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[gnumeric.git] / src / sf-dpq.c
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1 #include <gnumeric-config.h>
2 #include <sf-dpq.h>
3 #include <mathfunc.h>
5 #define give_log log_p
6 #define R_D__0 (log_p ? gnm_ninf : 0.0)
7 #define R_D__1 (log_p ? 0.0 : 1.0)
8 #define R_DT_0 (lower_tail ? R_D__0 : R_D__1)
9 #define R_DT_1 (lower_tail ? R_D__1 : R_D__0)
10 #define M_1_SQRT_2PI GNM_const(0.398942280401432677939946059934) /* 1/sqrt(2pi) */
11 #define M_SQRT_2PI GNM_const(2.506628274631000502415765284811045253006986740609938316629923)
13 /* ------------------------------------------------------------------------- */
15 #undef DEBUG_pfuncinverter
17 /**
18 * pfuncinverter:
19 * @p:
20 * @shape:
21 * @lower_tail:
22 * @log_p:
23 * @xlow:
24 * @xhigh:
25 * @x0:
26 * @pfunc: (scope call):
27 * @dpfunc_dx: (scope call):
29 * Returns:
30 **/
31 gnm_float
32 pfuncinverter (gnm_float p, const gnm_float shape[],
33 gboolean lower_tail, gboolean log_p,
34 gnm_float xlow, gnm_float xhigh, gnm_float x0,
35 GnmPFunc pfunc, GnmDPFunc dpfunc_dx)
37 gboolean have_xlow = gnm_finite (xlow);
38 gboolean have_xhigh = gnm_finite (xhigh);
39 gnm_float exlow, exhigh;
40 gnm_float x = 0, e = 0, px;
41 int i;
43 g_return_val_if_fail (pfunc != NULL, gnm_nan);
45 if (log_p ? (p > 0) : (p < 0 || p > 1))
46 return gnm_nan;
48 if (p == R_DT_0) return xlow;
49 if (p == R_DT_1) return xhigh;
51 exlow = R_DT_0 - p;
52 exhigh = R_DT_1 - p;
53 if (!lower_tail) {
54 exlow = -exlow;
55 exhigh = -exhigh;
58 #ifdef DEBUG_pfuncinverter
59 g_printerr ("p=%.15g\n", p);
60 #endif
62 for (i = 0; i < 100; i++) {
63 if (i == 0) {
64 if (x0 > xlow && x0 < xhigh)
65 /* Use supplied guess. */
66 x = x0;
67 else if (have_xlow && x0 <= xlow)
68 x = xlow + have_xhigh ? (xhigh - xlow) / 100 : 1;
69 else if (have_xhigh && x0 >= xhigh)
70 x = xhigh - have_xlow ? (xhigh - xlow) / 100 : 1;
71 else
72 x = 0; /* Whatever */
73 } else if (i == 1) {
75 * Under the assumption that the initial guess was
76 * good, pick a nearby point that is hopefully on
77 * the other side. If we already have both sides,
78 * just bisect.
