17363 : N - size of the sample. N>=5
17364 :
17365 : Output parameters:
17366 : P - p-value for the test
17367 :
17368 : Accuracy of the approximation used (5<=N<=1951):
17369 :
17370 : p-value relative error (5<=N<=1951)
17371 : [1, 0.1] < 1%
17372 : [0.1, 0.01] < 2%
17373 : [0.01, 0.001] < 6%
17374 : [0.001, 0] wasn't measured
17375 :
17376 : For N>1951 accuracy wasn't measured but it shouldn't be sharply different
17377 : from table values.
17378 :
17379 : -- ALGLIB --
17380 : Copyright 09.04.2007 by Bochkanov Sergey
17381 : *************************************************************************/
17382 0 : void jarqueberatest(/* Real */ ae_vector* x,
17383 : ae_int_t n,
17384 : double* p,
17385 : ae_state *_state)
17386 : {
17387 : double s;
17388 :
17389 0 : *p = 0;
17390 :
17391 :
17392 : /*
17393 : * N is too small
17394 : */
17395 0 : if( n<5 )
17396 : {
17397 0 : *p = 1.0;
17398 0 : return;
17399 : }
17400 :
17401 : /*
17402 : * N is large enough
17403 : */
17404 0 : jarquebera_jarqueberastatistic(x, n, &s, _state);
17405 0 : *p = jarquebera_jarqueberaapprox(n, s, _state);
17406 : }
17407 :
17408 :
17409 0 : static void jarquebera_jarqueberastatistic(/* Real */ ae_vector* x,
17410 : ae_int_t n,
17411 : double* s,
17412 : ae_state *_state)
17413 : {
17414 : ae_int_t i;
17415 : double v;
17416 : double v1;
17417 : double v2;
17418 : double stddev;
17419 : double mean;
17420 : double variance;
17421 : double skewness;
17422 : double kurtosis;
17423 :
17424 0 : *s = 0;
17425 :
17426 0 : mean = (double)(0);
17427 0 : variance = (double)(0);
17428 0 : skewness = (double)(0);
17429 0 : kurtosis = (double)(0);
17430 0 : stddev = (double)(0);
17431 0 : ae_assert(n>1, "Assertion failed", _state);
17432 :
17433 : /*
17434 : * Mean
17435 : */
17436 0 : for(i=0; i<=n-1; i++)
17437 : {
17438 0 : mean = mean+x->ptr.p_double[i];
17439 : }
17440 0 : mean = mean/n;
17441 :
17442 : /*
17443 : * Variance (using corrected two-pass algorithm)
17444 : */
17445 0 : if( n!=1 )
17446 : {
17447 0 : v1 = (double)(0);
17448 0 : for(i=0; i<=n-1; i++)
17449 : {
17450 0 : v1 = v1+ae_sqr(x->ptr.p_double[i]-mean, _state);
17451 : }
17452 0 : v2 = (double)(0);
17453 0 : for(i=0; i<=n-1; i++)
17454 : {
17455 0 : v2 = v2+(x->ptr.p_double[i]-mean);
17456 : }
17457 0 : v2 = ae_sqr(v2, _state)/n;
17458 0 : variance = (v1-v2)/(n-1);
17459 0 : if( ae_fp_less(variance,(double)(0)) )
17460 : {
17461 0 : variance = (double)(0);
17462 : }
17463 0 : stddev = ae_sqrt(variance, _state);
17464 : }
17465 :
17466 : /*
17467 : * Skewness and kurtosis
17468 : */
17469 0 : if( ae_fp_neq(stddev,(double)(0)) )
17470 : {
17471 0 : for(i=0; i<=n-1; i++)
17472 : {
17473 0 : v = (x->ptr.p_double[i]-mean)/stddev;
17474 0 : v2 = ae_sqr(v, _state);
17475 0 : skewness = skewness+v2*v;
17476 0 : kurtosis = kurtosis+ae_sqr(v2, _state);
17477 : }
17478 0 : skewness = skewness/n;
17479 0 : kurtosis = kurtosis/n-3;
17480 : }
17481 :
17482 : /*
17483 : * Statistic
17484 : */
17485 0 : *s = (double)n/(double)6*(ae_sqr(skewness, _state)+ae_sqr(kurtosis, _state)/4);
17486 0 : }
17487 :
17488 :
17489 0 : static double jarquebera_jarqueberaapprox(ae_int_t n,
17490 : double s,
17491 : ae_state *_state)
17492 : {
17493 : ae_frame _frame_block;
17494 : ae_vector vx;
17495 : ae_vector vy;
17496 : ae_matrix ctbl;
17497 : double t1;
17498 : double t2;
17499 : double t3;
17500 : double t;
17501 : double f1;
17502 : double f2;
17503 : double f3;
17504 : double f12;
17505 : double f23;
17506 : double x;
17507 : double result;
17508 :
17509 0 : ae_frame_make(_state, &_frame_block);
17510 0 : memset(&vx, 0, sizeof(vx));
17511 0 : memset(&vy, 0, sizeof(vy));
17512 0 : memset(&ctbl, 0, sizeof(ctbl));
17513 0 : ae_vector_init(&vx, 0, DT_REAL, _state, ae_true);
17514 0 : ae_vector_init(&vy, 0, DT_REAL, _state, ae_true);
17515 0 : ae_matrix_init(&ctbl, 0, 0, DT_REAL, _state, ae_true);
17516 :
17517 0 : result = (double)(1);
17518 0 : x = s;
17519 0 : if( n<5 )
17520 : {
17521 0 : ae_frame_leave(_state);
17522 0 : return result;
17523 : }
17524 :
17525 : /*
17526 : * N = 5..20 are tabulated
17527 : */
17528 0 : if( n>=5&&n<=20 )
17529 : {
17530 0 : if( n==5 )
17531 : {
17532 0 : result = ae_exp(jarquebera_jbtbl5(x, _state), _state);
17533 : }
17534 0 : if( n==6 )
17535 : {
17536 0 : result = ae_exp(jarquebera_jbtbl6(x, _state), _state);
17537 : }
17538 0 : if( n==7 )
17539 : {
17540 0 : result = ae_exp(jarquebera_jbtbl7(x, _state), _state);
17541 : }
17542 0 : if( n==8 )
17543 : {
17544 0 : result = ae_exp(jarquebera_jbtbl8(x, _state), _state);
17545 : }
17546 0 : if( n==9 )
17547 : {
17548 0 : result = ae_exp(jarquebera_jbtbl9(x, _state), _state);
17549 : }
17550 0 : if( n==10 )
17551 : {
17552 0 : result = ae_exp(jarquebera_jbtbl10(x, _state), _state);
17553 : }
17554 0 : if( n==11 )
17555 : {
17556 0 : result = ae_exp(jarquebera_jbtbl11(x, _state), _state);
17557 : }
17558 0 : if( n==12 )
17559 : {
17560 0 : result = ae_exp(jarquebera_jbtbl12(x, _state), _state);
17561 : }
17562 0 : if( n==13 )
17563 : {
17564 0 : result = ae_exp(jarquebera_jbtbl13(x, _state), _state);
17565 : }
17566 0 : if( n==14 )
17567 : {
17568 0 : result = ae_exp(jarquebera_jbtbl14(x, _state), _state);
17569 : }
17570 0 : if( n==15 )
17571 : {
17572 0 : result = ae_exp(jarquebera_jbtbl15(x, _state), _state);
17573 : }
17574 0 : if( n==16 )
17575 : {
17576 0 : result = ae_exp(jarquebera_jbtbl16(x, _state), _state);
17577 : }
17578 0 : if( n==17 )
17579 : {
17580 0 : result = ae_exp(jarquebera_jbtbl17(x, _state), _state);
17581 : }
17582 0 : if( n==18 )
17583 : {
17584 0 : result = ae_exp(jarquebera_jbtbl18(x, _state), _state);
17585 : }
17586 0 : if( n==19 )
17587 : {
17588 0 : result = ae_exp(jarquebera_jbtbl19(x, _state), _state);
17589 : }
17590 0 : if( n==20 )
17591 : {
17592 0 : result = ae_exp(jarquebera_jbtbl20(x, _state), _state);
17593 : }
17594 0 : ae_frame_leave(_state);
17595 0 : return result;
17596 : }
17597 :
17598 : /*
17599 : * N = 20, 30, 50 are tabulated.
17600 : * In-between values are interpolated
17601 : * using interpolating polynomial of the second degree.
17602 : */
17603 0 : if( n>20&&n<=50 )
17604 : {
17605 0 : t1 = -1.0/20.0;
17606 0 : t2 = -1.0/30.0;
17607 0 : t3 = -1.0/50.0;
17608 0 : t = -1.0/n;
17609 0 : f1 = jarquebera_jbtbl20(x, _state);
17610 0 : f2 = jarquebera_jbtbl30(x, _state);
17611 0 : f3 = jarquebera_jbtbl50(x, _state);
17612 0 : f12 = ((t-t2)*f1+(t1-t)*f2)/(t1-t2);
17613 0 : f23 = ((t-t3)*f2+(t2-t)*f3)/(t2-t3);
17614 0 : result = ((t-t3)*f12+(t1-t)*f23)/(t1-t3);
17615 0 : if( ae_fp_greater(result,(double)(0)) )
17616 : {
17617 0 : result = (double)(0);
17618 : }
17619 0 : result = ae_exp(result, _state);
17620 0 : ae_frame_leave(_state);
17621 0 : return result;
17622 : }
17623 :
17624 : /*
17625 : * N = 50, 65, 100 are tabulated.
17626 : * In-between values are interpolated
17627 : * using interpolating polynomial of the second degree.
17628 : */
17629 0 : if( n>50&&n<=100 )
17630 : {
17631 0 : t1 = -1.0/50.0;
17632 0 : t2 = -1.0/65.0;
17633 0 : t3 = -1.0/100.0;
17634 0 : t = -1.0/n;
17635 0 : f1 = jarquebera_jbtbl50(x, _state);
17636 0 : f2 = jarquebera_jbtbl65(x, _state);
17637 0 : f3 = jarquebera_jbtbl100(x, _state);
17638 0 : f12 = ((t-t2)*f1+(t1-t)*f2)/(t1-t2);
17639 0 : f23 = ((t-t3)*f2+(t2-t)*f3)/(t2-t3);
17640 0 : result = ((t-t3)*f12+(t1-t)*f23)/(t1-t3);
17641 0 : if( ae_fp_greater(result,(double)(0)) )
17642 : {
17643 0 : result = (double)(0);
17644 : }
17645 0 : result = ae_exp(result, _state);
17646 0 : ae_frame_leave(_state);
17647 0 : return result;
17648 : }
17649 :
17650 : /*
17651 : * N = 100, 130, 200 are tabulated.
17652 : * In-between values are interpolated
17653 : * using interpolating polynomial of the second degree.
17654 : */
17655 0 : if( n>100&&n<=200 )
17656 : {
17657 0 : t1 = -1.0/100.0;
17658 0 : t2 = -1.0/130.0;
17659 0 : t3 = -1.0/200.0;
17660 0 : t = -1.0/n;
17661 0 : f1 = jarquebera_jbtbl100(x, _state);
17662 0 : f2 = jarquebera_jbtbl130(x, _state);
17663 0 : f3 = jarquebera_jbtbl200(x, _state);
17664 0 : f12 = ((t-t2)*f1+(t1-t)*f2)/(t1-t2);
17665 0 : f23 = ((t-t3)*f2+(t2-t)*f3)/(t2-t3);
17666 0 : result = ((t-t3)*f12+(t1-t)*f23)/(t1-t3);
17667 0 : if( ae_fp_greater(result,(double)(0)) )
17668 : {
17669 0 : result = (double)(0);
17670 : }
17671 0 : result = ae_exp(result, _state);
17672 0 : ae_frame_leave(_state);
17673 0 : return result;
17674 : }
17675 :
17676 : /*
17677 : * N = 200, 301, 501 are tabulated.
17678 : * In-between values are interpolated
17679 : * using interpolating polynomial of the second degree.
17680 : */
17681 0 : if( n>200&&n<=501 )
17682 : {
17683 0 : t1 = -1.0/200.0;
17684 0 : t2 = -1.0/301.0;
17685 0 : t3 = -1.0/501.0;
17686 0 : t = -1.0/n;
17687 0 : f1 = jarquebera_jbtbl200(x, _state);
17688 0 : f2 = jarquebera_jbtbl301(x, _state);
17689 0 : f3 = jarquebera_jbtbl501(x, _state);
17690 0 : f12 = ((t-t2)*f1+(t1-t)*f2)/(t1-t2);
17691 0 : f23 = ((t-t3)*f2+(t2-t)*f3)/(t2-t3);
17692 0 : result = ((t-t3)*f12+(t1-t)*f23)/(t1-t3);
17693 0 : if( ae_fp_greater(result,(double)(0)) )
17694 : {
17695 0 : result = (double)(0);
17696 : }
17697 0 : result = ae_exp(result, _state);
17698 0 : ae_frame_leave(_state);
17699 0 : return result;
17700 : }
17701 :
17702 : /*
17703 : * N = 501, 701, 1401 are tabulated.
17704 : * In-between values are interpolated
17705 : * using interpolating polynomial of the second degree.
