/* * AUTHOR * Catherine Loader, catherine@research.bell-labs.com. * October 23, 2000 and Feb, 2001. * * dnbinom_mu(): Martin Maechler, June 2008 * * Merge in to R: * Copyright (C) 2000--2016, The R Core Team * * 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 * * Computes the negative binomial distribution. For integer n, * this is probability of x failures before the nth success in a * sequence of Bernoulli trials. We do not enforce integer n, since * the distribution is well defined for non-integers, * and this can be useful for e.g. overdispersed discrete survival times. */ #include "nmath.h" #include "dpq.h" double dnbinom(double x, double size, double prob, int give_log) { double ans, p; #ifdef IEEE_754 if (ISNAN(x) || ISNAN(size) || ISNAN(prob)) return x + size + prob; #endif if (prob <= 0 || prob > 1 || size < 0) ML_WARN_return_NAN; R_D_nonint_check(x); if (x < 0 || !R_FINITE(x)) return R_D__0; /* limiting case as size approaches zero is point mass at zero */ if (x == 0 && size==0) return R_D__1; x = R_forceint(x); if(!R_FINITE(size)) size = DBL_MAX; ans = dbinom_raw(size, x+size, prob, 1-prob, give_log); p = ((double)size)/(size+x); return((give_log) ? log(p) + ans : p * ans); } double dnbinom_mu(double x, double size, double mu, int give_log) { /* originally, just set prob := size / (size + mu) and called dbinom_raw(), * but that suffers from cancellation when mu << size */ #ifdef IEEE_754 if (ISNAN(x) || ISNAN(size) || ISNAN(mu)) return x + size + mu; #endif if (mu < 0 || size < 0) ML_WARN_return_NAN; R_D_nonint_check(x); if (x < 0 || !R_FINITE(x)) return R_D__0; /* limiting case as size approaches zero is point mass at zero, * even if mu is kept constant. limit distribution does not * have mean mu, though. */ if (x == 0 && size == 0) return R_D__1; x = R_forceint(x); if(!R_FINITE(size)) // limit case: Poisson return(dpois_raw(x, mu, give_log)); if(x == 0)/* be accurate, both for n << mu, and n >> mu :*/ return R_D_exp(size * (size < mu ? log(size/(size+mu)) : log1p(- mu/(size+mu)))); if(x < 1e-10 * size) { /* don't use dbinom_raw() but MM's formula: */ /* FIXME --- 1e-8 shows problem; rather use algdiv() from ./toms708.c */ double p = (size < mu ? log(size/(1 + size/mu)) : log(mu / (1 + mu/size))); return R_D_exp(x * p - mu - lgamma(x+1) + log1p(x*(x-1)/(2*size))); } else { /* no unnecessary cancellation inside dbinom_raw, when * x_ = size and n_ = x+size are so close that n_ - x_ loses accuracy */ double p = ((double)size)/(size+x), ans = dbinom_raw(size, x+size, size/(size+mu), mu/(size+mu), give_log); return((give_log) ? log(p) + ans : p * ans); } }