80 if (have_xlow && have_xhigh)
81 x = (xlow + xhigh) / 2;
82 else if (have_xlow)
83 x = xlow * 1.1;
84 else
85 x = xhigh / 1.1;
86 } else if (have_xlow && have_xhigh) {
87 switch (i % 8) {
88 case 0:
89 x = xhigh - (xhigh - xlow) *
90 (exhigh / (exhigh - exlow));
91 break;
92 case 4:
93 /* Half-way in log-space. */
94 if (xlow >= 0 && xhigh >= 0)
95 x = gnm_sqrt (MAX (GNM_MIN, xlow)) * gnm_sqrt (xhigh);
96 else if (xlow <= 0 && xhigh <= 0)
97 x = -gnm_sqrt (-xlow) * gnm_sqrt (MAX (GNM_MIN, -xhigh));
98 else
99 x = 0;
100 break;
101 case 2:
102 x = (xhigh + 1000 * xlow) / 1001;
103 break;
104 case 6:
105 x = (1000 * xhigh + xlow) / 1001;
106 break;
107 default:
108 x = (xhigh + xlow) / 2;
110 } else if (have_xlow) {
111 /* Agressively seek right in search of xhigh. */
112 x = (xlow < 1) ? 1 : (2 * i) * xlow;
113 } else {
114 /* Agressively seek left in search of xlow. */
115 x = (xhigh > -1) ? -1 : (2 * i) * xhigh;
118 newton_retry:
119 if ((have_xlow && x <= xlow) || (have_xhigh && x >= xhigh))
120 continue;
122 px = pfunc (x, shape, lower_tail, log_p);
123 e = px - p;
124 if (!lower_tail) e = -e;
126 #ifdef DEBUG_pfuncinverter
127 g_printerr ("%3d: x=%.15g e=%.15g l=%.15g h=%.15g\n",
128 i, x, e, xlow, xhigh);
129 #endif
131 if (e == 0)
132 goto done;
133 else if (e > 0) {
134 xhigh = x;
135 exhigh = e;
136 have_xhigh = TRUE;
137 } else if (e < 0) {
138 xlow = x;
139 exlow = e;
140 have_xlow = TRUE;
141 } else {
142 /* We got a NaN. */
145 if (have_xlow && have_xhigh) {
146 gnm_float prec = (xhigh - xlow) /
147 (gnm_abs (xlow) + gnm_abs (xhigh));
148 if (prec < GNM_EPSILON * 4) {
149 x = (xhigh + xlow) / 2;
150 e = pfunc (x, shape, lower_tail, log_p) - p;
151 if (!lower_tail) e = -e;
152 goto done;
155 if (dpfunc_dx && i % 3 < 2 && (i == 0 || prec < 0.05)) {
156 gnm_float d = dpfunc_dx (x, shape, log_p);
157 if (log_p) d = gnm_exp (d - px);
158 #ifdef DEBUG_pfuncinverter
159 g_printerr ("Newton: d=%-.14g\n", d);
160 #endif
161 if (d) {
163 * Deliberately overshoot a bit to help
164 * with getting good points on both
165 * sides of the root.
167 x = x - e / d * 1.000001;
168 if (x > xlow && x < xhigh) {
169 #ifdef DEBUG_pfuncinverter
170 g_printerr ("Newton ok\n");
171 #endif
172 i++;
173 goto newton_retry;
175 } else {
176 #ifdef DEBUG_pfuncinverter
177 g_printerr ("Newton d=0\n");
178 #endif
184 #ifdef DEBUG_pfuncinverter
185 g_printerr ("Failed to converge\n");
186 #endif
188 done:
189 /* Make sure to keep a lucky near-hit. */
191 if (have_xhigh && gnm_abs (e) > exhigh)
192 e = exhigh, x = xhigh;
193 if (have_xlow && gnm_abs (e) > -exlow)
194 e = exlow, x = xlow;
196 #ifdef DEBUG_pfuncinverter
197 g_printerr ("--> %.15g\n\n", x);
198 #endif
199 return x;
203 * discpfuncinverter:
204 * @p:
205 * @shape:
206 * @lower_tail:
207 * @log_p:
208 * @xlow:
209 * @xhigh:
210 * @x0:
211 * @pfunc: (scope call):
213 * Discrete pfuncs only. (Specifically: only integer x are allowed).