17706 : */
17707 0 : if( n>501&&n<=1401 )
17708 : {
17709 0 : t1 = -1.0/501.0;
17710 0 : t2 = -1.0/701.0;
17711 0 : t3 = -1.0/1401.0;
17712 0 : t = -1.0/n;
17713 0 : f1 = jarquebera_jbtbl501(x, _state);
17714 0 : f2 = jarquebera_jbtbl701(x, _state);
17715 0 : f3 = jarquebera_jbtbl1401(x, _state);
17716 0 : f12 = ((t-t2)*f1+(t1-t)*f2)/(t1-t2);
17717 0 : f23 = ((t-t3)*f2+(t2-t)*f3)/(t2-t3);
17718 0 : result = ((t-t3)*f12+(t1-t)*f23)/(t1-t3);
17719 0 : if( ae_fp_greater(result,(double)(0)) )
17720 : {
17721 0 : result = (double)(0);
17722 : }
17723 0 : result = ae_exp(result, _state);
17724 0 : ae_frame_leave(_state);
17725 0 : return result;
17726 : }
17727 :
17728 : /*
17729 : * Asymptotic expansion
17730 : */
17731 0 : if( n>1401 )
17732 : {
17733 0 : result = -0.5*x+(jarquebera_jbtbl1401(x, _state)+0.5*x)*ae_sqrt((double)1401/(double)n, _state);
17734 0 : if( ae_fp_greater(result,(double)(0)) )
17735 : {
17736 0 : result = (double)(0);
17737 : }
17738 0 : result = ae_exp(result, _state);
17739 0 : ae_frame_leave(_state);
17740 0 : return result;
17741 : }
17742 0 : ae_frame_leave(_state);
17743 0 : return result;
17744 : }
17745 :
17746 :
17747 0 : static double jarquebera_jbtbl5(double s, ae_state *_state)
17748 : {
17749 : double x;
17750 : double tj;
17751 : double tj1;
17752 : double result;
17753 :
17754 :
17755 0 : result = (double)(0);
17756 0 : if( ae_fp_less_eq(s,0.4000) )
17757 : {
17758 0 : x = 2*(s-0.000000)/0.400000-1;
17759 0 : tj = (double)(1);
17760 0 : tj1 = x;
17761 0 : jarquebera_jbcheb(x, -1.097885e-20, &tj, &tj1, &result, _state);
17762 0 : jarquebera_jbcheb(x, -2.854501e-20, &tj, &tj1, &result, _state);
17763 0 : jarquebera_jbcheb(x, -1.756616e-20, &tj, &tj1, &result, _state);
17764 0 : if( ae_fp_greater(result,(double)(0)) )
17765 : {
17766 0 : result = (double)(0);
17767 : }
17768 0 : return result;
17769 : }
17770 0 : if( ae_fp_less_eq(s,1.1000) )
17771 : {
17772 0 : x = 2*(s-0.400000)/0.700000-1;
17773 0 : tj = (double)(1);
17774 0 : tj1 = x;
17775 0 : jarquebera_jbcheb(x, -1.324545e+00, &tj, &tj1, &result, _state);
17776 0 : jarquebera_jbcheb(x, -1.075941e+00, &tj, &tj1, &result, _state);
17777 0 : jarquebera_jbcheb(x, -9.772272e-01, &tj, &tj1, &result, _state);
17778 0 : jarquebera_jbcheb(x, 3.175686e-01, &tj, &tj1, &result, _state);
17779 0 : jarquebera_jbcheb(x, -1.576162e-01, &tj, &tj1, &result, _state);
17780 0 : jarquebera_jbcheb(x, 1.126861e-01, &tj, &tj1, &result, _state);
17781 0 : jarquebera_jbcheb(x, -3.434425e-02, &tj, &tj1, &result, _state);
17782 0 : jarquebera_jbcheb(x, -2.790359e-01, &tj, &tj1, &result, _state);
17783 0 : jarquebera_jbcheb(x, 2.809178e-02, &tj, &tj1, &result, _state);
17784 0 : jarquebera_jbcheb(x, -5.479704e-01, &tj, &tj1, &result, _state);
17785 0 : jarquebera_jbcheb(x, 3.717040e-02, &tj, &tj1, &result, _state);
17786 0 : jarquebera_jbcheb(x, -5.294170e-01, &tj, &tj1, &result, _state);
17787 0 : jarquebera_jbcheb(x, 2.880632e-02, &tj, &tj1, &result, _state);
17788 0 : jarquebera_jbcheb(x, -3.023344e-01, &tj, &tj1, &result, _state);
17789 0 : jarquebera_jbcheb(x, 1.601531e-02, &tj, &tj1, &result, _state);
17790 0 : jarquebera_jbcheb(x, -7.920403e-02, &tj, &tj1, &result, _state);
17791 0 : if( ae_fp_greater(result,(double)(0)) )
17792 : {
17793 0 : result = (double)(0);
17794 : }
17795 0 : return result;
17796 : }
17797 0 : result = -5.188419e+02*(s-1.100000e+00)-4.767297e+00;
17798 0 : return result;
17799 : }
17800 :
17801 :
17802 0 : static double jarquebera_jbtbl6(double s, ae_state *_state)
17803 : {
17804 : double x;
17805 : double tj;
17806 : double tj1;
17807 : double result;
17808 :
17809 :
17810 0 : result = (double)(0);
17811 0 : if( ae_fp_less_eq(s,0.2500) )
17812 : {
17813 0 : x = 2*(s-0.000000)/0.250000-1;
17814 0 : tj = (double)(1);
17815 0 : tj1 = x;
17816 0 : jarquebera_jbcheb(x, -2.274707e-04, &tj, &tj1, &result, _state);
17817 0 : jarquebera_jbcheb(x, -5.700471e-04, &tj, &tj1, &result, _state);
17818 0 : jarquebera_jbcheb(x, -3.425764e-04, &tj, &tj1, &result, _state);
17819 0 : if( ae_fp_greater(result,(double)(0)) )
17820 : {
17821 0 : result = (double)(0);
17822 : }
17823 0 : return result;
17824 : }
17825 0 : if( ae_fp_less_eq(s,1.3000) )
17826 : {
17827 0 : x = 2*(s-0.250000)/1.050000-1;
17828 0 : tj = (double)(1);
17829 0 : tj1 = x;
17830 0 : jarquebera_jbcheb(x, -1.339000e+00, &tj, &tj1, &result, _state);
17831 0 : jarquebera_jbcheb(x, -2.011104e+00, &tj, &tj1, &result, _state);
17832 0 : jarquebera_jbcheb(x, -8.168177e-01, &tj, &tj1, &result, _state);
17833 0 : jarquebera_jbcheb(x, -1.085666e-01, &tj, &tj1, &result, _state);
17834 0 : jarquebera_jbcheb(x, 7.738606e-02, &tj, &tj1, &result, _state);
17835 0 : jarquebera_jbcheb(x, 7.022876e-02, &tj, &tj1, &result, _state);
17836 0 : jarquebera_jbcheb(x, 3.462402e-02, &tj, &tj1, &result, _state);
17837 0 : jarquebera_jbcheb(x, 6.908270e-03, &tj, &tj1, &result, _state);
17838 0 : jarquebera_jbcheb(x, -8.230772e-03, &tj, &tj1, &result, _state);
17839 0 : jarquebera_jbcheb(x, -1.006996e-02, &tj, &tj1, &result, _state);
17840 0 : jarquebera_jbcheb(x, -5.410222e-03, &tj, &tj1, &result, _state);
17841 0 : jarquebera_jbcheb(x, -2.893768e-03, &tj, &tj1, &result, _state);
17842 0 : jarquebera_jbcheb(x, 8.114564e-04, &tj, &tj1, &result, _state);
17843 0 : if( ae_fp_greater(result,(double)(0)) )
17844 : {
17845 0 : result = (double)(0);
17846 : }
17847 0 : return result;
17848 : }
17849 0 : if( ae_fp_less_eq(s,1.8500) )
17850 : {
17851 0 : x = 2*(s-1.300000)/0.550000-1;
17852 0 : tj = (double)(1);
17853 0 : tj1 = x;
17854 0 : jarquebera_jbcheb(x, -6.794311e+00, &tj, &tj1, &result, _state);
17855 0 : jarquebera_jbcheb(x, -3.578700e+00, &tj, &tj1, &result, _state);
17856 0 : jarquebera_jbcheb(x, -1.394664e+00, &tj, &tj1, &result, _state);
17857 0 : jarquebera_jbcheb(x, -7.928290e-01, &tj, &tj1, &result, _state);
17858 0 : jarquebera_jbcheb(x, -4.813273e-01, &tj, &tj1, &result, _state);
17859 0 : jarquebera_jbcheb(x, -3.076063e-01, &tj, &tj1, &result, _state);
17860 0 : jarquebera_jbcheb(x, -1.835380e-01, &tj, &tj1, &result, _state);
17861 0 : jarquebera_jbcheb(x, -1.013013e-01, &tj, &tj1, &result, _state);
17862 0 : jarquebera_jbcheb(x, -5.058903e-02, &tj, &tj1, &result, _state);
17863 0 : jarquebera_jbcheb(x, -1.856915e-02, &tj, &tj1, &result, _state);
17864 0 : jarquebera_jbcheb(x, -6.710887e-03, &tj, &tj1, &result, _state);
17865 0 : if( ae_fp_greater(result,(double)(0)) )
17866 : {
17867 0 : result = (double)(0);
17868 : }
17869 0 : return result;
17870 : }
17871 0 : result = -1.770029e+02*(s-1.850000e+00)-1.371015e+01;
17872 0 : return result;
17873 : }
17874 :
17875 :
17876 0 : static double jarquebera_jbtbl7(double s, ae_state *_state)
17877 : {
17878 : double x;
17879 : double tj;
17880 : double tj1;
17881 : double result;
17882 :
17883 :
17884 0 : result = (double)(0);
17885 0 : if( ae_fp_less_eq(s,1.4000) )
17886 : {
17887 0 : x = 2*(s-0.000000)/1.400000-1;
17888 0 : tj = (double)(1);
17889 0 : tj1 = x;
17890 0 : jarquebera_jbcheb(x, -1.093681e+00, &tj, &tj1, &result, _state);
17891 0 : jarquebera_jbcheb(x, -1.695911e+00, &tj, &tj1, &result, _state);
17892 0 : jarquebera_jbcheb(x, -7.473192e-01, &tj, &tj1, &result, _state);
17893 0 : jarquebera_jbcheb(x, -1.203236e-01, &tj, &tj1, &result, _state);
17894 0 : jarquebera_jbcheb(x, 6.590379e-02, &tj, &tj1, &result, _state);
17895 0 : jarquebera_jbcheb(x, 6.291876e-02, &tj, &tj1, &result, _state);
17896 0 : jarquebera_jbcheb(x, 3.132007e-02, &tj, &tj1, &result, _state);
17897 0 : jarquebera_jbcheb(x, 9.411147e-03, &tj, &tj1, &result, _state);
17898 0 : jarquebera_jbcheb(x, -1.180067e-03, &tj, &tj1, &result, _state);
17899 0 : jarquebera_jbcheb(x, -3.487610e-03, &tj, &tj1, &result, _state);
17900 0 : jarquebera_jbcheb(x, -2.436561e-03, &tj, &tj1, &result, _state);
17901 0 : if( ae_fp_greater(result,(double)(0)) )
17902 : {
17903 0 : result = (double)(0);
17904 : }
17905 0 : return result;
17906 : }
17907 0 : if( ae_fp_less_eq(s,3.0000) )
17908 : {
17909 0 : x = 2*(s-1.400000)/1.600000-1;
17910 0 : tj = (double)(1);
17911 0 : tj1 = x;
17912 0 : jarquebera_jbcheb(x, -5.947854e+00, &tj, &tj1, &result, _state);
17913 0 : jarquebera_jbcheb(x, -2.772675e+00, &tj, &tj1, &result, _state);
17914 0 : jarquebera_jbcheb(x, -4.707912e-01, &tj, &tj1, &result, _state);
17915 0 : jarquebera_jbcheb(x, -1.691171e-01, &tj, &tj1, &result, _state);
17916 0 : jarquebera_jbcheb(x, -4.132795e-02, &tj, &tj1, &result, _state);
17917 0 : jarquebera_jbcheb(x, -1.481310e-02, &tj, &tj1, &result, _state);
17918 0 : jarquebera_jbcheb(x, 2.867536e-03, &tj, &tj1, &result, _state);
17919 0 : jarquebera_jbcheb(x, 8.772327e-04, &tj, &tj1, &result, _state);
17920 0 : jarquebera_jbcheb(x, 5.033387e-03, &tj, &tj1, &result, _state);
17921 0 : jarquebera_jbcheb(x, -1.378277e-03, &tj, &tj1, &result, _state);
17922 0 : jarquebera_jbcheb(x, -2.497964e-03, &tj, &tj1, &result, _state);
17923 0 : jarquebera_jbcheb(x, -3.636814e-03, &tj, &tj1, &result, _state);
17924 0 : jarquebera_jbcheb(x, -9.581640e-04, &tj, &tj1, &result, _state);
17925 0 : if( ae_fp_greater(result,(double)(0)) )
17926 : {
17927 0 : result = (double)(0);
17928 : }
17929 0 : return result;
17930 : }
17931 0 : if( ae_fp_less_eq(s,3.2000) )
17932 : {
17933 0 : x = 2*(s-3.000000)/0.200000-1;
17934 0 : tj = (double)(1);
17935 0 : tj1 = x;
17936 0 : jarquebera_jbcheb(x, -7.511008e+00, &tj, &tj1, &result, _state);
17937 0 : jarquebera_jbcheb(x, -8.140472e-01, &tj, &tj1, &result, _state);
17938 0 : jarquebera_jbcheb(x, 1.682053e+00, &tj, &tj1, &result, _state);
17939 0 : jarquebera_jbcheb(x, -2.568561e-02, &tj, &tj1, &result, _state);
17940 0 : jarquebera_jbcheb(x, -1.933930e+00, &tj, &tj1, &result, _state);
17941 0 : jarquebera_jbcheb(x, -8.140472e-01, &tj, &tj1, &result, _state);
17942 0 : jarquebera_jbcheb(x, -3.895025e+00, &tj, &tj1, &result, _state);
17943 0 : jarquebera_jbcheb(x, -8.140472e-01, &tj, &tj1, &result, _state);
17944 0 : jarquebera_jbcheb(x, -1.933930e+00, &tj, &tj1, &result, _state);
17945 0 : jarquebera_jbcheb(x, -2.568561e-02, &tj, &tj1, &result, _state);
17946 0 : jarquebera_jbcheb(x, 1.682053e+00, &tj, &tj1, &result, _state);
17947 0 : if( ae_fp_greater(result,(double)(0)) )
17948 : {
17949 0 : result = (double)(0);
17950 : }
17951 0 : return result;
17952 : }
17953 0 : result = -1.824116e+03*(s-3.200000e+00)-1.440330e+01;
17954 0 : return result;
17955 : }
17956 :
17957 :
17958 0 : static double jarquebera_jbtbl8(double s, ae_state *_state)
17959 : {
17960 : double x;
17961 : double tj;
17962 : double tj1;
17963 : double result;
17964 :
17965 :
17966 0 : result = (double)(0);
17967 0 : if( ae_fp_less_eq(s,1.3000) )
17968 : {
17969 0 : x = 2*(s-0.000000)/1.300000-1;
17970 0 : tj = (double)(1);
17971 0 : tj1 = x;
17972 0 : jarquebera_jbcheb(x, -7.199015e-01, &tj, &tj1, &result, _state);
17973 0 : jarquebera_jbcheb(x, -1.095921e+00, &tj, &tj1, &result, _state);
17974 0 : jarquebera_jbcheb(x, -4.736828e-01, &tj, &tj1, &result, _state);
17975 0 : jarquebera_jbcheb(x, -1.047438e-01, &tj, &tj1, &result, _state);
17976 0 : jarquebera_jbcheb(x, -2.484320e-03, &tj, &tj1, &result, _state);
17977 0 : jarquebera_jbcheb(x, 7.937923e-03, &tj, &tj1, &result, _state);
17978 0 : jarquebera_jbcheb(x, 4.810470e-03, &tj, &tj1, &result, _state);
17979 0 : jarquebera_jbcheb(x, 2.139780e-03, &tj, &tj1, &result, _state);
17980 0 : jarquebera_jbcheb(x, 6.708443e-04, &tj, &tj1, &result, _state);
17981 0 : if( ae_fp_greater(result,(double)(0)) )
17982 : {
17983 0 : result = (double)(0);
17984 : }
17985 0 : return result;
17986 : }
17987 0 : if( ae_fp_less_eq(s,2.0000) )
17988 : {
17989 0 : x = 2*(s-1.300000)/0.700000-1;
17990 0 : tj = (double)(1);
17991 0 : tj1 = x;
17992 0 : jarquebera_jbcheb(x, -3.378966e+00, &tj, &tj1, &result, _state);
17993 0 : jarquebera_jbcheb(x, -7.802461e-01, &tj, &tj1, &result, _state);
17994 0 : jarquebera_jbcheb(x, 1.547593e-01, &tj, &tj1, &result, _state);
17995 0 : jarquebera_jbcheb(x, -6.241042e-02, &tj, &tj1, &result, _state);
17996 0 : jarquebera_jbcheb(x, 1.203274e-02, &tj, &tj1, &result, _state);
17997 0 : jarquebera_jbcheb(x, 5.201990e-03, &tj, &tj1, &result, _state);
17998 0 : jarquebera_jbcheb(x, -5.125597e-03, &tj, &tj1, &result, _state);
