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/** AUTHOR* Claus Ekstrøm, ekstrom@dina.kvl.dk* July 15, 2003.** Merge in to R:* Copyright (C) 2003 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, write to the Free Software* Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA.*** NOTE** Requires the following auxiliary routines:** lgammafn(x) - log gamma function* pnt(x, df, ncp) - the distribution function for* the non-central t distribution*** DESCRIPTION** The non-central t density is** f(x, df, ncp) =* df^(df/2) * exp(-.5*ncp^2) /* (sqrt(pi)*gamma(df/2)*(df+x^2)^((df+1)/2)) ** sum_{k=0}^Inf gamma((df + k + df)/2)*ncp^k /* prod(1:k)*(2*x^2/(df+x^2))^(k/2)** The functional relationship** f(x, df, ncp) = df/x ** (F(sqrt((df+2)/df)*x, df+2, ncp) - F(x, df, ncp))** is used to evaluate the density at x != 0 and** f(0, df, ncp) = exp(-.5*ncp^2) /* (sqrt(pi)*sqrt(df)*gamma(df/2))*gamma((df+1)/2)** is used for x=0.** All calculations are done on log-scale to increase stability.**/#include "nmath.h"#include "dpq.h"double dnt(double x, double df, double ncp, int give_log){double u;#ifdef IEEE_754if (ISNAN(x) || ISNAN(df))return x + df;#endif/* If non-positive df then error */if (df <= 0) ML_ERR_return_NAN;/* If x is infinite then return 0 */if(!R_FINITE(x))return R_D__0;/* If infinite df then the density is identical to a *//* normal distribution with mean = ncp */if(!R_FINITE(df))return dnorm(x, ncp, 1., give_log);/* Consider two cases: x==0 or not *//* Do calculations on log scale to stabilize */if (x != 0) {u = log(df) - log(fabs(x)) +log(fabs(pnt(x*sqrt((df+2)/df), df+2, ncp, 1, 0) -pnt(x, df, ncp, 1, 0)));}else {u = lgammafn((df+1)/2) - lgammafn(df/2)- .5*(log(M_PI) + log(df) + ncp*ncp);}return (give_log ? u : exp(u));}