214 * Returns:
216 gnm_float
217 discpfuncinverter (gnm_float p, const gnm_float shape[],
218 gboolean lower_tail, gboolean log_p,
219 gnm_float xlow, gnm_float xhigh, gnm_float x0,
220 GnmPFunc pfunc)
222 gboolean have_xlow = gnm_finite (xlow);
223 gboolean have_xhigh = gnm_finite (xhigh);
224 gboolean check_left = TRUE;
225 gnm_float step;
226 int i;
228 if (log_p ? (p > 0) : (p < 0 || p > 1))
229 return gnm_nan;
231 if (p == R_DT_0) return xlow;
232 if (p == R_DT_1) return xhigh;
234 if (gnm_finite (x0) && x0 >= xlow && x0 <= xhigh)
235 ; /* Nothing -- guess is good. */
236 else if (have_xlow && have_xhigh)
237 x0 = (xlow + xhigh) / 2;
238 else if (have_xhigh)
239 x0 = xhigh;
240 else if (have_xlow)
241 x0 = xlow;
242 else
243 x0 = 0;
244 x0 = gnm_floor (x0 + 0.5);
245 step = 1 + gnm_floor (gnm_abs (x0) * GNM_EPSILON);
247 #if 0
248 g_printerr ("step=%.20g\n", step);
249 #endif
251 for (i = 1; 1; i++) {
252 gnm_float ex0 = pfunc (x0, shape, lower_tail, log_p) - p;
253 #if 0
254 g_printerr ("x=%.20g e=%.20g\n", x0, ex0);
255 #endif
256 if (!lower_tail) ex0 = -ex0;
258 if (ex0 == 0)
259 return x0;
260 else if (ex0 < 0)
261 xlow = x0, have_xlow = TRUE, check_left = FALSE;
262 else if (ex0 > 0)
263 xhigh = x0, have_xhigh = TRUE, step = -gnm_abs (step);
265 if (i > 1 && have_xlow && have_xhigh) {
266 gnm_float xmid = gnm_floor ((xlow + xhigh) / 2);
267 if (xmid - xlow < 0.5 ||
268 xmid - xlow < gnm_abs (xlow) * GNM_EPSILON) {
269 if (check_left) {
271 * The lower edge of the support might
272 * have a probability higher than what
273 * we are looking for.
275 gnm_float e = pfunc (xlow, shape, lower_tail, log_p) - p;
276 if (!lower_tail) e = -e;
277 if (e >= 0)
278 return xhigh = xlow;
280 return xhigh;
282 x0 = xmid;
283 } else {
284 gnm_float x1 = x0 + step;
286 if (x1 == x0) {
287 /* Probably infinite. */
288 return gnm_nan;
289 } else if (x1 >= xlow && x1 <= xhigh) {
290 x0 = x1;
291 step *= 2 * i;
292 } else {
293 /* We went off the edge by walking too fast. */
294 gnm_float newstep = 1 + gnm_floor (gnm_abs (x0) * GNM_EPSILON);
295 step = (step > 0) ? newstep : -newstep;
296 x1 = x0 + step;
297 if (x1 >= xlow && x1 <= xhigh)
298 continue;
300 * We don't seem to find a finite x on the
301 * other side of the root.
303 return (step > 0) ? xhigh : xlow;
308 g_assert_not_reached ();
311 /* ------------------------------------------------------------------------ */
314 * dnorm:
315 * @x: observation
316 * @mu: mean of the distribution
317 * @sigma: standard deviation of the distribution
318 * @give_log: if %TRUE, log of the result will be returned instead
320 * Returns: density of the normal distribution.