17999 0 : jarquebera_jbcheb(x, 1.584426e-03, &tj, &tj1, &result, _state);
18000 0 : jarquebera_jbcheb(x, 2.546069e-04, &tj, &tj1, &result, _state);
18001 0 : if( ae_fp_greater(result,(double)(0)) )
18002 : {
18003 0 : result = (double)(0);
18004 : }
18005 0 : return result;
18006 : }
18007 0 : if( ae_fp_less_eq(s,5.0000) )
18008 : {
18009 0 : x = 2*(s-2.000000)/3.000000-1;
18010 0 : tj = (double)(1);
18011 0 : tj1 = x;
18012 0 : jarquebera_jbcheb(x, -6.828366e+00, &tj, &tj1, &result, _state);
18013 0 : jarquebera_jbcheb(x, -3.137533e+00, &tj, &tj1, &result, _state);
18014 0 : jarquebera_jbcheb(x, -5.016671e-01, &tj, &tj1, &result, _state);
18015 0 : jarquebera_jbcheb(x, -1.745637e-01, &tj, &tj1, &result, _state);
18016 0 : jarquebera_jbcheb(x, -5.189801e-02, &tj, &tj1, &result, _state);
18017 0 : jarquebera_jbcheb(x, -1.621610e-02, &tj, &tj1, &result, _state);
18018 0 : jarquebera_jbcheb(x, -6.741122e-03, &tj, &tj1, &result, _state);
18019 0 : jarquebera_jbcheb(x, -4.516368e-03, &tj, &tj1, &result, _state);
18020 0 : jarquebera_jbcheb(x, 3.552085e-04, &tj, &tj1, &result, _state);
18021 0 : jarquebera_jbcheb(x, 2.787029e-03, &tj, &tj1, &result, _state);
18022 0 : jarquebera_jbcheb(x, 5.359774e-03, &tj, &tj1, &result, _state);
18023 0 : if( ae_fp_greater(result,(double)(0)) )
18024 : {
18025 0 : result = (double)(0);
18026 : }
18027 0 : return result;
18028 : }
18029 0 : result = -5.087028e+00*(s-5.000000e+00)-1.071300e+01;
18030 0 : return result;
18031 : }
18032 :
18033 :
18034 0 : static double jarquebera_jbtbl9(double s, ae_state *_state)
18035 : {
18036 : double x;
18037 : double tj;
18038 : double tj1;
18039 : double result;
18040 :
18041 :
18042 0 : result = (double)(0);
18043 0 : if( ae_fp_less_eq(s,1.3000) )
18044 : {
18045 0 : x = 2*(s-0.000000)/1.300000-1;
18046 0 : tj = (double)(1);
18047 0 : tj1 = x;
18048 0 : jarquebera_jbcheb(x, -6.279320e-01, &tj, &tj1, &result, _state);
18049 0 : jarquebera_jbcheb(x, -9.277151e-01, &tj, &tj1, &result, _state);
18050 0 : jarquebera_jbcheb(x, -3.669339e-01, &tj, &tj1, &result, _state);
18051 0 : jarquebera_jbcheb(x, -7.086149e-02, &tj, &tj1, &result, _state);
18052 0 : jarquebera_jbcheb(x, -1.333816e-03, &tj, &tj1, &result, _state);
18053 0 : jarquebera_jbcheb(x, 3.871249e-03, &tj, &tj1, &result, _state);
18054 0 : jarquebera_jbcheb(x, 2.007048e-03, &tj, &tj1, &result, _state);
18055 0 : jarquebera_jbcheb(x, 7.482245e-04, &tj, &tj1, &result, _state);
18056 0 : jarquebera_jbcheb(x, 2.355615e-04, &tj, &tj1, &result, _state);
18057 0 : if( ae_fp_greater(result,(double)(0)) )
18058 : {
18059 0 : result = (double)(0);
18060 : }
18061 0 : return result;
18062 : }
18063 0 : if( ae_fp_less_eq(s,2.0000) )
18064 : {
18065 0 : x = 2*(s-1.300000)/0.700000-1;
18066 0 : tj = (double)(1);
18067 0 : tj1 = x;
18068 0 : jarquebera_jbcheb(x, -2.981430e+00, &tj, &tj1, &result, _state);
18069 0 : jarquebera_jbcheb(x, -7.972248e-01, &tj, &tj1, &result, _state);
18070 0 : jarquebera_jbcheb(x, 1.747737e-01, &tj, &tj1, &result, _state);
18071 0 : jarquebera_jbcheb(x, -3.808530e-02, &tj, &tj1, &result, _state);
18072 0 : jarquebera_jbcheb(x, -7.888305e-03, &tj, &tj1, &result, _state);
18073 0 : jarquebera_jbcheb(x, 9.001302e-03, &tj, &tj1, &result, _state);
18074 0 : jarquebera_jbcheb(x, -1.378767e-03, &tj, &tj1, &result, _state);
18075 0 : jarquebera_jbcheb(x, -1.108510e-03, &tj, &tj1, &result, _state);
18076 0 : jarquebera_jbcheb(x, 5.915372e-04, &tj, &tj1, &result, _state);
18077 0 : if( ae_fp_greater(result,(double)(0)) )
18078 : {
18079 0 : result = (double)(0);
18080 : }
18081 0 : return result;
18082 : }
18083 0 : if( ae_fp_less_eq(s,7.0000) )
18084 : {
18085 0 : x = 2*(s-2.000000)/5.000000-1;
18086 0 : tj = (double)(1);
18087 0 : tj1 = x;
18088 0 : jarquebera_jbcheb(x, -6.387463e+00, &tj, &tj1, &result, _state);
18089 0 : jarquebera_jbcheb(x, -2.845231e+00, &tj, &tj1, &result, _state);
18090 0 : jarquebera_jbcheb(x, -1.809956e-01, &tj, &tj1, &result, _state);
18091 0 : jarquebera_jbcheb(x, -7.543461e-02, &tj, &tj1, &result, _state);
18092 0 : jarquebera_jbcheb(x, -4.880397e-03, &tj, &tj1, &result, _state);
18093 0 : jarquebera_jbcheb(x, -1.160074e-02, &tj, &tj1, &result, _state);
18094 0 : jarquebera_jbcheb(x, -7.356527e-03, &tj, &tj1, &result, _state);
18095 0 : jarquebera_jbcheb(x, -4.394428e-03, &tj, &tj1, &result, _state);
18096 0 : jarquebera_jbcheb(x, 9.619892e-04, &tj, &tj1, &result, _state);
18097 0 : jarquebera_jbcheb(x, -2.758763e-04, &tj, &tj1, &result, _state);
18098 0 : jarquebera_jbcheb(x, 4.790977e-05, &tj, &tj1, &result, _state);
18099 0 : if( ae_fp_greater(result,(double)(0)) )
18100 : {
18101 0 : result = (double)(0);
18102 : }
18103 0 : return result;
18104 : }
18105 0 : result = -2.020952e+00*(s-7.000000e+00)-9.516623e+00;
18106 0 : return result;
18107 : }
18108 :
18109 :
18110 0 : static double jarquebera_jbtbl10(double s, ae_state *_state)
18111 : {
18112 : double x;
18113 : double tj;
18114 : double tj1;
18115 : double result;
18116 :
18117 :
18118 0 : result = (double)(0);
18119 0 : if( ae_fp_less_eq(s,1.2000) )
18120 : {
18121 0 : x = 2*(s-0.000000)/1.200000-1;
18122 0 : tj = (double)(1);
18123 0 : tj1 = x;
18124 0 : jarquebera_jbcheb(x, -4.590993e-01, &tj, &tj1, &result, _state);
18125 0 : jarquebera_jbcheb(x, -6.562730e-01, &tj, &tj1, &result, _state);
18126 0 : jarquebera_jbcheb(x, -2.353934e-01, &tj, &tj1, &result, _state);
18127 0 : jarquebera_jbcheb(x, -4.069933e-02, &tj, &tj1, &result, _state);
18128 0 : jarquebera_jbcheb(x, -1.849151e-03, &tj, &tj1, &result, _state);
18129 0 : jarquebera_jbcheb(x, 8.931406e-04, &tj, &tj1, &result, _state);
18130 0 : jarquebera_jbcheb(x, 3.636295e-04, &tj, &tj1, &result, _state);
18131 0 : jarquebera_jbcheb(x, 1.178340e-05, &tj, &tj1, &result, _state);
18132 0 : jarquebera_jbcheb(x, -8.917749e-05, &tj, &tj1, &result, _state);
18133 0 : if( ae_fp_greater(result,(double)(0)) )
18134 : {
18135 0 : result = (double)(0);
18136 : }
18137 0 : return result;
18138 : }
18139 0 : if( ae_fp_less_eq(s,2.0000) )
18140 : {
18141 0 : x = 2*(s-1.200000)/0.800000-1;
18142 0 : tj = (double)(1);
18143 0 : tj1 = x;
18144 0 : jarquebera_jbcheb(x, -2.537658e+00, &tj, &tj1, &result, _state);
18145 0 : jarquebera_jbcheb(x, -9.962401e-01, &tj, &tj1, &result, _state);
18146 0 : jarquebera_jbcheb(x, 1.838715e-01, &tj, &tj1, &result, _state);
18147 0 : jarquebera_jbcheb(x, 1.055792e-02, &tj, &tj1, &result, _state);
18148 0 : jarquebera_jbcheb(x, -2.580316e-02, &tj, &tj1, &result, _state);
18149 0 : jarquebera_jbcheb(x, 1.781701e-03, &tj, &tj1, &result, _state);
18150 0 : jarquebera_jbcheb(x, 3.770362e-03, &tj, &tj1, &result, _state);
18151 0 : jarquebera_jbcheb(x, -4.838983e-04, &tj, &tj1, &result, _state);
18152 0 : jarquebera_jbcheb(x, -6.999052e-04, &tj, &tj1, &result, _state);
18153 0 : if( ae_fp_greater(result,(double)(0)) )
18154 : {
18155 0 : result = (double)(0);
18156 : }
18157 0 : return result;
18158 : }
18159 0 : if( ae_fp_less_eq(s,7.0000) )
18160 : {
18161 0 : x = 2*(s-2.000000)/5.000000-1;
18162 0 : tj = (double)(1);
18163 0 : tj1 = x;
18164 0 : jarquebera_jbcheb(x, -5.337524e+00, &tj, &tj1, &result, _state);
18165 0 : jarquebera_jbcheb(x, -1.877029e+00, &tj, &tj1, &result, _state);
18166 0 : jarquebera_jbcheb(x, 4.734650e-02, &tj, &tj1, &result, _state);
18167 0 : jarquebera_jbcheb(x, -4.249254e-02, &tj, &tj1, &result, _state);
18168 0 : jarquebera_jbcheb(x, 3.320250e-03, &tj, &tj1, &result, _state);
18169 0 : jarquebera_jbcheb(x, -6.432266e-03, &tj, &tj1, &result, _state);
18170 0 : if( ae_fp_greater(result,(double)(0)) )
18171 : {
18172 0 : result = (double)(0);
18173 : }
18174 0 : return result;
18175 : }
18176 0 : result = -8.711035e-01*(s-7.000000e+00)-7.212811e+00;
18177 0 : return result;
18178 : }
18179 :
18180 :
18181 0 : static double jarquebera_jbtbl11(double s, ae_state *_state)
18182 : {
18183 : double x;
18184 : double tj;
18185 : double tj1;
18186 : double result;
18187 :
18188 :
18189 0 : result = (double)(0);
18190 0 : if( ae_fp_less_eq(s,1.2000) )
18191 : {
18192 0 : x = 2*(s-0.000000)/1.200000-1;
18193 0 : tj = (double)(1);
18194 0 : tj1 = x;
18195 0 : jarquebera_jbcheb(x, -4.339517e-01, &tj, &tj1, &result, _state);
18196 0 : jarquebera_jbcheb(x, -6.051558e-01, &tj, &tj1, &result, _state);
18197 0 : jarquebera_jbcheb(x, -2.000992e-01, &tj, &tj1, &result, _state);
18198 0 : jarquebera_jbcheb(x, -3.022547e-02, &tj, &tj1, &result, _state);
18199 0 : jarquebera_jbcheb(x, -9.808401e-04, &tj, &tj1, &result, _state);
18200 0 : jarquebera_jbcheb(x, 5.592870e-04, &tj, &tj1, &result, _state);
18201 0 : jarquebera_jbcheb(x, 3.575081e-04, &tj, &tj1, &result, _state);
18202 0 : jarquebera_jbcheb(x, 2.086173e-04, &tj, &tj1, &result, _state);
18203 0 : jarquebera_jbcheb(x, 6.089011e-05, &tj, &tj1, &result, _state);
18204 0 : if( ae_fp_greater(result,(double)(0)) )
18205 : {
18206 0 : result = (double)(0);
18207 : }
18208 0 : return result;
18209 : }
18210 0 : if( ae_fp_less_eq(s,2.2500) )
18211 : {
18212 0 : x = 2*(s-1.200000)/1.050000-1;
18213 0 : tj = (double)(1);
18214 0 : tj1 = x;
18215 0 : jarquebera_jbcheb(x, -2.523221e+00, &tj, &tj1, &result, _state);
18216 0 : jarquebera_jbcheb(x, -1.068388e+00, &tj, &tj1, &result, _state);
18217 0 : jarquebera_jbcheb(x, 2.179661e-01, &tj, &tj1, &result, _state);
18218 0 : jarquebera_jbcheb(x, -1.555524e-03, &tj, &tj1, &result, _state);
18219 0 : jarquebera_jbcheb(x, -3.238964e-02, &tj, &tj1, &result, _state);
18220 0 : jarquebera_jbcheb(x, 7.364320e-03, &tj, &tj1, &result, _state);
18221 0 : jarquebera_jbcheb(x, 4.895771e-03, &tj, &tj1, &result, _state);
18222 0 : jarquebera_jbcheb(x, -1.762774e-03, &tj, &tj1, &result, _state);
18223 0 : jarquebera_jbcheb(x, -8.201340e-04, &tj, &tj1, &result, _state);
18224 0 : if( ae_fp_greater(result,(double)(0)) )
18225 : {
18226 0 : result = (double)(0);
18227 : }
18228 0 : return result;
18229 : }
18230 0 : if( ae_fp_less_eq(s,8.0000) )
18231 : {
18232 0 : x = 2*(s-2.250000)/5.750000-1;
18233 0 : tj = (double)(1);
18234 0 : tj1 = x;
18235 0 : jarquebera_jbcheb(x, -5.212179e+00, &tj, &tj1, &result, _state);
18236 0 : jarquebera_jbcheb(x, -1.684579e+00, &tj, &tj1, &result, _state);
18237 0 : jarquebera_jbcheb(x, 8.299519e-02, &tj, &tj1, &result, _state);
18238 0 : jarquebera_jbcheb(x, -3.606261e-02, &tj, &tj1, &result, _state);
18239 0 : jarquebera_jbcheb(x, 7.310869e-03, &tj, &tj1, &result, _state);
18240 0 : jarquebera_jbcheb(x, -3.320115e-03, &tj, &tj1, &result, _state);
18241 0 : if( ae_fp_greater(result,(double)(0)) )
18242 : {
18243 0 : result = (double)(0);
18244 : }
18245 0 : return result;
18246 : }
18247 0 : result = -5.715445e-01*(s-8.000000e+00)-6.845834e+00;
18248 0 : return result;
18249 : }
18250 :
18251 :
18252 0 : static double jarquebera_jbtbl12(double s, ae_state *_state)
18253 : {
18254 : double x;
18255 : double tj;
18256 : double tj1;
18257 : double result;
18258 :
18259 :
18260 0 : result = (double)(0);
18261 0 : if( ae_fp_less_eq(s,1.0000) )
18262 : {
18263 0 : x = 2*(s-0.000000)/1.000000-1;
18264 0 : tj = (double)(1);
18265 0 : tj1 = x;
18266 0 : jarquebera_jbcheb(x, -2.736742e-01, &tj, &tj1, &result, _state);
18267 0 : jarquebera_jbcheb(x, -3.657836e-01, &tj, &tj1, &result, _state);
18268 0 : jarquebera_jbcheb(x, -1.047209e-01, &tj, &tj1, &result, _state);
18269 0 : jarquebera_jbcheb(x, -1.319599e-02, &tj, &tj1, &result, _state);
18270 0 : jarquebera_jbcheb(x, -5.545631e-04, &tj, &tj1, &result, _state);
18271 0 : jarquebera_jbcheb(x, 9.280445e-05, &tj, &tj1, &result, _state);
18272 0 : jarquebera_jbcheb(x, 2.815679e-05, &tj, &tj1, &result, _state);
18273 0 : jarquebera_jbcheb(x, -2.213519e-05, &tj, &tj1, &result, _state);
18274 0 : jarquebera_jbcheb(x, 1.256838e-05, &tj, &tj1, &result, _state);
18275 0 : if( ae_fp_greater(result,(double)(0)) )
18276 : {
18277 0 : result = (double)(0);
18278 : }
18279 0 : return result;
18280 : }
18281 0 : if( ae_fp_less_eq(s,3.0000) )
18282 : {
18283 0 : x = 2*(s-1.000000)/2.000000-1;
18284 0 : tj = (double)(1);
18285 0 : tj1 = x;
18286 0 : jarquebera_jbcheb(x, -2.573947e+00, &tj, &tj1, &result, _state);
18287 0 : jarquebera_jbcheb(x, -1.515287e+00, &tj, &tj1, &result, _state);
18288 0 : jarquebera_jbcheb(x, 3.611880e-01, &tj, &tj1, &result, _state);
