Rev 45874 | Blame | Compare with Previous | Last modification | View Log | Download | RSS feed
/** R : A Computer Language for Statistical Data Analysis* Copyright (C) 1995, 1996 Robert Gentleman and Ross Ihaka* Copyright (C) 1998--2007 The R Development Core Team* based on code (C) 1979 and later Royal Statistical Society** This program is free software; you can redistribute it and/or modify* it under the terms of the GNU General Public License as published by* the Free Software Foundation; either version 2 of the License, or* (at your option) any later version.** This program is distributed in the hope that it will be useful,* but WITHOUT ANY WARRANTY; without even the implied warranty of* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the* GNU General Public License for more details.** You should have received a copy of the GNU General Public License* along with this program; if not, a copy is available at* http://www.r-project.org/Licenses/** Reference:* Cran, G. W., K. J. Martin and G. E. Thomas (1977).* Remark AS R19 and Algorithm AS 109,* Applied Statistics, 26(1), 111-114.* Remark AS R83 (v.39, 309-310) and the correction (v.40(1) p.236)* have been incorporated in this version.*/#include "nmath.h"#include "dpq.h"/* set the exponent of accu to -2r-2 for r digits of accuracy *//*---- NEW ---- -- still fails for p = 1e11, q=.5*/#define fpu 3e-308/* acu_min: Minimal value for accuracy 'acu' which will depend on (a,p);acu_min >= fpu ! */#define acu_min 1e-300#define lower fpu#define upper 1-2.22e-16#define const1 2.30753#define const2 0.27061#define const3 0.99229#define const4 0.04481double qbeta(double alpha, double p, double q, int lower_tail, int log_p){int swap_tail, i_pb, i_inn;double a, adj, logbeta, g, h, pp, p_, prev, qq, r, s, t, tx, w, y, yprev;double acu;volatile double xinbta;/* test for admissibility of parameters */#ifdef IEEE_754if (ISNAN(p) || ISNAN(q) || ISNAN(alpha))return p + q + alpha;#endifif(p < 0. || q < 0.) ML_ERR_return_NAN;R_Q_P01_boundaries(alpha, 0, 1);p_ = R_DT_qIv(alpha);/* lower_tail prob (in any case) */if(log_p && (p_ == 0. || p_ == 1.))return p_; /* better than NaN or infinite loop;FIXME: suboptimal, since -Inf < alpha ! *//* initialize */logbeta = lbeta(p, q);/* change tail if necessary; afterwards 0 < a <= 1/2 */if (p_ <= 0.5) {a = p_; pp = p; qq = q; swap_tail = 0;} else { /* change tail, swap p <-> q :*/a = (!lower_tail && !log_p)? alpha : 1 - p_;pp = q; qq = p; swap_tail = 1;}/* calculate the initial approximation *//* y := {fast approximation of} qnorm(1 - a) :*/r = sqrt(-2 * log(a));y = r - (const1 + const2 * r) / (1. + (const3 + const4 * r) * r);if (pp > 1 && qq > 1) {r = (y * y - 3.) / 6.;s = 1. / (pp + pp - 1.);t = 1. / (qq + qq - 1.);h = 2. / (s + t);w = y * sqrt(h + r) / h - (t - s) * (r + 5. / 6. - 2. / (3. * h));xinbta = pp / (pp + qq * exp(w + w));} else {r = qq + qq;t = 1. / (9. * qq);t = r * pow(1. - t + y * sqrt(t), 3.0);if (t <= 0.)xinbta = 1. - exp((log1p(-a)+ log(qq) + logbeta) / qq);else {t = (4. * pp + r - 2.) / t;if (t <= 1.)xinbta = exp((log(a * pp) + logbeta) / pp);elsexinbta = 1. - 2. / (t + 1.);}}/* solve for x by a modified newton-raphson method, *//* using the function pbeta_raw */r = 1 - pp;t = 1 - qq;yprev = 0.;adj = 1;/* Sometimes the approximation is negative! */if (xinbta < lower)xinbta = 0.5;else if (xinbta > upper)xinbta = 0.5;/* Desired accuracy should depend on (a,p)* This is from Remark .. on AS 109, adapted.* However, it's not clear if this is "optimal" for IEEE double prec.* acu = fmax2(acu_min, pow(10., -25. - 5./(pp * pp) - 1./(a * a)));* NEW: 'acu' accuracy NOT for squared adjustment, but simple;* ---- i.e., "new acu" = sqrt(old acu)*/acu = fmax2(acu_min, pow(10., -13 - 2.5/(pp * pp) - 0.5/(a * a)));tx = prev = 0.; /* keep -Wall happy */for (i_pb=0; i_pb < 1000; i_pb++) {y = pbeta_raw(xinbta, pp, qq, /*lower_tail = */ TRUE, FALSE);#ifdef IEEE_754if(!R_FINITE(y))#elseif (errno)#endifML_ERR_return_NAN;y = (y - a) *exp(logbeta + r * log(xinbta) + t * log1p(-xinbta));if (y * yprev <= 0.)prev = fmax2(fabs(adj),fpu);g = 1;for (i_inn=0; i_inn < 1000;i_inn++) {adj = g * y;if (fabs(adj) < prev) {tx = xinbta - adj; /* trial new x */if (tx >= 0. && tx <= 1) {if (prev <= acu) goto L_converged;if (fabs(y) <= acu) goto L_converged;if (tx != 0. && tx != 1)break;}}g /= 3;}if (fabs(tx - xinbta) < 1e-15*xinbta) goto L_converged;xinbta = tx;yprev = y;}/*-- NOT converged: Iteration count --*/ML_ERROR(ME_PRECISION, "qbeta");L_converged:return swap_tail ? 1 - xinbta : xinbta;}