##### https://github.com/cran/nacopula
Revision 161411bb86f97e5a8bd89091cd61d03a33c2761a authored by Martin Maechler on 06 February 2012, 00:00 UTC, committed by Gabor Csardi on 06 February 2012, 00:00 UTC
1 parent 5bc804b
Tip revision: 161411b
rLog.c
``````/*
Copyright (C) 2010 Marius Hofert and Martin Maechler

This program is free software; you can redistribute it and/or modify it under
Foundation; either version 3 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, see <http://www.gnu.org/licenses/>.
*/

#include <Rmath.h>

#include "nacopula.h"

/**
* Sample a Log(p) distribution with the algorithm "LK" of Kemp (1981).
* Note: The caller of this function must use GetRNGstate() and PutRNGstate().
* @param p in (0,1)
* @param Ip = 1 - p_ (possibly more accurate)
* @return a random variate from Log(p)
* @author Marius Hofert, Martin Maechler
*/
double rLog(double p, double Ip) {
if(p <= 0. ||  p > 1.) {
error("rLog(): p must be inside (0,1)");
return -1.; /**< -Wall */
}
else if(Ip <= 0. || Ip >= 1.) {
error("rLog(): Ip must be inside (0,1)");
return -1.; /**< -Wall */
}
else {
double U=unif_rand();
if(U > p) {
return 1.;
}
else {
double Q, logQ;
if(p <= 0.5) {
Q = - expm1(log1p(- p) * unif_rand()); /* = 1-(1-p)^unif */
/**
* == 1. - exp(log1p(- p) * unif_rand())
* == 1. - pow(1. - p, unif_rand())
*/
logQ = log(Q);
} else { // p > 0.5  <==> Ip < 0.5
double iQ = pow(Ip, unif_rand()); /* = (1-p)^unif */
Q = 1. - iQ;
logQ = log1p(-iQ);
}
return(U < Q*Q
? floor(1. + log(U)/logQ)
: ((U > Q) ? 1. : 2.));
}
}
}

/**
* Generate a vector of variates from a Log(p) distribution with the algorithm
* "LK" of Kemp (1981).
* @param n_ sample size
* @param p_ parameter p in (0,1)
* @param Ip_ = 1 - p_ (possibly more accurate)
* @return vector of random variates from Log(p)
* @author Martin Maechler
*/
SEXP rLog_vec_c(SEXP n_, SEXP p_, SEXP Ip_) {
int n = asInteger(n_);
double p = asReal(p_),Ip = asReal(Ip_);
SEXP res = PROTECT(allocVector(REALSXP, n));
double* X = REAL(res);

GetRNGstate();

for(int i=0; i < n; i++)
X[i] = rLog(p, Ip);

PutRNGstate();
UNPROTECT(1);
return res;
}
`````` Computing file changes ...