/*
* Mathlib : A C Library of Special Functions
* Copyright (C) 1998 Ross Ihaka
* Copyright (C) 2000-1 The R Development Core Team
* Copyright (C) 2004 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., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301
* USA.
*
* DESCRIPTION
*
* The density of the noncentral chi-squared distribution with "df"
* degrees of freedom and noncentrality parameter "lambda".
*/
#include "nmath.h"
#include "dpq.h"
double dnchisq(double x, double df, double lambda, int give_log)
{
const static double eps = 5e-15;
double i, lambda2, term, sum, q, mid, dfmid, imax, errorbound;
#ifdef IEEE_754
if (ISNAN(x) || ISNAN(df) || ISNAN(lambda))
return x + df + lambda;
#endif
if (lambda < 0 || df <= 0) ML_ERR_return_NAN;
if (!R_FINITE(df) || !R_FINITE(lambda))
ML_ERR_return_NAN;
if(x < 0) return R_D__0;
if(x == 0 && df < 2.)
return ML_POSINF;
if(lambda == 0)
return dchisq(x, df, give_log);
lambda2 = 0.5 * lambda;
/* find max element of sum */
imax = ceil((-(2+df) +sqrt((2-df) * (2-df) + 4 * lambda * x))/4);
if (imax < 0) imax = 0;
dfmid = df + 2 * imax;
mid = dpois_raw(imax, lambda2, FALSE) * dchisq(x, dfmid, FALSE);
sum = mid;
/* upper tail */
term = mid;
i = imax;
df = dfmid;
do {
i++;
q = x * lambda2 / i / df;
df += 2;
term = q * term;
sum += term;
errorbound = term * q / (1-q);
} while (errorbound > eps || q >= 1);
/* lower tail */
term = mid;
df = dfmid;
i = imax;
while ( i ){
df -= 2;
q = i * df / x / lambda2;
i--;
term = q * term;
sum += term;
errorbound = term * q / (1-q);
if (errorbound <= eps && q < 1) break;
}
return R_D_val(sum);
}
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