18289 0 : jarquebera_jbcheb(x, -3.271311e-02, &tj, &tj1, &result, _state);
18290 0 : jarquebera_jbcheb(x, -6.495815e-02, &tj, &tj1, &result, _state);
18291 0 : jarquebera_jbcheb(x, 4.141186e-02, &tj, &tj1, &result, _state);
18292 0 : jarquebera_jbcheb(x, 7.180886e-04, &tj, &tj1, &result, _state);
18293 0 : jarquebera_jbcheb(x, -1.388211e-02, &tj, &tj1, &result, _state);
18294 0 : jarquebera_jbcheb(x, 4.890761e-03, &tj, &tj1, &result, _state);
18295 0 : jarquebera_jbcheb(x, 3.233175e-03, &tj, &tj1, &result, _state);
18296 0 : jarquebera_jbcheb(x, -2.946156e-03, &tj, &tj1, &result, _state);
18297 0 : if( ae_fp_greater(result,(double)(0)) )
18298 : {
18299 0 : result = (double)(0);
18300 : }
18301 0 : return result;
18302 : }
18303 0 : if( ae_fp_less_eq(s,12.0000) )
18304 : {
18305 0 : x = 2*(s-3.000000)/9.000000-1;
18306 0 : tj = (double)(1);
18307 0 : tj1 = x;
18308 0 : jarquebera_jbcheb(x, -5.947819e+00, &tj, &tj1, &result, _state);
18309 0 : jarquebera_jbcheb(x, -2.034157e+00, &tj, &tj1, &result, _state);
18310 0 : jarquebera_jbcheb(x, 6.878986e-02, &tj, &tj1, &result, _state);
18311 0 : jarquebera_jbcheb(x, -4.078603e-02, &tj, &tj1, &result, _state);
18312 0 : jarquebera_jbcheb(x, 6.990977e-03, &tj, &tj1, &result, _state);
18313 0 : jarquebera_jbcheb(x, -2.866215e-03, &tj, &tj1, &result, _state);
18314 0 : jarquebera_jbcheb(x, 3.897866e-03, &tj, &tj1, &result, _state);
18315 0 : jarquebera_jbcheb(x, 2.512252e-03, &tj, &tj1, &result, _state);
18316 0 : jarquebera_jbcheb(x, 2.073743e-03, &tj, &tj1, &result, _state);
18317 0 : jarquebera_jbcheb(x, 3.022621e-03, &tj, &tj1, &result, _state);
18318 0 : jarquebera_jbcheb(x, 1.501343e-03, &tj, &tj1, &result, _state);
18319 0 : if( ae_fp_greater(result,(double)(0)) )
18320 : {
18321 0 : result = (double)(0);
18322 : }
18323 0 : return result;
18324 : }
18325 0 : result = -2.877243e-01*(s-1.200000e+01)-7.936839e+00;
18326 0 : return result;
18327 : }
18328 :
18329 :
18330 0 : static double jarquebera_jbtbl13(double s, ae_state *_state)
18331 : {
18332 : double x;
18333 : double tj;
18334 : double tj1;
18335 : double result;
18336 :
18337 :
18338 0 : result = (double)(0);
18339 0 : if( ae_fp_less_eq(s,1.0000) )
18340 : {
18341 0 : x = 2*(s-0.000000)/1.000000-1;
18342 0 : tj = (double)(1);
18343 0 : tj1 = x;
18344 0 : jarquebera_jbcheb(x, -2.713276e-01, &tj, &tj1, &result, _state);
18345 0 : jarquebera_jbcheb(x, -3.557541e-01, &tj, &tj1, &result, _state);
18346 0 : jarquebera_jbcheb(x, -9.459092e-02, &tj, &tj1, &result, _state);
18347 0 : jarquebera_jbcheb(x, -1.044145e-02, &tj, &tj1, &result, _state);
18348 0 : jarquebera_jbcheb(x, -2.546132e-04, &tj, &tj1, &result, _state);
18349 0 : jarquebera_jbcheb(x, 1.002374e-04, &tj, &tj1, &result, _state);
18350 0 : jarquebera_jbcheb(x, 2.349456e-05, &tj, &tj1, &result, _state);
18351 0 : jarquebera_jbcheb(x, -7.025669e-05, &tj, &tj1, &result, _state);
18352 0 : jarquebera_jbcheb(x, -1.590242e-05, &tj, &tj1, &result, _state);
18353 0 : if( ae_fp_greater(result,(double)(0)) )
18354 : {
18355 0 : result = (double)(0);
18356 : }
18357 0 : return result;
18358 : }
18359 0 : if( ae_fp_less_eq(s,3.0000) )
18360 : {
18361 0 : x = 2*(s-1.000000)/2.000000-1;
18362 0 : tj = (double)(1);
18363 0 : tj1 = x;
18364 0 : jarquebera_jbcheb(x, -2.454383e+00, &tj, &tj1, &result, _state);
18365 0 : jarquebera_jbcheb(x, -1.467539e+00, &tj, &tj1, &result, _state);
18366 0 : jarquebera_jbcheb(x, 3.270774e-01, &tj, &tj1, &result, _state);
18367 0 : jarquebera_jbcheb(x, -8.075763e-03, &tj, &tj1, &result, _state);
18368 0 : jarquebera_jbcheb(x, -6.611647e-02, &tj, &tj1, &result, _state);
18369 0 : jarquebera_jbcheb(x, 2.990785e-02, &tj, &tj1, &result, _state);
18370 0 : jarquebera_jbcheb(x, 8.109212e-03, &tj, &tj1, &result, _state);
18371 0 : jarquebera_jbcheb(x, -1.135031e-02, &tj, &tj1, &result, _state);
18372 0 : jarquebera_jbcheb(x, 5.915919e-04, &tj, &tj1, &result, _state);
18373 0 : jarquebera_jbcheb(x, 3.522390e-03, &tj, &tj1, &result, _state);
18374 0 : jarquebera_jbcheb(x, -1.144701e-03, &tj, &tj1, &result, _state);
18375 0 : if( ae_fp_greater(result,(double)(0)) )
18376 : {
18377 0 : result = (double)(0);
18378 : }
18379 0 : return result;
18380 : }
18381 0 : if( ae_fp_less_eq(s,13.0000) )
18382 : {
18383 0 : x = 2*(s-3.000000)/10.000000-1;
18384 0 : tj = (double)(1);
18385 0 : tj1 = x;
18386 0 : jarquebera_jbcheb(x, -5.736127e+00, &tj, &tj1, &result, _state);
18387 0 : jarquebera_jbcheb(x, -1.920809e+00, &tj, &tj1, &result, _state);
18388 0 : jarquebera_jbcheb(x, 1.175858e-01, &tj, &tj1, &result, _state);
18389 0 : jarquebera_jbcheb(x, -4.002049e-02, &tj, &tj1, &result, _state);
18390 0 : jarquebera_jbcheb(x, 1.158966e-02, &tj, &tj1, &result, _state);
18391 0 : jarquebera_jbcheb(x, -3.157781e-03, &tj, &tj1, &result, _state);
18392 0 : jarquebera_jbcheb(x, 2.762172e-03, &tj, &tj1, &result, _state);
18393 0 : jarquebera_jbcheb(x, 5.780347e-04, &tj, &tj1, &result, _state);
18394 0 : jarquebera_jbcheb(x, -1.193310e-03, &tj, &tj1, &result, _state);
18395 0 : jarquebera_jbcheb(x, -2.442421e-05, &tj, &tj1, &result, _state);
18396 0 : jarquebera_jbcheb(x, 2.547756e-03, &tj, &tj1, &result, _state);
18397 0 : if( ae_fp_greater(result,(double)(0)) )
18398 : {
18399 0 : result = (double)(0);
18400 : }
18401 0 : return result;
18402 : }
18403 0 : result = -2.799944e-01*(s-1.300000e+01)-7.566269e+00;
18404 0 : return result;
18405 : }
18406 :
18407 :
18408 0 : static double jarquebera_jbtbl14(double s, ae_state *_state)
18409 : {
18410 : double x;
18411 : double tj;
18412 : double tj1;
18413 : double result;
18414 :
18415 :
18416 0 : result = (double)(0);
18417 0 : if( ae_fp_less_eq(s,1.0000) )
18418 : {
18419 0 : x = 2*(s-0.000000)/1.000000-1;
18420 0 : tj = (double)(1);
18421 0 : tj1 = x;
18422 0 : jarquebera_jbcheb(x, -2.698527e-01, &tj, &tj1, &result, _state);
18423 0 : jarquebera_jbcheb(x, -3.479081e-01, &tj, &tj1, &result, _state);
18424 0 : jarquebera_jbcheb(x, -8.640733e-02, &tj, &tj1, &result, _state);
18425 0 : jarquebera_jbcheb(x, -8.466899e-03, &tj, &tj1, &result, _state);
18426 0 : jarquebera_jbcheb(x, -1.469485e-04, &tj, &tj1, &result, _state);
18427 0 : jarquebera_jbcheb(x, 2.150009e-05, &tj, &tj1, &result, _state);
18428 0 : jarquebera_jbcheb(x, 1.965975e-05, &tj, &tj1, &result, _state);
18429 0 : jarquebera_jbcheb(x, -4.710210e-05, &tj, &tj1, &result, _state);
18430 0 : jarquebera_jbcheb(x, -1.327808e-05, &tj, &tj1, &result, _state);
18431 0 : if( ae_fp_greater(result,(double)(0)) )
18432 : {
18433 0 : result = (double)(0);
18434 : }
18435 0 : return result;
18436 : }
18437 0 : if( ae_fp_less_eq(s,3.0000) )
18438 : {
18439 0 : x = 2*(s-1.000000)/2.000000-1;
18440 0 : tj = (double)(1);
18441 0 : tj1 = x;
18442 0 : jarquebera_jbcheb(x, -2.350359e+00, &tj, &tj1, &result, _state);
18443 0 : jarquebera_jbcheb(x, -1.421365e+00, &tj, &tj1, &result, _state);
18444 0 : jarquebera_jbcheb(x, 2.960468e-01, &tj, &tj1, &result, _state);
18445 0 : jarquebera_jbcheb(x, 1.149167e-02, &tj, &tj1, &result, _state);
18446 0 : jarquebera_jbcheb(x, -6.361109e-02, &tj, &tj1, &result, _state);
18447 0 : jarquebera_jbcheb(x, 1.976022e-02, &tj, &tj1, &result, _state);
18448 0 : jarquebera_jbcheb(x, 1.082700e-02, &tj, &tj1, &result, _state);
18449 0 : jarquebera_jbcheb(x, -8.563328e-03, &tj, &tj1, &result, _state);
18450 0 : jarquebera_jbcheb(x, -1.453123e-03, &tj, &tj1, &result, _state);
18451 0 : jarquebera_jbcheb(x, 2.917559e-03, &tj, &tj1, &result, _state);
18452 0 : jarquebera_jbcheb(x, -1.151067e-05, &tj, &tj1, &result, _state);
18453 0 : if( ae_fp_greater(result,(double)(0)) )
18454 : {
18455 0 : result = (double)(0);
18456 : }
18457 0 : return result;
18458 : }
18459 0 : if( ae_fp_less_eq(s,15.0000) )
18460 : {
18461 0 : x = 2*(s-3.000000)/12.000000-1;
18462 0 : tj = (double)(1);
18463 0 : tj1 = x;
18464 0 : jarquebera_jbcheb(x, -5.746892e+00, &tj, &tj1, &result, _state);
18465 0 : jarquebera_jbcheb(x, -2.010441e+00, &tj, &tj1, &result, _state);
18466 0 : jarquebera_jbcheb(x, 1.566146e-01, &tj, &tj1, &result, _state);
18467 0 : jarquebera_jbcheb(x, -5.129690e-02, &tj, &tj1, &result, _state);
18468 0 : jarquebera_jbcheb(x, 1.929724e-02, &tj, &tj1, &result, _state);
18469 0 : jarquebera_jbcheb(x, -2.524227e-03, &tj, &tj1, &result, _state);
18470 0 : jarquebera_jbcheb(x, 3.192933e-03, &tj, &tj1, &result, _state);
18471 0 : jarquebera_jbcheb(x, -4.254730e-04, &tj, &tj1, &result, _state);
18472 0 : jarquebera_jbcheb(x, 1.620685e-03, &tj, &tj1, &result, _state);
18473 0 : jarquebera_jbcheb(x, 7.289618e-04, &tj, &tj1, &result, _state);
18474 0 : jarquebera_jbcheb(x, -2.112350e-03, &tj, &tj1, &result, _state);
18475 0 : if( ae_fp_greater(result,(double)(0)) )
18476 : {
18477 0 : result = (double)(0);
18478 : }
18479 0 : return result;
18480 : }
18481 0 : result = -2.590621e-01*(s-1.500000e+01)-7.632238e+00;
18482 0 : return result;
18483 : }
18484 :
18485 :
18486 0 : static double jarquebera_jbtbl15(double s, ae_state *_state)
18487 : {
18488 : double x;
18489 : double tj;
18490 : double tj1;
18491 : double result;
18492 :
18493 :
18494 0 : result = (double)(0);
18495 0 : if( ae_fp_less_eq(s,2.0000) )
18496 : {
18497 0 : x = 2*(s-0.000000)/2.000000-1;
18498 0 : tj = (double)(1);
18499 0 : tj1 = x;
18500 0 : jarquebera_jbcheb(x, -1.043660e+00, &tj, &tj1, &result, _state);
18501 0 : jarquebera_jbcheb(x, -1.361653e+00, &tj, &tj1, &result, _state);
18502 0 : jarquebera_jbcheb(x, -3.009497e-01, &tj, &tj1, &result, _state);
18503 0 : jarquebera_jbcheb(x, 4.951784e-02, &tj, &tj1, &result, _state);
18504 0 : jarquebera_jbcheb(x, 4.377903e-02, &tj, &tj1, &result, _state);
18505 0 : jarquebera_jbcheb(x, 1.003253e-02, &tj, &tj1, &result, _state);
18506 0 : jarquebera_jbcheb(x, -1.271309e-03, &tj, &tj1, &result, _state);
18507 0 : if( ae_fp_greater(result,(double)(0)) )
18508 : {
18509 0 : result = (double)(0);
18510 : }
18511 0 : return result;
18512 : }
18513 0 : if( ae_fp_less_eq(s,5.0000) )
18514 : {
18515 0 : x = 2*(s-2.000000)/3.000000-1;
18516 0 : tj = (double)(1);
18517 0 : tj1 = x;
18518 0 : jarquebera_jbcheb(x, -3.582778e+00, &tj, &tj1, &result, _state);
18519 0 : jarquebera_jbcheb(x, -8.349578e-01, &tj, &tj1, &result, _state);
18520 0 : jarquebera_jbcheb(x, 9.476514e-02, &tj, &tj1, &result, _state);
18521 0 : jarquebera_jbcheb(x, -2.717385e-02, &tj, &tj1, &result, _state);
18522 0 : jarquebera_jbcheb(x, 1.222591e-02, &tj, &tj1, &result, _state);
18523 0 : jarquebera_jbcheb(x, -6.635124e-03, &tj, &tj1, &result, _state);
18524 0 : jarquebera_jbcheb(x, 2.815993e-03, &tj, &tj1, &result, _state);
18525 0 : if( ae_fp_greater(result,(double)(0)) )
18526 : {
18527 0 : result = (double)(0);
18528 : }
18529 0 : return result;
18530 : }
18531 0 : if( ae_fp_less_eq(s,17.0000) )
18532 : {
18533 0 : x = 2*(s-5.000000)/12.000000-1;
18534 0 : tj = (double)(1);
18535 0 : tj1 = x;
18536 0 : jarquebera_jbcheb(x, -6.115476e+00, &tj, &tj1, &result, _state);
18537 0 : jarquebera_jbcheb(x, -1.655936e+00, &tj, &tj1, &result, _state);
18538 0 : jarquebera_jbcheb(x, 8.404310e-02, &tj, &tj1, &result, _state);
18539 0 : jarquebera_jbcheb(x, -2.663794e-02, &tj, &tj1, &result, _state);
18540 0 : jarquebera_jbcheb(x, 8.868618e-03, &tj, &tj1, &result, _state);
18541 0 : jarquebera_jbcheb(x, 1.381447e-03, &tj, &tj1, &result, _state);
18542 0 : jarquebera_jbcheb(x, 9.444801e-04, &tj, &tj1, &result, _state);
18543 0 : jarquebera_jbcheb(x, -1.581503e-04, &tj, &tj1, &result, _state);
18544 0 : jarquebera_jbcheb(x, -9.468696e-04, &tj, &tj1, &result, _state);
18545 0 : jarquebera_jbcheb(x, 1.728509e-03, &tj, &tj1, &result, _state);
18546 0 : jarquebera_jbcheb(x, 1.206470e-03, &tj, &tj1, &result, _state);
18547 0 : if( ae_fp_greater(result,(double)(0)) )
18548 : {
18549 0 : result = (double)(0);
18550 : }
18551 0 : return result;
18552 : }
18553 0 : result = -1.927937e-01*(s-1.700000e+01)-7.700983e+00;
18554 0 : return result;
18555 : }
18556 :
18557 :
18558 0 : static double jarquebera_jbtbl16(double s, ae_state *_state)
18559 : {
18560 : double x;
18561 : double tj;
18562 : double tj1;
18563 : double result;
18564 :
18565 :
18566 0 : result = (double)(0);
18567 0 : if( ae_fp_less_eq(s,2.0000) )
18568 : {
18569 0 : x = 2*(s-0.000000)/2.000000-1;