322 gnm_float
323 dnorm (gnm_float x, gnm_float mu, gnm_float sigma, gboolean give_log)
325 gnm_float x0;
327 if (gnm_isnan (x) || gnm_isnan (mu) || gnm_isnan (sigma))
328 return x + mu + sigma;
329 if (sigma < 0)
330 return gnm_nan;
332 /* Center. */
333 x = x0 = gnm_abs (x - mu);
334 x /= sigma;
336 if (give_log)
337 return -(M_LN_SQRT_2PI + 0.5 * x * x + gnm_log (sigma));
338 else if (x > 3 + 2 * gnm_sqrt (gnm_log (GNM_MAX)))
339 /* Far into the tail; x > ~100 for long double */
340 return 0;
341 else if (x > 4) {
343 * Split x into xh+xl such that:
344 * 1) xh*xh is exact
345 * 2) 0 <= xl <= 1/65536
346 * 3) 0 <= xl*xh < ~100/65536
348 gnm_float xh = gnm_floor (x * 65536) / 65536; /* At most 24 bits */
349 gnm_float xl = (x0 - xh * sigma) / sigma;
350 return M_1_SQRT_2PI *
351 gnm_exp (-0.5 * (xh * xh)) *
352 gnm_exp (-xl * (0.5 * xl + xh)) /
353 sigma;
354 } else
355 /* Near-center case. */
356 return M_1_SQRT_2PI * expmx2h (x) / sigma;
359 gnm_float
360 pnorm2 (gnm_float x1, gnm_float x2)
362 if (gnm_isnan (x1) || gnm_isnan (x2))
363 return gnm_nan;
365 if (x1 > x2)
366 return 0 - pnorm2 (x2, x1);
368 /* A bunch of special cases: */
369 if (x1 == x2)
370 return 0.0;
371 if (x1 == gnm_ninf)
372 return pnorm (x2, 0.0, 1.0, TRUE, FALSE);
373 if (x2 == gnm_pinf)
374 return pnorm (x1, 0.0, 1.0, FALSE, FALSE);
375 if (x1 == 0)
376 return gnm_erf (x2 / M_SQRT2gnum) / 2;
377 if (x2 == 0)
378 return gnm_erf (x1 / -M_SQRT2gnum) / 2;
380 if (x1 <= 0 && x2 >= 0) {
381 /* The interval spans 0. */
382 gnm_float p1 = pnorm2 (0, MIN (-x1, x2));
383 gnm_float p2 = pnorm2 (MIN (-x1, x2), MAX (-x1, x2));
384 return 2 * p1 + p2;
385 } else if (x1 < 0) {
386 /* Both < 0 -- use symmetry */
387 return pnorm2 (-x2, -x1);
388 } else {
389 /* Both >= 0 */
390 gnm_float p1C = pnorm (x1, 0.0, 1.0, FALSE, FALSE);
391 gnm_float p2C = pnorm (x2, 0.0, 1.0, FALSE, FALSE);
392 gnm_float raw = p1C - p2C;
393 gnm_float dx, d1, d2, ub, lb;
395 if (gnm_abs (p1C - p2C) * 32 > gnm_abs (p1C + p2C))
396 return raw;
398 /* dnorm is strictly decreasing in this area. */
399 dx = x2 - x1;
400 d1 = dnorm (x1, 0.0, 1.0, FALSE);
401 d2 = dnorm (x2, 0.0, 1.0, FALSE);
402 ub = dx * d1; /* upper bound */
403 lb = dx * d2; /* lower bound */
405 raw = MAX (raw, lb);
406 raw = MIN (raw, ub);
407 return raw;
411 /* ------------------------------------------------------------------------ */
414 * dlnorm:
415 * @x: observation
416 * @logmean: mean of the underlying normal distribution
417 * @logsd: standard deviation of the underlying normal distribution
418 * @give_log: if %TRUE, log of the result will be returned instead
420 * Returns: density of the log-normal distribution.
422 gnm_float
423 dlnorm (gnm_float x, gnm_float logmean, gnm_float logsd, gboolean give_log)
425 void *state;
426 GnmQuad qx, qlx, qs, qy, qt;
427 static GnmQuad qsqrt2pi;
428 gnm_float r;
430 if (gnm_isnan (x) || gnm_isnan (logmean) || gnm_isnan (logsd))
431 return x + logmean + logsd;
433 if (logsd <= 0)
434 return gnm_nan;
436 if (x <= 0)
437 return R_D__0;
439 state = gnm_quad_start ();
440 if (qsqrt2pi.h == 0)
441 gnm_quad_sqrt (&qsqrt2pi, &gnm_quad_2pi);
442 gnm_quad_init (&qx, x);
443 gnm_quad_log (&qlx, &qx);
444 gnm_quad_init (&qt, logmean);
445 gnm_quad_sub (&qy, &qlx, &qt);
446 gnm_quad_init (&qs, logsd);
447 gnm_quad_div (&qy, &qy, &qs);
448 gnm_quad_mul (&qy, &qy, &qy);
449 qy.h *= -0.5; qy.l *= -0.5;
450 gnm_quad_mul (&qt, &qs, &qx);
451 gnm_quad_mul (&qt, &qt, &qsqrt2pi);
452 if (give_log) {
453 gnm_quad_log (&qt, &qt);
454 gnm_quad_sub (&qy, &qy, &qt);
455 } else {
456 gnm_quad_exp (&qy, NULL, &qy);
457 gnm_quad_div (&qy, &qy, &qt);
459 r = gnm_quad_value (&qy);
460 gnm_quad_end (state);
462 return r;
465 /* ------------------------------------------------------------------------ */
468 * plnorm:
469 * @x: observation
470 * @logmean: mean of the underlying normal distribution
471 * @logsd: standard deviation of the underlying normal distribution
472 * @lower_tail: if %TRUE, the lower tail of the distribution is considered.
