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/** AUTHOR* Catherine Loader, catherine@research.bell-labs.com.* October 23, 2000.** Merge in to R and further tweaks :* notably using log1p() and pow1p(), thanks to Morten Welinder, PR#18642** Copyright (C) 2000-2025 The R Core Team* Copyright (C) 2008 The R Foundation** 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* https://www.R-project.org/Licenses/*** DESCRIPTION** To compute the binomial probability, call dbinom(x,n,p).* This checks for argument validity, and calls dbinom_raw().** dbinom_raw() does the actual computation; note this is called by* other functions in addition to dbinom().* (1) dbinom_raw() has both p and q arguments, when one may be represented* more accurately than the other (in particular, in df()).* (2) dbinom_raw() does NOT check that inputs x and n are integers. This* should be done in the calling function, where necessary.* -- but is not the case at all when called e.g., from df() or dbeta() !* (3) Also does not check for 0 <= p <= 1 and 0 <= q <= 1 or NaN's.* Do this in the calling function.*/#include "nmath.h"#include "dpq.h"/* Compute (1+x)^y accurately also for |x| << 1 */double pow1p(double x, double y){if(isnan(y))return (x == 0) ? 1. : y; // (0+1)^NaN := 1 by standardsif(0 <= y && y == trunc(y) && y <= 4.) {switch((int)y) {case 0: return 1;case 1: return x + 1.;case 2: return x*(x + 2.) + 1.;case 3: return x*(x*(x + 3.) + 3.) + 1.;case 4: return x*(x*(x*(x + 4.) + 6.) + 4.) + 1.;}}/* naive algorithm in two cases: (1) when 1+x is exact (compiler should not over-optimize !),* and (2) when |x| > 1/2 and we have no better algorithm.*/volatile double xp1 = x + 1., x_ = xp1 - 1.; // compiler should *not* optimize theseif (x_ == x || fabs(x) > 0.5 || isnan(x)) {return pow(xp1, y);} else { /* not perfect, e.g., for small |x|, non-huge y, usebinom expansion 1 + y*x + y(y-1)/2 x^2 + .. */return exp(y * log1p(x));}}double dbinom_raw(double x, double n, double p, double q, int give_log){if (p == 0) return((x == 0) ? R_D__1 : R_D__0);if (q == 0) return((x == n) ? R_D__1 : R_D__0);// NB: The smaller of p and q is the most accurateif (x == 0) {if(n == 0) return R_D__1;if (p > q)return give_log ? n * log(q) : pow(q, n);else // 0 < p <= 1/2return give_log ? n * log1p(-p) : pow1p(-p, n);}if (x == n) { // r = p^x = p^n -- accuratelyif (p > q)return give_log ? n * log1p(-q) : pow1p(-q, n);elsereturn give_log ? n * log (p) : pow (p, n);}if (x < 0 || x > n) return( R_D__0 );if(!R_FINITE(n)) {if(R_FINITE(x)) return( R_D__0 ); /* finite x << n = Inf */else n = DBL_MAX; // helps ? extreme dnbinom() cases}// TODO? Improve accuracy in these cases:#ifdef _NO_LOG_DBINOM_if(!give_log) { // more accurate *not* going via log when result is much much smaller than 1if (x <= M || n-x <= M) { /* use "recursive" direct formula withk := min(x, n-x) multiplications */}}#endif/* n*p or n*q can underflow to zero if n and p or q are small. Thisused to occur in dbeta, and gives NaN as from R 2.3.0. */double lc = stirlerr(n) - stirlerr(x) - stirlerr(n-x) - bd0(x,n*p) - bd0(n-x,n*q);/* f = (M_2PI*x*(n-x))/n; could overflow or underflow *//* Upto R 2.7.1:* lf = log(M_2PI) + log(x) + log(n-x) - log(n);* -- following is much better for x << n : */double lf = M_LN_2PI + log(x) + log1p(- x/n);return R_D_exp(lc - 0.5*lf);}double dbinom(double x, double n, double p, int give_log){#ifdef IEEE_754/* NaNs propagated correctly */if (ISNAN(x) || ISNAN(n) || ISNAN(p)) return x + n + p;#endifif (p < 0 || p > 1 || R_D_negInonint(n))ML_WARN_return_NAN;R_D_nonint_check(x);if (x < 0 || !R_FINITE(x)) return R_D__0;n = R_forceint(n);x = R_forceint(x);return dbinom_raw(x, n, p, 1-p, give_log);}