18570 0 : tj = (double)(1);
18571 0 : tj1 = x;
18572 0 : jarquebera_jbcheb(x, -1.002570e+00, &tj, &tj1, &result, _state);
18573 0 : jarquebera_jbcheb(x, -1.298141e+00, &tj, &tj1, &result, _state);
18574 0 : jarquebera_jbcheb(x, -2.832803e-01, &tj, &tj1, &result, _state);
18575 0 : jarquebera_jbcheb(x, 3.877026e-02, &tj, &tj1, &result, _state);
18576 0 : jarquebera_jbcheb(x, 3.539436e-02, &tj, &tj1, &result, _state);
18577 0 : jarquebera_jbcheb(x, 8.439658e-03, &tj, &tj1, &result, _state);
18578 0 : jarquebera_jbcheb(x, -4.756911e-04, &tj, &tj1, &result, _state);
18579 0 : if( ae_fp_greater(result,(double)(0)) )
18580 : {
18581 0 : result = (double)(0);
18582 : }
18583 0 : return result;
18584 : }
18585 0 : if( ae_fp_less_eq(s,5.0000) )
18586 : {
18587 0 : x = 2*(s-2.000000)/3.000000-1;
18588 0 : tj = (double)(1);
18589 0 : tj1 = x;
18590 0 : jarquebera_jbcheb(x, -3.486198e+00, &tj, &tj1, &result, _state);
18591 0 : jarquebera_jbcheb(x, -8.242944e-01, &tj, &tj1, &result, _state);
18592 0 : jarquebera_jbcheb(x, 1.020002e-01, &tj, &tj1, &result, _state);
18593 0 : jarquebera_jbcheb(x, -3.130531e-02, &tj, &tj1, &result, _state);
18594 0 : jarquebera_jbcheb(x, 1.512373e-02, &tj, &tj1, &result, _state);
18595 0 : jarquebera_jbcheb(x, -8.054876e-03, &tj, &tj1, &result, _state);
18596 0 : jarquebera_jbcheb(x, 3.556839e-03, &tj, &tj1, &result, _state);
18597 0 : if( ae_fp_greater(result,(double)(0)) )
18598 : {
18599 0 : result = (double)(0);
18600 : }
18601 0 : return result;
18602 : }
18603 0 : if( ae_fp_less_eq(s,20.0000) )
18604 : {
18605 0 : x = 2*(s-5.000000)/15.000000-1;
18606 0 : tj = (double)(1);
18607 0 : tj1 = x;
18608 0 : jarquebera_jbcheb(x, -6.241608e+00, &tj, &tj1, &result, _state);
18609 0 : jarquebera_jbcheb(x, -1.832655e+00, &tj, &tj1, &result, _state);
18610 0 : jarquebera_jbcheb(x, 1.340545e-01, &tj, &tj1, &result, _state);
18611 0 : jarquebera_jbcheb(x, -3.361143e-02, &tj, &tj1, &result, _state);
18612 0 : jarquebera_jbcheb(x, 1.283219e-02, &tj, &tj1, &result, _state);
18613 0 : jarquebera_jbcheb(x, 3.484549e-03, &tj, &tj1, &result, _state);
18614 0 : jarquebera_jbcheb(x, 1.805968e-03, &tj, &tj1, &result, _state);
18615 0 : jarquebera_jbcheb(x, -2.057243e-03, &tj, &tj1, &result, _state);
18616 0 : jarquebera_jbcheb(x, -1.454439e-03, &tj, &tj1, &result, _state);
18617 0 : jarquebera_jbcheb(x, -2.177513e-03, &tj, &tj1, &result, _state);
18618 0 : jarquebera_jbcheb(x, -1.819209e-03, &tj, &tj1, &result, _state);
18619 0 : if( ae_fp_greater(result,(double)(0)) )
18620 : {
18621 0 : result = (double)(0);
18622 : }
18623 0 : return result;
18624 : }
18625 0 : result = -2.391580e-01*(s-2.000000e+01)-7.963205e+00;
18626 0 : return result;
18627 : }
18628 :
18629 :
18630 0 : static double jarquebera_jbtbl17(double s, ae_state *_state)
18631 : {
18632 : double x;
18633 : double tj;
18634 : double tj1;
18635 : double result;
18636 :
18637 :
18638 0 : result = (double)(0);
18639 0 : if( ae_fp_less_eq(s,3.0000) )
18640 : {
18641 0 : x = 2*(s-0.000000)/3.000000-1;
18642 0 : tj = (double)(1);
18643 0 : tj1 = x;
18644 0 : jarquebera_jbcheb(x, -1.566973e+00, &tj, &tj1, &result, _state);
18645 0 : jarquebera_jbcheb(x, -1.810330e+00, &tj, &tj1, &result, _state);
18646 0 : jarquebera_jbcheb(x, -4.840039e-02, &tj, &tj1, &result, _state);
18647 0 : jarquebera_jbcheb(x, 2.337294e-01, &tj, &tj1, &result, _state);
18648 0 : jarquebera_jbcheb(x, -5.383549e-04, &tj, &tj1, &result, _state);
18649 0 : jarquebera_jbcheb(x, -5.556515e-02, &tj, &tj1, &result, _state);
18650 0 : jarquebera_jbcheb(x, -8.656965e-03, &tj, &tj1, &result, _state);
18651 0 : jarquebera_jbcheb(x, 1.404569e-02, &tj, &tj1, &result, _state);
18652 0 : jarquebera_jbcheb(x, 6.447867e-03, &tj, &tj1, &result, _state);
18653 0 : if( ae_fp_greater(result,(double)(0)) )
18654 : {
18655 0 : result = (double)(0);
18656 : }
18657 0 : return result;
18658 : }
18659 0 : if( ae_fp_less_eq(s,6.0000) )
18660 : {
18661 0 : x = 2*(s-3.000000)/3.000000-1;
18662 0 : tj = (double)(1);
18663 0 : tj1 = x;
18664 0 : jarquebera_jbcheb(x, -3.905684e+00, &tj, &tj1, &result, _state);
18665 0 : jarquebera_jbcheb(x, -6.222920e-01, &tj, &tj1, &result, _state);
18666 0 : jarquebera_jbcheb(x, 4.146667e-02, &tj, &tj1, &result, _state);
18667 0 : jarquebera_jbcheb(x, -4.809176e-03, &tj, &tj1, &result, _state);
18668 0 : jarquebera_jbcheb(x, 1.057028e-03, &tj, &tj1, &result, _state);
18669 0 : jarquebera_jbcheb(x, -1.211838e-04, &tj, &tj1, &result, _state);
18670 0 : jarquebera_jbcheb(x, -4.099683e-04, &tj, &tj1, &result, _state);
18671 0 : jarquebera_jbcheb(x, 1.161105e-04, &tj, &tj1, &result, _state);
18672 0 : jarquebera_jbcheb(x, 2.225465e-04, &tj, &tj1, &result, _state);
18673 0 : if( ae_fp_greater(result,(double)(0)) )
18674 : {
18675 0 : result = (double)(0);
18676 : }
18677 0 : return result;
18678 : }
18679 0 : if( ae_fp_less_eq(s,24.0000) )
18680 : {
18681 0 : x = 2*(s-6.000000)/18.000000-1;
18682 0 : tj = (double)(1);
18683 0 : tj1 = x;
18684 0 : jarquebera_jbcheb(x, -6.594282e+00, &tj, &tj1, &result, _state);
18685 0 : jarquebera_jbcheb(x, -1.917838e+00, &tj, &tj1, &result, _state);
18686 0 : jarquebera_jbcheb(x, 1.455980e-01, &tj, &tj1, &result, _state);
18687 0 : jarquebera_jbcheb(x, -2.999589e-02, &tj, &tj1, &result, _state);
18688 0 : jarquebera_jbcheb(x, 5.604263e-03, &tj, &tj1, &result, _state);
18689 0 : jarquebera_jbcheb(x, -3.484445e-03, &tj, &tj1, &result, _state);
18690 0 : jarquebera_jbcheb(x, -1.819937e-03, &tj, &tj1, &result, _state);
18691 0 : jarquebera_jbcheb(x, -2.930390e-03, &tj, &tj1, &result, _state);
18692 0 : jarquebera_jbcheb(x, 2.771761e-04, &tj, &tj1, &result, _state);
18693 0 : jarquebera_jbcheb(x, -6.232581e-04, &tj, &tj1, &result, _state);
18694 0 : jarquebera_jbcheb(x, -7.029083e-04, &tj, &tj1, &result, _state);
18695 0 : if( ae_fp_greater(result,(double)(0)) )
18696 : {
18697 0 : result = (double)(0);
18698 : }
18699 0 : return result;
18700 : }
18701 0 : result = -2.127771e-01*(s-2.400000e+01)-8.400197e+00;
18702 0 : return result;
18703 : }
18704 :
18705 :
18706 0 : static double jarquebera_jbtbl18(double s, ae_state *_state)
18707 : {
18708 : double x;
18709 : double tj;
18710 : double tj1;
18711 : double result;
18712 :
18713 :
18714 0 : result = (double)(0);
18715 0 : if( ae_fp_less_eq(s,3.0000) )
18716 : {
18717 0 : x = 2*(s-0.000000)/3.000000-1;
18718 0 : tj = (double)(1);
18719 0 : tj1 = x;
18720 0 : jarquebera_jbcheb(x, -1.526802e+00, &tj, &tj1, &result, _state);
18721 0 : jarquebera_jbcheb(x, -1.762373e+00, &tj, &tj1, &result, _state);
18722 0 : jarquebera_jbcheb(x, -5.598890e-02, &tj, &tj1, &result, _state);
18723 0 : jarquebera_jbcheb(x, 2.189437e-01, &tj, &tj1, &result, _state);
18724 0 : jarquebera_jbcheb(x, 5.971721e-03, &tj, &tj1, &result, _state);
18725 0 : jarquebera_jbcheb(x, -4.823067e-02, &tj, &tj1, &result, _state);
18726 0 : jarquebera_jbcheb(x, -1.064501e-02, &tj, &tj1, &result, _state);
18727 0 : jarquebera_jbcheb(x, 1.014932e-02, &tj, &tj1, &result, _state);
18728 0 : jarquebera_jbcheb(x, 5.953513e-03, &tj, &tj1, &result, _state);
18729 0 : if( ae_fp_greater(result,(double)(0)) )
18730 : {
18731 0 : result = (double)(0);
18732 : }
18733 0 : return result;
18734 : }
18735 0 : if( ae_fp_less_eq(s,6.0000) )
18736 : {
18737 0 : x = 2*(s-3.000000)/3.000000-1;
18738 0 : tj = (double)(1);
18739 0 : tj1 = x;
18740 0 : jarquebera_jbcheb(x, -3.818669e+00, &tj, &tj1, &result, _state);
18741 0 : jarquebera_jbcheb(x, -6.070918e-01, &tj, &tj1, &result, _state);
18742 0 : jarquebera_jbcheb(x, 4.277196e-02, &tj, &tj1, &result, _state);
18743 0 : jarquebera_jbcheb(x, -4.879817e-03, &tj, &tj1, &result, _state);
18744 0 : jarquebera_jbcheb(x, 6.887357e-04, &tj, &tj1, &result, _state);
18745 0 : jarquebera_jbcheb(x, 1.638451e-05, &tj, &tj1, &result, _state);
18746 0 : jarquebera_jbcheb(x, 1.502800e-04, &tj, &tj1, &result, _state);
18747 0 : jarquebera_jbcheb(x, -3.165796e-05, &tj, &tj1, &result, _state);
18748 0 : jarquebera_jbcheb(x, 5.034960e-05, &tj, &tj1, &result, _state);
18749 0 : if( ae_fp_greater(result,(double)(0)) )
18750 : {
18751 0 : result = (double)(0);
18752 : }
18753 0 : return result;
18754 : }
18755 0 : if( ae_fp_less_eq(s,20.0000) )
18756 : {
18757 0 : x = 2*(s-6.000000)/14.000000-1;
18758 0 : tj = (double)(1);
18759 0 : tj1 = x;
18760 0 : jarquebera_jbcheb(x, -6.010656e+00, &tj, &tj1, &result, _state);
18761 0 : jarquebera_jbcheb(x, -1.496296e+00, &tj, &tj1, &result, _state);
18762 0 : jarquebera_jbcheb(x, 1.002227e-01, &tj, &tj1, &result, _state);
18763 0 : jarquebera_jbcheb(x, -2.338250e-02, &tj, &tj1, &result, _state);
18764 0 : jarquebera_jbcheb(x, 4.137036e-03, &tj, &tj1, &result, _state);
18765 0 : jarquebera_jbcheb(x, -2.586202e-03, &tj, &tj1, &result, _state);
18766 0 : jarquebera_jbcheb(x, -9.736384e-04, &tj, &tj1, &result, _state);
18767 0 : jarquebera_jbcheb(x, 1.332251e-03, &tj, &tj1, &result, _state);
18768 0 : jarquebera_jbcheb(x, 1.877982e-03, &tj, &tj1, &result, _state);
18769 0 : jarquebera_jbcheb(x, -1.160963e-05, &tj, &tj1, &result, _state);
18770 0 : jarquebera_jbcheb(x, -2.547247e-03, &tj, &tj1, &result, _state);
18771 0 : if( ae_fp_greater(result,(double)(0)) )
18772 : {
18773 0 : result = (double)(0);
18774 : }
18775 0 : return result;
18776 : }
18777 0 : result = -1.684623e-01*(s-2.000000e+01)-7.428883e+00;
18778 0 : return result;
18779 : }
18780 :
18781 :
18782 0 : static double jarquebera_jbtbl19(double s, ae_state *_state)
18783 : {
18784 : double x;
18785 : double tj;
18786 : double tj1;
18787 : double result;
18788 :
18789 :
18790 0 : result = (double)(0);
18791 0 : if( ae_fp_less_eq(s,3.0000) )
18792 : {
18793 0 : x = 2*(s-0.000000)/3.000000-1;
18794 0 : tj = (double)(1);
18795 0 : tj1 = x;
18796 0 : jarquebera_jbcheb(x, -1.490213e+00, &tj, &tj1, &result, _state);
18797 0 : jarquebera_jbcheb(x, -1.719633e+00, &tj, &tj1, &result, _state);
18798 0 : jarquebera_jbcheb(x, -6.459123e-02, &tj, &tj1, &result, _state);
18799 0 : jarquebera_jbcheb(x, 2.034878e-01, &tj, &tj1, &result, _state);
18800 0 : jarquebera_jbcheb(x, 1.113868e-02, &tj, &tj1, &result, _state);
18801 0 : jarquebera_jbcheb(x, -4.030922e-02, &tj, &tj1, &result, _state);
18802 0 : jarquebera_jbcheb(x, -1.054022e-02, &tj, &tj1, &result, _state);
18803 0 : jarquebera_jbcheb(x, 7.525623e-03, &tj, &tj1, &result, _state);
18804 0 : jarquebera_jbcheb(x, 5.277360e-03, &tj, &tj1, &result, _state);
18805 0 : if( ae_fp_greater(result,(double)(0)) )
18806 : {
18807 0 : result = (double)(0);
18808 : }
18809 0 : return result;
18810 : }
18811 0 : if( ae_fp_less_eq(s,6.0000) )
18812 : {
18813 0 : x = 2*(s-3.000000)/3.000000-1;
18814 0 : tj = (double)(1);
18815 0 : tj1 = x;
18816 0 : jarquebera_jbcheb(x, -3.744750e+00, &tj, &tj1, &result, _state);
18817 0 : jarquebera_jbcheb(x, -5.977749e-01, &tj, &tj1, &result, _state);
18818 0 : jarquebera_jbcheb(x, 4.223716e-02, &tj, &tj1, &result, _state);
18819 0 : jarquebera_jbcheb(x, -5.363889e-03, &tj, &tj1, &result, _state);
18820 0 : jarquebera_jbcheb(x, 5.711774e-04, &tj, &tj1, &result, _state);
18821 0 : jarquebera_jbcheb(x, -5.557257e-04, &tj, &tj1, &result, _state);
18822 0 : jarquebera_jbcheb(x, 4.254794e-04, &tj, &tj1, &result, _state);
18823 0 : jarquebera_jbcheb(x, 9.034207e-05, &tj, &tj1, &result, _state);
18824 0 : jarquebera_jbcheb(x, 5.498107e-05, &tj, &tj1, &result, _state);
18825 0 : if( ae_fp_greater(result,(double)(0)) )
18826 : {
18827 0 : result = (double)(0);
18828 : }
18829 0 : return result;
18830 : }
18831 0 : if( ae_fp_less_eq(s,20.0000) )
18832 : {
18833 0 : x = 2*(s-6.000000)/14.000000-1;
18834 0 : tj = (double)(1);
18835 0 : tj1 = x;
18836 0 : jarquebera_jbcheb(x, -5.872768e+00, &tj, &tj1, &result, _state);
18837 0 : jarquebera_jbcheb(x, -1.430689e+00, &tj, &tj1, &result, _state);
18838 0 : jarquebera_jbcheb(x, 1.136575e-01, &tj, &tj1, &result, _state);
18839 0 : jarquebera_jbcheb(x, -1.726627e-02, &tj, &tj1, &result, _state);
18840 0 : jarquebera_jbcheb(x, 3.421110e-03, &tj, &tj1, &result, _state);
18841 0 : jarquebera_jbcheb(x, -1.581510e-03, &tj, &tj1, &result, _state);
18842 0 : jarquebera_jbcheb(x, -5.559520e-04, &tj, &tj1, &result, _state);
18843 0 : jarquebera_jbcheb(x, -6.838208e-04, &tj, &tj1, &result, _state);
