Having not much success with my previous question I try to reformulate it:
I'm simulating a Markow chain in Fortran interfaced with R.
Each loop of my Fortran calls various functions of the R RNG through
the wrapper given below.
In a run of 100 iterations of the Markov kernel,
after 20 iterations, the RNG seems like frozen.
For example, the first call to the RNG in my loop is:
rpostlamb = ggrgam(dble(m),1.d0)
write(*,*) 'rpostlamb=',rpostlamb
after the 20th iteration, it will return the same value
rpostlamb= 1.24634557
for all the following interations.
Is there any suggestion of explanation for this strange fact ?
Thanks in advance
Gilles
R Version 2.2.0 compiled under Mandrake 10.1
#include <R.h>
#include <Rmath.h>
/******************/
/* random numbers */
/******************/
void F77_SUB(rndstart)(void)
{ GetRNGstate(); }
void F77_SUB(rndend)(void)
{ PutRNGstate(); }
double F77_SUB(ggrnorm)(double *mu, double *sigma)
{ return rnorm(*mu, *sigma); }
double F77_SUB(ggrexp)(double *scale)
{return rexp(*scale);}
double F77_SUB(ggrgam)(double *a, double *scale)
{return rgamma(*a, *scale);}
double F77_SUB(ggrunif)(double *a, double *b)
{return runif(*a, *b);}
double F77_SUB(ggrbinom)(double *n, double *p)
{return rbinom(*n, *p);}
double F77_SUB(ggrpois)(double *lambda)
{return rpois(*lambda);}
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