473 * @log_p: if %TRUE, log of the result will be returned instead
475 * Returns: cumulative density of the log-normal distribution.
477 gnm_float
478 plnorm (gnm_float x, gnm_float logmean, gnm_float logsd, gboolean lower_tail, gboolean log_p)
480 if (gnm_isnan (x) || gnm_isnan (logmean) || gnm_isnan (logsd))
481 return x + logmean + logsd;
483 if (logsd <= 0)
484 return gnm_nan;
486 return (x > 0)
487 ? pnorm (gnm_log (x), logmean, logsd, lower_tail, log_p)
488 : R_D__0;
491 /* ------------------------------------------------------------------------ */
494 * qlnorm:
495 * @p: probability
496 * @logmean: mean of the underlying normal distribution
497 * @logsd: standard deviation of the underlying normal distribution
498 * @lower_tail: if %TRUE, the lower tail of the distribution is considered.
499 * @log_p: if %TRUE, @p is given as log probability
501 * Returns: the observation with cumulative probability @p for the
502 * log-normal distribution.
504 gnm_float
505 qlnorm (gnm_float p, gnm_float logmean, gnm_float logsd, gboolean lower_tail, gboolean log_p)
507 if (gnm_isnan (p) || gnm_isnan (logmean) || gnm_isnan (logsd))
508 return p + logmean + logsd;
510 if (log_p ? (p > 0) : (p < 0 || p > 1))
511 return gnm_nan;
513 return gnm_exp (qnorm (p, logmean, logsd, lower_tail, log_p));
516 /* ------------------------------------------------------------------------ */
518 static gnm_float
519 dcauchy1 (gnm_float x, const gnm_float shape[], gboolean give_log)
521 return dcauchy (x, shape[0], shape[1], give_log);
524 static gnm_float
525 pcauchy1 (gnm_float x, const gnm_float shape[], gboolean lower_tail, gboolean log_p)
527 return pcauchy (x, shape[0], shape[1], lower_tail, log_p);
531 * qcauchy:
532 * @p: probability
533 * @location: center of distribution
534 * @scale: scale parameter of the distribution
535 * @lower_tail: if %TRUE, the lower tail of the distribution is considered.
536 * @log_p: if %TRUE, @p is given as log probability
538 * Returns: the observation with cumulative probability @p for the
539 * Cauchy distribution.