18844 0 : jarquebera_jbcheb(x, 8.428839e-04, &tj, &tj1, &result, _state);
18845 0 : jarquebera_jbcheb(x, -7.170682e-04, &tj, &tj1, &result, _state);
18846 0 : jarquebera_jbcheb(x, -6.006647e-04, &tj, &tj1, &result, _state);
18847 0 : if( ae_fp_greater(result,(double)(0)) )
18848 : {
18849 0 : result = (double)(0);
18850 : }
18851 0 : return result;
18852 : }
18853 0 : result = -1.539373e-01*(s-2.000000e+01)-7.206941e+00;
18854 0 : return result;
18855 : }
18856 :
18857 :
18858 0 : static double jarquebera_jbtbl20(double s, ae_state *_state)
18859 : {
18860 : double x;
18861 : double tj;
18862 : double tj1;
18863 : double result;
18864 :
18865 :
18866 0 : result = (double)(0);
18867 0 : if( ae_fp_less_eq(s,4.0000) )
18868 : {
18869 0 : x = 2*(s-0.000000)/4.000000-1;
18870 0 : tj = (double)(1);
18871 0 : tj1 = x;
18872 0 : jarquebera_jbcheb(x, -1.854794e+00, &tj, &tj1, &result, _state);
18873 0 : jarquebera_jbcheb(x, -1.948947e+00, &tj, &tj1, &result, _state);
18874 0 : jarquebera_jbcheb(x, 1.632184e-01, &tj, &tj1, &result, _state);
18875 0 : jarquebera_jbcheb(x, 2.139397e-01, &tj, &tj1, &result, _state);
18876 0 : jarquebera_jbcheb(x, -1.006237e-01, &tj, &tj1, &result, _state);
18877 0 : jarquebera_jbcheb(x, -3.810031e-02, &tj, &tj1, &result, _state);
18878 0 : jarquebera_jbcheb(x, 3.573620e-02, &tj, &tj1, &result, _state);
18879 0 : jarquebera_jbcheb(x, 9.951242e-03, &tj, &tj1, &result, _state);
18880 0 : jarquebera_jbcheb(x, -1.274092e-02, &tj, &tj1, &result, _state);
18881 0 : jarquebera_jbcheb(x, -3.464196e-03, &tj, &tj1, &result, _state);
18882 0 : jarquebera_jbcheb(x, 4.882139e-03, &tj, &tj1, &result, _state);
18883 0 : jarquebera_jbcheb(x, 1.575144e-03, &tj, &tj1, &result, _state);
18884 0 : jarquebera_jbcheb(x, -1.822804e-03, &tj, &tj1, &result, _state);
18885 0 : jarquebera_jbcheb(x, -7.061348e-04, &tj, &tj1, &result, _state);
18886 0 : jarquebera_jbcheb(x, 5.908404e-04, &tj, &tj1, &result, _state);
18887 0 : jarquebera_jbcheb(x, 1.978353e-04, &tj, &tj1, &result, _state);
18888 0 : if( ae_fp_greater(result,(double)(0)) )
18889 : {
18890 0 : result = (double)(0);
18891 : }
18892 0 : return result;
18893 : }
18894 0 : if( ae_fp_less_eq(s,15.0000) )
18895 : {
18896 0 : x = 2*(s-4.000000)/11.000000-1;
18897 0 : tj = (double)(1);
18898 0 : tj1 = x;
18899 0 : jarquebera_jbcheb(x, -5.030989e+00, &tj, &tj1, &result, _state);
18900 0 : jarquebera_jbcheb(x, -1.327151e+00, &tj, &tj1, &result, _state);
18901 0 : jarquebera_jbcheb(x, 1.346404e-01, &tj, &tj1, &result, _state);
18902 0 : jarquebera_jbcheb(x, -2.840051e-02, &tj, &tj1, &result, _state);
18903 0 : jarquebera_jbcheb(x, 7.578551e-03, &tj, &tj1, &result, _state);
18904 0 : jarquebera_jbcheb(x, -9.813886e-04, &tj, &tj1, &result, _state);
18905 0 : jarquebera_jbcheb(x, 5.905973e-05, &tj, &tj1, &result, _state);
18906 0 : jarquebera_jbcheb(x, -5.358489e-04, &tj, &tj1, &result, _state);
18907 0 : jarquebera_jbcheb(x, -3.450795e-04, &tj, &tj1, &result, _state);
18908 0 : jarquebera_jbcheb(x, -6.941157e-04, &tj, &tj1, &result, _state);
18909 0 : jarquebera_jbcheb(x, -7.432418e-04, &tj, &tj1, &result, _state);
18910 0 : jarquebera_jbcheb(x, -2.070537e-04, &tj, &tj1, &result, _state);
18911 0 : jarquebera_jbcheb(x, 9.375654e-04, &tj, &tj1, &result, _state);
18912 0 : jarquebera_jbcheb(x, 5.367378e-04, &tj, &tj1, &result, _state);
18913 0 : jarquebera_jbcheb(x, 9.890859e-04, &tj, &tj1, &result, _state);
18914 0 : jarquebera_jbcheb(x, 6.679782e-04, &tj, &tj1, &result, _state);
18915 0 : if( ae_fp_greater(result,(double)(0)) )
18916 : {
18917 0 : result = (double)(0);
18918 : }
18919 0 : return result;
18920 : }
18921 0 : if( ae_fp_less_eq(s,25.0000) )
18922 : {
18923 0 : x = 2*(s-15.000000)/10.000000-1;
18924 0 : tj = (double)(1);
18925 0 : tj1 = x;
18926 0 : jarquebera_jbcheb(x, -7.015854e+00, &tj, &tj1, &result, _state);
18927 0 : jarquebera_jbcheb(x, -7.487737e-01, &tj, &tj1, &result, _state);
18928 0 : jarquebera_jbcheb(x, 2.244254e-02, &tj, &tj1, &result, _state);
18929 0 : if( ae_fp_greater(result,(double)(0)) )
18930 : {
18931 0 : result = (double)(0);
18932 : }
18933 0 : return result;
18934 : }
18935 0 : result = -1.318007e-01*(s-2.500000e+01)-7.742185e+00;
18936 0 : return result;
18937 : }
18938 :
18939 :
18940 0 : static double jarquebera_jbtbl30(double s, ae_state *_state)
18941 : {
18942 : double x;
18943 : double tj;
18944 : double tj1;
18945 : double result;
18946 :
18947 :
18948 0 : result = (double)(0);
18949 0 : if( ae_fp_less_eq(s,4.0000) )
18950 : {
18951 0 : x = 2*(s-0.000000)/4.000000-1;
18952 0 : tj = (double)(1);
18953 0 : tj1 = x;
18954 0 : jarquebera_jbcheb(x, -1.630822e+00, &tj, &tj1, &result, _state);
18955 0 : jarquebera_jbcheb(x, -1.724298e+00, &tj, &tj1, &result, _state);
18956 0 : jarquebera_jbcheb(x, 7.872756e-02, &tj, &tj1, &result, _state);
18957 0 : jarquebera_jbcheb(x, 1.658268e-01, &tj, &tj1, &result, _state);
18958 0 : jarquebera_jbcheb(x, -3.573597e-02, &tj, &tj1, &result, _state);
18959 0 : jarquebera_jbcheb(x, -2.994157e-02, &tj, &tj1, &result, _state);
18960 0 : jarquebera_jbcheb(x, 5.994825e-03, &tj, &tj1, &result, _state);
18961 0 : jarquebera_jbcheb(x, 7.394303e-03, &tj, &tj1, &result, _state);
18962 0 : jarquebera_jbcheb(x, -5.785029e-04, &tj, &tj1, &result, _state);
18963 0 : jarquebera_jbcheb(x, -1.990264e-03, &tj, &tj1, &result, _state);
18964 0 : jarquebera_jbcheb(x, -1.037838e-04, &tj, &tj1, &result, _state);
18965 0 : jarquebera_jbcheb(x, 6.755546e-04, &tj, &tj1, &result, _state);
18966 0 : jarquebera_jbcheb(x, 1.774473e-04, &tj, &tj1, &result, _state);
18967 0 : jarquebera_jbcheb(x, -2.821395e-04, &tj, &tj1, &result, _state);
18968 0 : jarquebera_jbcheb(x, -1.392603e-04, &tj, &tj1, &result, _state);
18969 0 : jarquebera_jbcheb(x, 1.353313e-04, &tj, &tj1, &result, _state);
18970 0 : if( ae_fp_greater(result,(double)(0)) )
18971 : {
18972 0 : result = (double)(0);
18973 : }
18974 0 : return result;
18975 : }
18976 0 : if( ae_fp_less_eq(s,15.0000) )
18977 : {
18978 0 : x = 2*(s-4.000000)/11.000000-1;
18979 0 : tj = (double)(1);
18980 0 : tj1 = x;
18981 0 : jarquebera_jbcheb(x, -4.539322e+00, &tj, &tj1, &result, _state);
18982 0 : jarquebera_jbcheb(x, -1.197018e+00, &tj, &tj1, &result, _state);
18983 0 : jarquebera_jbcheb(x, 1.396848e-01, &tj, &tj1, &result, _state);
18984 0 : jarquebera_jbcheb(x, -2.804293e-02, &tj, &tj1, &result, _state);
18985 0 : jarquebera_jbcheb(x, 6.867928e-03, &tj, &tj1, &result, _state);
18986 0 : jarquebera_jbcheb(x, -2.768758e-03, &tj, &tj1, &result, _state);
18987 0 : jarquebera_jbcheb(x, 5.211792e-04, &tj, &tj1, &result, _state);
18988 0 : jarquebera_jbcheb(x, 4.925799e-04, &tj, &tj1, &result, _state);
18989 0 : jarquebera_jbcheb(x, 5.046235e-04, &tj, &tj1, &result, _state);
18990 0 : jarquebera_jbcheb(x, -9.536469e-05, &tj, &tj1, &result, _state);
18991 0 : jarquebera_jbcheb(x, -6.489642e-04, &tj, &tj1, &result, _state);
18992 0 : if( ae_fp_greater(result,(double)(0)) )
18993 : {
18994 0 : result = (double)(0);
18995 : }
18996 0 : return result;
18997 : }
18998 0 : if( ae_fp_less_eq(s,25.0000) )
18999 : {
19000 0 : x = 2*(s-15.000000)/10.000000-1;
19001 0 : tj = (double)(1);
19002 0 : tj1 = x;
19003 0 : jarquebera_jbcheb(x, -6.263462e+00, &tj, &tj1, &result, _state);
19004 0 : jarquebera_jbcheb(x, -6.177316e-01, &tj, &tj1, &result, _state);
19005 0 : jarquebera_jbcheb(x, 2.590637e-02, &tj, &tj1, &result, _state);
19006 0 : if( ae_fp_greater(result,(double)(0)) )
19007 : {
19008 0 : result = (double)(0);
19009 : }
19010 0 : return result;
19011 : }
19012 0 : result = -1.028212e-01*(s-2.500000e+01)-6.855288e+00;
19013 0 : return result;
19014 : }
19015 :
19016 :
19017 0 : static double jarquebera_jbtbl50(double s, ae_state *_state)
19018 : {
19019 : double x;
19020 : double tj;
19021 : double tj1;
19022 : double result;
19023 :
19024 :
19025 0 : result = (double)(0);
19026 0 : if( ae_fp_less_eq(s,4.0000) )
19027 : {
19028 0 : x = 2*(s-0.000000)/4.000000-1;
19029 0 : tj = (double)(1);
19030 0 : tj1 = x;
19031 0 : jarquebera_jbcheb(x, -1.436279e+00, &tj, &tj1, &result, _state);
19032 0 : jarquebera_jbcheb(x, -1.519711e+00, &tj, &tj1, &result, _state);
19033 0 : jarquebera_jbcheb(x, 1.148699e-02, &tj, &tj1, &result, _state);
19034 0 : jarquebera_jbcheb(x, 1.001204e-01, &tj, &tj1, &result, _state);
19035 0 : jarquebera_jbcheb(x, -3.207620e-03, &tj, &tj1, &result, _state);
19036 0 : jarquebera_jbcheb(x, -1.034778e-02, &tj, &tj1, &result, _state);
19037 0 : jarquebera_jbcheb(x, -1.220322e-03, &tj, &tj1, &result, _state);
19038 0 : jarquebera_jbcheb(x, 1.033260e-03, &tj, &tj1, &result, _state);
19039 0 : jarquebera_jbcheb(x, 2.588280e-04, &tj, &tj1, &result, _state);
19040 0 : jarquebera_jbcheb(x, -1.851653e-04, &tj, &tj1, &result, _state);
19041 0 : jarquebera_jbcheb(x, -1.287733e-04, &tj, &tj1, &result, _state);
19042 0 : if( ae_fp_greater(result,(double)(0)) )
19043 : {
19044 0 : result = (double)(0);
19045 : }
19046 0 : return result;
19047 : }
19048 0 : if( ae_fp_less_eq(s,15.0000) )
19049 : {
19050 0 : x = 2*(s-4.000000)/11.000000-1;
19051 0 : tj = (double)(1);
19052 0 : tj1 = x;
19053 0 : jarquebera_jbcheb(x, -4.234645e+00, &tj, &tj1, &result, _state);
19054 0 : jarquebera_jbcheb(x, -1.189127e+00, &tj, &tj1, &result, _state);
19055 0 : jarquebera_jbcheb(x, 1.429738e-01, &tj, &tj1, &result, _state);
19056 0 : jarquebera_jbcheb(x, -3.058822e-02, &tj, &tj1, &result, _state);
19057 0 : jarquebera_jbcheb(x, 9.086776e-03, &tj, &tj1, &result, _state);
19058 0 : jarquebera_jbcheb(x, -1.445783e-03, &tj, &tj1, &result, _state);
19059 0 : jarquebera_jbcheb(x, 1.311671e-03, &tj, &tj1, &result, _state);
19060 0 : jarquebera_jbcheb(x, -7.261298e-04, &tj, &tj1, &result, _state);
19061 0 : jarquebera_jbcheb(x, 6.496987e-04, &tj, &tj1, &result, _state);
19062 0 : jarquebera_jbcheb(x, 2.605249e-04, &tj, &tj1, &result, _state);
19063 0 : jarquebera_jbcheb(x, 8.162282e-04, &tj, &tj1, &result, _state);
19064 0 : if( ae_fp_greater(result,(double)(0)) )
19065 : {
19066 0 : result = (double)(0);
19067 : }
19068 0 : return result;
19069 : }
19070 0 : if( ae_fp_less_eq(s,25.0000) )
19071 : {
19072 0 : x = 2*(s-15.000000)/10.000000-1;
19073 0 : tj = (double)(1);
19074 0 : tj1 = x;
19075 0 : jarquebera_jbcheb(x, -5.921095e+00, &tj, &tj1, &result, _state);
19076 0 : jarquebera_jbcheb(x, -5.888603e-01, &tj, &tj1, &result, _state);
19077 0 : jarquebera_jbcheb(x, 3.080113e-02, &tj, &tj1, &result, _state);
19078 0 : if( ae_fp_greater(result,(double)(0)) )
19079 : {
19080 0 : result = (double)(0);
19081 : }
19082 0 : return result;
19083 : }
19084 0 : result = -9.313116e-02*(s-2.500000e+01)-6.479154e+00;
19085 0 : return result;
19086 : }
19087 :
19088 :
19089 0 : static double jarquebera_jbtbl65(double s, ae_state *_state)
19090 : {
19091 : double x;
19092 : double tj;
19093 : double tj1;
19094 : double result;
19095 :
19096 :
19097 0 : result = (double)(0);
19098 0 : if( ae_fp_less_eq(s,4.0000) )
19099 : {
19100 0 : x = 2*(s-0.000000)/4.000000-1;
19101 0 : tj = (double)(1);
19102 0 : tj1 = x;
19103 0 : jarquebera_jbcheb(x, -1.360024e+00, &tj, &tj1, &result, _state);
19104 0 : jarquebera_jbcheb(x, -1.434631e+00, &tj, &tj1, &result, _state);
19105 0 : jarquebera_jbcheb(x, -6.514580e-03, &tj, &tj1, &result, _state);
19106 0 : jarquebera_jbcheb(x, 7.332038e-02, &tj, &tj1, &result, _state);
19107 0 : jarquebera_jbcheb(x, 1.158197e-03, &tj, &tj1, &result, _state);
19108 0 : jarquebera_jbcheb(x, -5.121233e-03, &tj, &tj1, &result, _state);
19109 0 : jarquebera_jbcheb(x, -1.051056e-03, &tj, &tj1, &result, _state);
19110 0 : if( ae_fp_greater(result,(double)(0)) )
19111 : {
19112 0 : result = (double)(0);
19113 : }
19114 0 : return result;
19115 : }
19116 0 : if( ae_fp_less_eq(s,15.0000) )
19117 : {
19118 0 : x = 2*(s-4.000000)/11.000000-1;
19119 0 : tj = (double)(1);
19120 0 : tj1 = x;
19121 0 : jarquebera_jbcheb(x, -4.148601e+00, &tj, &tj1, &result, _state);
19122 0 : jarquebera_jbcheb(x, -1.214233e+00, &tj, &tj1, &result, _state);
19123 0 : jarquebera_jbcheb(x, 1.487977e-01, &tj, &tj1, &result, _state);
19124 0 : jarquebera_jbcheb(x, -3.424720e-02, &tj, &tj1, &result, _state);
19125 0 : jarquebera_jbcheb(x, 1.116715e-02, &tj, &tj1, &result, _state);
19126 0 : jarquebera_jbcheb(x, -4.043152e-03, &tj, &tj1, &result, _state);
19127 0 : jarquebera_jbcheb(x, 1.718149e-03, &tj, &tj1, &result, _state);
19128 0 : jarquebera_jbcheb(x, -1.313701e-03, &tj, &tj1, &result, _state);
19129 0 : jarquebera_jbcheb(x, 3.097305e-04, &tj, &tj1, &result, _state);
19130 0 : jarquebera_jbcheb(x, 2.181031e-04, &tj, &tj1, &result, _state);
19131 0 : jarquebera_jbcheb(x, 1.256975e-04, &tj, &tj1, &result, _state);
19132 0 : if( ae_fp_greater(result,(double)(0)) )
19133 : {
19134 0 : result = (double)(0);
19135 : }
19136 0 : return result;
19137 : }
19138 0 : if( ae_fp_less_eq(s,25.0000) )
19139 : {
19140 0 : x = 2*(s-15.000000)/10.000000-1;
19141 0 : tj = (double)(1);
19142 0 : tj1 = x;
19143 0 : jarquebera_jbcheb(x, -5.858951e+00, &tj, &tj1, &result, _state);
19144 0 : jarquebera_jbcheb(x, -5.895179e-01, &tj, &tj1, &result, _state);
19145 0 : jarquebera_jbcheb(x, 2.933237e-02, &tj, &tj1, &result, _state);
19146 0 : if( ae_fp_greater(result,(double)(0)) )
19147 : {
19148 0 : result = (double)(0);
19149 : }
19150 0 : return result;
19151 : }
19152 0 : result = -9.443768e-02*(s-2.500000e+01)-6.419137e+00;
19153 0 : return result;
19154 : }
19155 :
19156 :
19157 0 : static double jarquebera_jbtbl100(double s, ae_state *_state)
19158 : {
19159 : double x;
19160 : double tj;
19161 : double tj1;
19162 : double result;
19163 :
19164 :
19165 0 : result = (double)(0);
19166 0 : if( ae_fp_less_eq(s,4.0000) )
19167 : {
19168 0 : x = 2*(s-0.000000)/4.000000-1;
19169 0 : tj = (double)(1);
19170 0 : tj1 = x;
19171 0 : jarquebera_jbcheb(x, -1.257021e+00, &tj, &tj1, &result, _state);
19172 0 : jarquebera_jbcheb(x, -1.313418e+00, &tj, &tj1, &result, _state);
19173 0 : jarquebera_jbcheb(x, -1.628931e-02, &tj, &tj1, &result, _state);
19174 0 : jarquebera_jbcheb(x, 4.264287e-02, &tj, &tj1, &result, _state);
19175 0 : jarquebera_jbcheb(x, 1.518487e-03, &tj, &tj1, &result, _state);
19176 0 : jarquebera_jbcheb(x, -1.499826e-03, &tj, &tj1, &result, _state);
19177 0 : jarquebera_jbcheb(x, -4.836044e-04, &tj, &tj1, &result, _state);
19178 0 : if( ae_fp_greater(result,(double)(0)) )
19179 : {
19180 0 : result = (double)(0);
19181 : }
19182 0 : return result;
19183 : }
19184 0 : if( ae_fp_less_eq(s,15.0000) )
19185 : {
19186 0 : x = 2*(s-4.000000)/11.000000-1;
19187 0 : tj = (double)(1);
19188 0 : tj1 = x;
19189 0 : jarquebera_jbcheb(x, -4.056508e+00, &tj, &tj1, &result, _state);
19190 0 : jarquebera_jbcheb(x, -1.279690e+00, &tj, &tj1, &result, _state);
19191 0 : jarquebera_jbcheb(x, 1.665746e-01, &tj, &tj1, &result, _state);
19192 0 : jarquebera_jbcheb(x, -4.290012e-02, &tj, &tj1, &result, _state);
19193 0 : jarquebera_jbcheb(x, 1.487632e-02, &tj, &tj1, &result, _state);
19194 0 : jarquebera_jbcheb(x, -5.704465e-03, &tj, &tj1, &result, _state);
19195 0 : jarquebera_jbcheb(x, 2.211669e-03, &tj, &tj1, &result, _state);
19196 0 : if( ae_fp_greater(result,(double)(0)) )
19197 : {
19198 0 : result = (double)(0);
19199 : }
19200 0 : return result;
19201 : }
19202 0 : if( ae_fp_less_eq(s,25.0000) )
19203 : {
19204 0 : x = 2*(s-15.000000)/10.000000-1;
19205 0 : tj = (double)(1);
19206 0 : tj1 = x;
19207 0 : jarquebera_jbcheb(x, -5.866099e+00, &tj, &tj1, &result, _state);
19208 0 : jarquebera_jbcheb(x, -6.399767e-01, &tj, &tj1, &result, _state);
19209 0 : jarquebera_jbcheb(x, 2.498208e-02, &tj, &tj1, &result, _state);
19210 0 : if( ae_fp_greater(result,(double)(0)) )
19211 : {
19212 0 : result = (double)(0);
19213 : }
19214 0 : return result;
19215 : }
19216 0 : result = -1.080097e-01*(s-2.500000e+01)-6.481094e+00;
19217 0 : return result;
19218 : }
19219 :
19220 :
19221 0 : static double jarquebera_jbtbl130(double s, ae_state *_state)
19222 : {
19223 : double x;
19224 : double tj;
19225 : double tj1;
19226 : double result;
19227 :
19228 :
19229 0 : result = (double)(0);
19230 0 : if( ae_fp_less_eq(s,4.0000) )
19231 : {
19232 0 : x = 2*(s-0.000000)/4.000000-1;
19233 0 : tj = (double)(1);
19234 0 : tj1 = x;
19235 0 : jarquebera_jbcheb(x, -1.207999e+00, &tj, &tj1, &result, _state);
19236 0 : jarquebera_jbcheb(x, -1.253864e+00, &tj, &tj1, &result, _state);
19237 0 : jarquebera_jbcheb(x, -1.618032e-02, &tj, &tj1, &result, _state);
19238 0 : jarquebera_jbcheb(x, 3.112729e-02, &tj, &tj1, &result, _state);
19239 0 : jarquebera_jbcheb(x, 1.210546e-03, &tj, &tj1, &result, _state);
19240 0 : jarquebera_jbcheb(x, -4.732602e-04, &tj, &tj1, &result, _state);
19241 0 : jarquebera_jbcheb(x, -2.410527e-04, &tj, &tj1, &result, _state);
19242 0 : if( ae_fp_greater(result,(double)(0)) )
19243 : {
19244 0 : result = (double)(0);
19245 : }
19246 0 : return result;
19247 : }
19248 0 : if( ae_fp_less_eq(s,15.0000) )
19249 : {
19250 0 : x = 2*(s-4.000000)/11.000000-1;
19251 0 : tj = (double)(1);
19252 0 : tj1 = x;
19253 0 : jarquebera_jbcheb(x, -4.026324e+00, &tj, &tj1, &result, _state);
19254 0 : jarquebera_jbcheb(x, -1.331990e+00, &tj, &tj1, &result, _state);
19255 0 : jarquebera_jbcheb(x, 1.779129e-01, &tj, &tj1, &result, _state);
19256 0 : jarquebera_jbcheb(x, -4.674749e-02, &tj, &tj1, &result, _state);
19257 0 : jarquebera_jbcheb(x, 1.669077e-02, &tj, &tj1, &result, _state);
19258 0 : jarquebera_jbcheb(x, -5.679136e-03, &tj, &tj1, &result, _state);
19259 0 : jarquebera_jbcheb(x, 8.833221e-04, &tj, &tj1, &result, _state);
19260 0 : if( ae_fp_greater(result,(double)(0)) )
19261 : {
19262 0 : result = (double)(0);
19263 : }
19264 0 : return result;
19265 : }
19266 0 : if( ae_fp_less_eq(s,25.0000) )
19267 : {
19268 0 : x = 2*(s-15.000000)/10.000000-1;
19269 0 : tj = (double)(1);
19270 0 : tj1 = x;
19271 0 : jarquebera_jbcheb(x, -5.893951e+00, &tj, &tj1, &result, _state);
19272 0 : jarquebera_jbcheb(x, -6.475304e-01, &tj, &tj1, &result, _state);
19273 0 : jarquebera_jbcheb(x, 3.116734e-02, &tj, &tj1, &result, _state);
19274 0 : if( ae_fp_greater(result,(double)(0)) )
19275 : {
19276 0 : result = (double)(0);
19277 : }
19278 0 : return result;
19279 : }
19280 0 : result = -1.045722e-01*(s-2.500000e+01)-6.510314e+00;
19281 0 : return result;
19282 : }
19283 :
19284 :
19285 0 : static double jarquebera_jbtbl200(double s, ae_state *_state)
19286 : {
19287 : double x;
19288 : double tj;
19289 : double tj1;
19290 : double result;
19291 :
19292 :
19293 0 : result = (double)(0);
19294 0 : if( ae_fp_less_eq(s,4.0000) )
19295 : {
19296 0 : x = 2*(s-0.000000)/4.000000-1;
19297 0 : tj = (double)(1);
19298 0 : tj1 = x;
19299 0 : jarquebera_jbcheb(x, -1.146155e+00, &tj, &tj1, &result, _state);
19300 0 : jarquebera_jbcheb(x, -1.177398e+00, &tj, &tj1, &result, _state);
19301 0 : jarquebera_jbcheb(x, -1.297970e-02, &tj, &tj1, &result, _state);
19302 0 : jarquebera_jbcheb(x, 1.869745e-02, &tj, &tj1, &result, _state);
19303 0 : jarquebera_jbcheb(x, 1.717288e-04, &tj, &tj1, &result, _state);
19304 0 : jarquebera_jbcheb(x, -1.982108e-04, &tj, &tj1, &result, _state);
19305 0 : jarquebera_jbcheb(x, 6.427636e-05, &tj, &tj1, &result, _state);
19306 0 : if( ae_fp_greater(result,(double)(0)) )
19307 : {
19308 0 : result = (double)(0);
19309 : }
19310 0 : return result;
19311 : }
19312 0 : if( ae_fp_less_eq(s,15.0000) )
19313 : {
19314 0 : x = 2*(s-4.000000)/11.000000-1;
19315 0 : tj = (double)(1);
19316 0 : tj1 = x;
19317 0 : jarquebera_jbcheb(x, -4.034235e+00, &tj, &tj1, &result, _state);
19318 0 : jarquebera_jbcheb(x, -1.455006e+00, &tj, &tj1, &result, _state);
19319 0 : jarquebera_jbcheb(x, 1.942996e-01, &tj, &tj1, &result, _state);
19320 0 : jarquebera_jbcheb(x, -4.973795e-02, &tj, &tj1, &result, _state);
19321 0 : jarquebera_jbcheb(x, 1.418812e-02, &tj, &tj1, &result, _state);
19322 0 : jarquebera_jbcheb(x, -3.156778e-03, &tj, &tj1, &result, _state);
19323 0 : jarquebera_jbcheb(x, 4.896705e-05, &tj, &tj1, &result, _state);
19324 0 : if( ae_fp_greater(result,(double)(0)) )
19325 : {
19326 0 : result = (double)(0);
19327 : }
19328 0 : return result;
19329 : }
19330 0 : if( ae_fp_less_eq(s,25.0000) )
19331 : {
19332 0 : x = 2*(s-15.000000)/10.000000-1;
19333 0 : tj = (double)(1);
19334 0 : tj1 = x;
19335 0 : jarquebera_jbcheb(x, -6.086071e+00, &tj, &tj1, &result, _state);
19336 0 : jarquebera_jbcheb(x, -7.152176e-01, &tj, &tj1, &result, _state);
19337 0 : jarquebera_jbcheb(x, 3.725393e-02, &tj, &tj1, &result, _state);
19338 0 : if( ae_fp_greater(result,(double)(0)) )
19339 : {
19340 0 : result = (double)(0);
19341 : }
19342 0 : return result;
19343 : }
19344 0 : result = -1.132404e-01*(s-2.500000e+01)-6.764034e+00;
19345 0 : return result;
19346 : }
19347 :
19348 :
19349 0 : static double jarquebera_jbtbl301(double s, ae_state *_state)
19350 : {
19351 : double x;
19352 : double tj;
19353 : double tj1;
19354 : double result;
19355 :
19356 :
19357 0 : result = (double)(0);
19358 0 : if( ae_fp_less_eq(s,4.0000) )
19359 : {
19360 0 : x = 2*(s-0.000000)/4.000000-1;
19361 0 : tj = (double)(1);
19362 0 : tj1 = x;
19363 0 : jarquebera_jbcheb(x, -1.104290e+00, &tj, &tj1, &result, _state);
19364 0 : jarquebera_jbcheb(x, -1.125800e+00, &tj, &tj1, &result, _state);
19365 0 : jarquebera_jbcheb(x, -9.595847e-03, &tj, &tj1, &result, _state);
19366 0 : jarquebera_jbcheb(x, 1.219666e-02, &tj, &tj1, &result, _state);
19367 0 : jarquebera_jbcheb(x, 1.502210e-04, &tj, &tj1, &result, _state);
19368 0 : jarquebera_jbcheb(x, -6.414543e-05, &tj, &tj1, &result, _state);
19369 0 : jarquebera_jbcheb(x, 6.754115e-05, &tj, &tj1, &result, _state);
19370 0 : if( ae_fp_greater(result,(double)(0)) )
19371 : {
19372 0 : result = (double)(0);
19373 : }
19374 0 : return result;
19375 : }
19376 0 : if( ae_fp_less_eq(s,15.0000) )
19377 : {
19378 0 : x = 2*(s-4.000000)/11.000000-1;
19379 0 : tj = (double)(1);
19380 0 : tj1 = x;
19381 0 : jarquebera_jbcheb(x, -4.065955e+00, &tj, &tj1, &result, _state);
19382 0 : jarquebera_jbcheb(x, -1.582060e+00, &tj, &tj1, &result, _state);
19383 0 : jarquebera_jbcheb(x, 2.004472e-01, &tj, &tj1, &result, _state);
19384 0 : jarquebera_jbcheb(x, -4.709092e-02, &tj, &tj1, &result, _state);
19385 0 : jarquebera_jbcheb(x, 1.105779e-02, &tj, &tj1, &result, _state);
19386 0 : jarquebera_jbcheb(x, 1.197391e-03, &tj, &tj1, &result, _state);
19387 0 : jarquebera_jbcheb(x, -8.386780e-04, &tj, &tj1, &result, _state);
19388 0 : if( ae_fp_greater(result,(double)(0)) )
19389 : {
19390 0 : result = (double)(0);
19391 : }
19392 0 : return result;
19393 : }
19394 0 : if( ae_fp_less_eq(s,25.0000) )
19395 : {
19396 0 : x = 2*(s-15.000000)/10.000000-1;
19397 0 : tj = (double)(1);
19398 0 : tj1 = x;
19399 0 : jarquebera_jbcheb(x, -6.311384e+00, &tj, &tj1, &result, _state);
19400 0 : jarquebera_jbcheb(x, -7.918763e-01, &tj, &tj1, &result, _state);
19401 0 : jarquebera_jbcheb(x, 3.626584e-02, &tj, &tj1, &result, _state);
19402 0 : if( ae_fp_greater(result,(double)(0)) )
19403 : {
19404 0 : result = (double)(0);
19405 : }
19406 0 : return result;
19407 : }
19408 0 : result = -1.293626e-01*(s-2.500000e+01)-7.066995e+00;
19409 0 : return result;
19410 : }
19411 :
19412 :
19413 0 : static double jarquebera_jbtbl501(double s, ae_state *_state)
19414 : {
19415 : double x;
19416 : double tj;
19417 : double tj1;
19418 : double result;
19419 :
19420 :
19421 0 : result = (double)(0);
19422 0 : if( ae_fp_less_eq(s,4.0000) )
19423 : {
19424 0 : x = 2*(s-0.000000)/4.000000-1;
19425 0 : tj = (double)(1);
19426 0 : tj1 = x;
19427 0 : jarquebera_jbcheb(x, -1.067426e+00, &tj, &tj1, &result, _state);
19428 0 : jarquebera_jbcheb(x, -1.079765e+00, &tj, &tj1, &result, _state);
19429 0 : jarquebera_jbcheb(x, -5.463005e-03, &tj, &tj1, &result, _state);
19430 0 : jarquebera_jbcheb(x, 6.875659e-03, &tj, &tj1, &result, _state);
19431 0 : if( ae_fp_greater(result,(double)(0)) )
19432 : {
19433 0 : result = (double)(0);
19434 : }
19435 0 : return result;
19436 : }
19437 0 : if( ae_fp_less_eq(s,15.0000) )
19438 : {
19439 0 : x = 2*(s-4.000000)/11.000000-1;
19440 0 : tj = (double)(1);
19441 0 : tj1 = x;
19442 0 : jarquebera_jbcheb(x, -4.127574e+00, &tj, &tj1, &result, _state);
19443 0 : jarquebera_jbcheb(x, -1.740694e+00, &tj, &tj1, &result, _state);
19444 0 : jarquebera_jbcheb(x, 2.044502e-01, &tj, &tj1, &result, _state);
19445 0 : jarquebera_jbcheb(x, -3.746714e-02, &tj, &tj1, &result, _state);
19446 0 : jarquebera_jbcheb(x, 3.810594e-04, &tj, &tj1, &result, _state);
19447 0 : jarquebera_jbcheb(x, 1.197111e-03, &tj, &tj1, &result, _state);