542 gnm_float
543 qcauchy (gnm_float p, gnm_float location, gnm_float scale,
544 gboolean lower_tail, gboolean log_p)
546 gnm_float x;
548 if (gnm_isnan(p) || gnm_isnan(location) || gnm_isnan(scale))
549 return p + location + scale;
551 if (log_p ? (p > 0) : (p < 0 || p > 1))
552 return gnm_nan;
554 if (scale < 0 || !gnm_finite(scale)) return gnm_nan;
556 if (log_p) {
557 if (p > -1)
558 /* The "0" here is important for the p=0 case: */
559 lower_tail = !lower_tail, p = 0 - gnm_expm1 (p);
560 else
561 p = gnm_exp (p);
562 log_p = FALSE;
563 } else {
564 if (p > 0.5) {
565 p = 1 - p;
566 lower_tail = !lower_tail;
569 x = location + (lower_tail ? -scale : scale) * gnm_cotpi (p);
571 if (location != 0 && gnm_abs (x / location) < 0.25) {
572 /* Cancellation has occurred. */
573 gnm_float shape[2];
574 shape[0] = location;
575 shape[1] = scale;
576 x = pfuncinverter (p, shape, lower_tail, log_p,
577 gnm_ninf, gnm_pinf, x,
578 pcauchy1, dcauchy1);
582 return x;
585 /* ------------------------------------------------------------------------ */
587 static gnm_float
588 phyper1 (gnm_float x, const gnm_float shape[],
589 gboolean lower_tail, gboolean log_p)
591 return phyper (x, shape[0], shape[1], shape[2], lower_tail, log_p);
594 gnm_float
595 qhyper (gnm_float p, gnm_float NR, gnm_float NB, gnm_float n,
596 gboolean lower_tail, gboolean log_p)
598 gnm_float y, shape[3];
599 gnm_float N = NR + NB;
601 if (gnm_isnan (p) || gnm_isnan (N) || gnm_isnan (n))
602 return p + N + n;
603 if(!gnm_finite (p) || !gnm_finite (N) ||
604 NR < 0 || NB < 0 || n < 0 || n > N)
605 return gnm_nan;
607 shape[0] = NR;
608 shape[1] = NB;
609 shape[2] = n;
611 if (N > 2) {
612 gnm_float mu = n * NR / N;
613 gnm_float sigma =
614 gnm_sqrt (NR * NB * n * (N - n) / (N * N * (N - 1)));
615 gnm_float sigma_gamma =
616 (N - 2 * NR) * (N - 2 * n) / ((N - 2) * N);
618 /* Cornish-Fisher expansion: */
619 gnm_float z = qnorm (p, 0., 1., lower_tail, log_p);
620 y = mu + sigma * z + sigma_gamma * (z * z - 1) / 6;
621 } else
622 y = 0;
624 return discpfuncinverter (p, shape, lower_tail, log_p,
625 MAX (0, n - NB), MIN (n, NR), y,
626 phyper1);
629 /* ------------------------------------------------------------------------ */
631 * drayleigh:
632 * @x: observation
633 * @scale: scale parameter
634 * @give_log: if %TRUE, log of the result will be returned instead
636 * Returns: density of the Rayleigh distribution.
639 gnm_float
640 drayleigh (gnm_float x, gnm_float scale, gboolean give_log)
642 // This is tempting, but has lower precision since sqrt(2)
643 // is inexact.
645 // return dweibull (x, 2, M_SQRT2gnum * scale, give_log);
647 if (scale <= 0)
648 return gnm_nan;
649 if (x <= 0)
650 return R_D__0;
651 else {
652 gnm_float p = dnorm (x, 0, scale, give_log);
653 return give_log
654 ? p + gnm_log (x / scale) + M_LN_SQRT_2PI
655 : p * x / scale * M_SQRT_2PI;
659 /* ------------------------------------------------------------------------ */
661 * prayleigh:
662 * @x: observation
663 * @scale: scale parameter
664 * @lower_tail: if %TRUE, the lower tail of the distribution is considered.
665 * @log_p: if %TRUE, log of the result will be returned instead
667 * Returns: cumulative density of the Rayleigh distribution.
670 gnm_float
671 prayleigh (gnm_float x, gnm_float scale, gboolean lower_tail, gboolean log_p)
673 return pweibull (x, 2, M_SQRT2gnum * scale, lower_tail, log_p);
678 * qrayleigh:
679 * @p: probability
680 * @scale: scale parameter
681 * @lower_tail: if %TRUE, the lower tail of the distribution is considered.
682 * @log_p: if %TRUE, log of the result will be returned instead
684 * Returns: the observation with cumulative probability @p for the
685 * Rayleigh distribution.
687 gnm_float
688 qrayleigh (gnm_float p, gnm_float scale, gboolean lower_tail, gboolean log_p)
690 return qweibull (p, 2, M_SQRT2gnum * scale, lower_tail, log_p);
693 /* ------------------------------------------------------------------------ */