19448 0 : if( ae_fp_greater(result,(double)(0)) )
19449 : {
19450 0 : result = (double)(0);
19451 : }
19452 0 : return result;
19453 : }
19454 0 : if( ae_fp_less_eq(s,25.0000) )
19455 : {
19456 0 : x = 2*(s-15.000000)/10.000000-1;
19457 0 : tj = (double)(1);
19458 0 : tj1 = x;
19459 0 : jarquebera_jbcheb(x, -6.628194e+00, &tj, &tj1, &result, _state);
19460 0 : jarquebera_jbcheb(x, -8.846221e-01, &tj, &tj1, &result, _state);
19461 0 : jarquebera_jbcheb(x, 4.386405e-02, &tj, &tj1, &result, _state);
19462 0 : if( ae_fp_greater(result,(double)(0)) )
19463 : {
19464 0 : result = (double)(0);
19465 : }
19466 0 : return result;
19467 : }
19468 0 : result = -1.418332e-01*(s-2.500000e+01)-7.468952e+00;
19469 0 : return result;
19470 : }
19471 :
19472 :
19473 0 : static double jarquebera_jbtbl701(double s, ae_state *_state)
19474 : {
19475 : double x;
19476 : double tj;
19477 : double tj1;
19478 : double result;
19479 :
19480 :
19481 0 : result = (double)(0);
19482 0 : if( ae_fp_less_eq(s,4.0000) )
19483 : {
19484 0 : x = 2*(s-0.000000)/4.000000-1;
19485 0 : tj = (double)(1);
19486 0 : tj1 = x;
19487 0 : jarquebera_jbcheb(x, -1.050999e+00, &tj, &tj1, &result, _state);
19488 0 : jarquebera_jbcheb(x, -1.059769e+00, &tj, &tj1, &result, _state);
19489 0 : jarquebera_jbcheb(x, -3.922680e-03, &tj, &tj1, &result, _state);
19490 0 : jarquebera_jbcheb(x, 4.847054e-03, &tj, &tj1, &result, _state);
19491 0 : if( ae_fp_greater(result,(double)(0)) )
19492 : {
19493 0 : result = (double)(0);
19494 : }
19495 0 : return result;
19496 : }
19497 0 : if( ae_fp_less_eq(s,15.0000) )
19498 : {
19499 0 : x = 2*(s-4.000000)/11.000000-1;
19500 0 : tj = (double)(1);
19501 0 : tj1 = x;
19502 0 : jarquebera_jbcheb(x, -4.192182e+00, &tj, &tj1, &result, _state);
19503 0 : jarquebera_jbcheb(x, -1.860007e+00, &tj, &tj1, &result, _state);
19504 0 : jarquebera_jbcheb(x, 1.963942e-01, &tj, &tj1, &result, _state);
19505 0 : jarquebera_jbcheb(x, -2.838711e-02, &tj, &tj1, &result, _state);
19506 0 : jarquebera_jbcheb(x, -2.893112e-04, &tj, &tj1, &result, _state);
19507 0 : jarquebera_jbcheb(x, 2.159788e-03, &tj, &tj1, &result, _state);
19508 0 : if( ae_fp_greater(result,(double)(0)) )
19509 : {
19510 0 : result = (double)(0);
19511 : }
19512 0 : return result;
19513 : }
19514 0 : if( ae_fp_less_eq(s,25.0000) )
19515 : {
19516 0 : x = 2*(s-15.000000)/10.000000-1;
19517 0 : tj = (double)(1);
19518 0 : tj1 = x;
19519 0 : jarquebera_jbcheb(x, -6.917851e+00, &tj, &tj1, &result, _state);
19520 0 : jarquebera_jbcheb(x, -9.817020e-01, &tj, &tj1, &result, _state);
19521 0 : jarquebera_jbcheb(x, 5.383727e-02, &tj, &tj1, &result, _state);
19522 0 : if( ae_fp_greater(result,(double)(0)) )
19523 : {
19524 0 : result = (double)(0);
19525 : }
19526 0 : return result;
19527 : }
19528 0 : result = -1.532706e-01*(s-2.500000e+01)-7.845715e+00;
19529 0 : return result;
19530 : }
19531 :
19532 :
19533 0 : static double jarquebera_jbtbl1401(double s, ae_state *_state)
19534 : {
19535 : double x;
19536 : double tj;
19537 : double tj1;
19538 : double result;
19539 :
19540 :
19541 0 : result = (double)(0);
19542 0 : if( ae_fp_less_eq(s,4.0000) )
19543 : {
19544 0 : x = 2*(s-0.000000)/4.000000-1;
19545 0 : tj = (double)(1);
19546 0 : tj1 = x;
19547 0 : jarquebera_jbcheb(x, -1.026266e+00, &tj, &tj1, &result, _state);
19548 0 : jarquebera_jbcheb(x, -1.030061e+00, &tj, &tj1, &result, _state);
19549 0 : jarquebera_jbcheb(x, -1.259222e-03, &tj, &tj1, &result, _state);
19550 0 : jarquebera_jbcheb(x, 2.536254e-03, &tj, &tj1, &result, _state);
19551 0 : if( ae_fp_greater(result,(double)(0)) )
19552 : {
19553 0 : result = (double)(0);
19554 : }
19555 0 : return result;
19556 : }
19557 0 : if( ae_fp_less_eq(s,15.0000) )
19558 : {
19559 0 : x = 2*(s-4.000000)/11.000000-1;
19560 0 : tj = (double)(1);
19561 0 : tj1 = x;
19562 0 : jarquebera_jbcheb(x, -4.329849e+00, &tj, &tj1, &result, _state);
19563 0 : jarquebera_jbcheb(x, -2.095443e+00, &tj, &tj1, &result, _state);
19564 0 : jarquebera_jbcheb(x, 1.759363e-01, &tj, &tj1, &result, _state);
19565 0 : jarquebera_jbcheb(x, -7.751359e-03, &tj, &tj1, &result, _state);
19566 0 : jarquebera_jbcheb(x, -6.124368e-03, &tj, &tj1, &result, _state);
19567 0 : jarquebera_jbcheb(x, -1.793114e-03, &tj, &tj1, &result, _state);
19568 0 : if( ae_fp_greater(result,(double)(0)) )
19569 : {
19570 0 : result = (double)(0);
19571 : }
19572 0 : return result;
19573 : }
19574 0 : if( ae_fp_less_eq(s,25.0000) )
19575 : {
19576 0 : x = 2*(s-15.000000)/10.000000-1;
19577 0 : tj = (double)(1);
19578 0 : tj1 = x;
19579 0 : jarquebera_jbcheb(x, -7.544330e+00, &tj, &tj1, &result, _state);
19580 0 : jarquebera_jbcheb(x, -1.225382e+00, &tj, &tj1, &result, _state);
19581 0 : jarquebera_jbcheb(x, 5.392349e-02, &tj, &tj1, &result, _state);
19582 0 : if( ae_fp_greater(result,(double)(0)) )
19583 : {
19584 0 : result = (double)(0);
19585 : }
19586 0 : return result;
19587 : }
19588 0 : result = -2.019375e-01*(s-2.500000e+01)-8.715788e+00;
19589 0 : return result;
19590 : }
19591 :
19592 :
19593 0 : static void jarquebera_jbcheb(double x,
19594 : double c,
19595 : double* tj,
19596 : double* tj1,
19597 : double* r,
19598 : ae_state *_state)
19599 : {
19600 : double t;
19601 :
19602 :
19603 0 : *r = *r+c*(*tj);
19604 0 : t = 2*x*(*tj1)-(*tj);
19605 0 : *tj = *tj1;
19606 0 : *tj1 = t;
19607 0 : }
19608 :
19609 :
19610 : #endif
19611 : #if defined(AE_COMPILE_VARIANCETESTS) || !defined(AE_PARTIAL_BUILD)
19612 :
19613 :
19614 : /*************************************************************************
19615 : Two-sample F-test
19616 :
19617 : This test checks three hypotheses about dispersions of the given samples.
19618 : The following tests are performed:
19619 : * two-tailed test (null hypothesis - the dispersions are equal)
19620 : * left-tailed test (null hypothesis - the dispersion of the first
19621 : sample is greater than or equal to the dispersion of the second
19622 : sample).
19623 : * right-tailed test (null hypothesis - the dispersion of the first
19624 : sample is less than or equal to the dispersion of the second sample)
19625 :
19626 : The test is based on the following assumptions:
19627 : * the given samples have normal distributions
19628 : * the samples are independent.
19629 :
19630 : Input parameters:
19631 : X - sample 1. Array whose index goes from 0 to N-1.
19632 : N - sample size.
19633 : Y - sample 2. Array whose index goes from 0 to M-1.
19634 : M - sample size.
19635 :
19636 : Output parameters:
19637 : BothTails - p-value for two-tailed test.
19638 : If BothTails is less than the given significance level
19639 : the null hypothesis is rejected.
19640 : LeftTail - p-value for left-tailed test.
19641 : If LeftTail is less than the given significance level,
19642 : the null hypothesis is rejected.
19643 : RightTail - p-value for right-tailed test.
19644 : If RightTail is less than the given significance level
19645 : the null hypothesis is rejected.
19646 :
19647 : -- ALGLIB --
19648 : Copyright 19.09.2006 by Bochkanov Sergey
19649 : *************************************************************************/
19650 0 : void ftest(/* Real */ ae_vector* x,
19651 : ae_int_t n,
19652 : /* Real */ ae_vector* y,
19653 : ae_int_t m,
19654 : double* bothtails,
19655 : double* lefttail,
19656 : double* righttail,
19657 : ae_state *_state)
19658 : {
19659 : ae_int_t i;
19660 : double xmean;
19661 : double ymean;
19662 : double xvar;
19663 : double yvar;
19664 : ae_int_t df1;
19665 : ae_int_t df2;
19666 : double stat;
19667 :
19668 0 : *bothtails = 0;
19669 0 : *lefttail = 0;
19670 0 : *righttail = 0;
19671 :
19672 0 : if( n<=2||m<=2 )
19673 : {
19674 0 : *bothtails = 1.0;
19675 0 : *lefttail = 1.0;
19676 0 : *righttail = 1.0;
19677 0 : return;
19678 : }
19679 :
19680 : /*
19681 : * Mean
19682 : */
19683 0 : xmean = (double)(0);
19684 0 : for(i=0; i<=n-1; i++)
19685 : {
19686 0 : xmean = xmean+x->ptr.p_double[i];
19687 : }
19688 0 : xmean = xmean/n;
19689 0 : ymean = (double)(0);
19690 0 : for(i=0; i<=m-1; i++)
19691 : {
19692 0 : ymean = ymean+y->ptr.p_double[i];
19693 : }
19694 0 : ymean = ymean/m;
19695 :
19696 : /*
19697 : * Variance (using corrected two-pass algorithm)
19698 : */
19699 0 : xvar = (double)(0);
19700 0 : for(i=0; i<=n-1; i++)
19701 : {
19702 0 : xvar = xvar+ae_sqr(x->ptr.p_double[i]-xmean, _state);
19703 : }
19704 0 : xvar = xvar/(n-1);
19705 0 : yvar = (double)(0);
19706 0 : for(i=0; i<=m-1; i++)
19707 : {
19708 0 : yvar = yvar+ae_sqr(y->ptr.p_double[i]-ymean, _state);
19709 : }
19710 0 : yvar = yvar/(m-1);
19711 0 : if( ae_fp_eq(xvar,(double)(0))||ae_fp_eq(yvar,(double)(0)) )
19712 : {
19713 0 : *bothtails = 1.0;
19714 0 : *lefttail = 1.0;
19715 0 : *righttail = 1.0;
19716 0 : return;
19717 : }
19718 :
19719 : /*
19720 : * Statistic
19721 : */
19722 0 : df1 = n-1;
19723 0 : df2 = m-1;
19724 0 : stat = ae_minreal(xvar/yvar, yvar/xvar, _state);
19725 0 : *bothtails = 1-(fdistribution(df1, df2, 1/stat, _state)-fdistribution(df1, df2, stat, _state));
19726 0 : *lefttail = fdistribution(df1, df2, xvar/yvar, _state);
19727 0 : *righttail = 1-(*lefttail);
19728 : }
19729 :
19730 :
19731 : /*************************************************************************
19732 : One-sample chi-square test
19733 :
19734 : This test checks three hypotheses about the dispersion of the given sample
19735 : The following tests are performed:
19736 : * two-tailed test (null hypothesis - the dispersion equals the given
19737 : number)
19738 : * left-tailed test (null hypothesis - the dispersion is greater than
19739 : or equal to the given number)
19740 : * right-tailed test (null hypothesis - dispersion is less than or
19741 : equal to the given number).
19742 :
19743 : Test is based on the following assumptions:
19744 : * the given sample has a normal distribution.
19745 :
19746 : Input parameters:
19747 : X - sample 1. Array whose index goes from 0 to N-1.
19748 : N - size of the sample.
19749 : Variance - dispersion value to compare with.
19750 :
19751 : Output parameters:
19752 : BothTails - p-value for two-tailed test.
19753 : If BothTails is less than the given significance level
19754 : the null hypothesis is rejected.
19755 : LeftTail - p-value for left-tailed test.
19756 : If LeftTail is less than the given significance level,
19757 : the null hypothesis is rejected.
19758 : RightTail - p-value for right-tailed test.
19759 : If RightTail is less than the given significance level
19760 : the null hypothesis is rejected.
19761 :
19762 : -- ALGLIB --
19763 : Copyright 19.09.2006 by Bochkanov Sergey
19764 : *************************************************************************/
19765 0 : void onesamplevariancetest(/* Real */ ae_vector* x,
19766 : ae_int_t n,
19767 : double variance,
19768 : double* bothtails,
19769 : double* lefttail,
19770 : double* righttail,
19771 : ae_state *_state)
19772 : {
19773 : ae_int_t i;
19774 : double xmean;
19775 : double xvar;
19776 : double s;
19777 : double stat;
19778 :
19779 0 : *bothtails = 0;
19780 0 : *lefttail = 0;
19781 0 : *righttail = 0;
19782 :
19783 0 : if( n<=1 )
19784 : {
19785 0 : *bothtails = 1.0;
19786 0 : *lefttail = 1.0;
19787 0 : *righttail = 1.0;
19788 0 : return;
19789 : }
19790 :
19791 : /*
19792 : * Mean
19793 : */
19794 0 : xmean = (double)(0);
19795 0 : for(i=0; i<=n-1; i++)
19796 : {
19797 0 : xmean = xmean+x->ptr.p_double[i];
19798 : }
19799 0 : xmean = xmean/n;
19800 :
19801 : /*
19802 : * Variance
19803 : */
19804 0 : xvar = (double)(0);
19805 0 : for(i=0; i<=n-1; i++)
19806 : {
19807 0 : xvar = xvar+ae_sqr(x->ptr.p_double[i]-xmean, _state);
19808 : }
19809 0 : xvar = xvar/(n-1);
19810 0 : if( ae_fp_eq(xvar,(double)(0)) )
19811 : {
19812 0 : *bothtails = 1.0;
19813 0 : *lefttail = 1.0;
19814 0 : *righttail = 1.0;
19815 0 : return;
19816 : }
19817 :
19818 : /*
19819 : * Statistic
19820 : */
19821 0 : stat = (n-1)*xvar/variance;
19822 0 : s = chisquaredistribution((double)(n-1), stat, _state);
19823 0 : *bothtails = 2*ae_minreal(s, 1-s, _state);
19824 0 : *lefttail = s;
19825 0 : *righttail = 1-(*lefttail);
19826 : }
19827 :
19828 :
19829 : #endif
19830 :
19831 : }
19832 :
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