/* sample from truncated inverse chi squared truncated above at "max" */
double TruncInvChisq(int df, double scale, double max, int invcdf) {
double temp = 0, temp_pg, g_shape, g_scale;
double out;
int i;
g_shape = (double)df / 2;
g_scale = 2 / ((double)df * scale);
if (invcdf) {/* inverse cdf method */
temp = runif(0, 1);
temp_pg = pgamma(1 / max, g_shape, g_scale, 1, 0);
temp = (temp * ((double)1 - temp_pg)) + temp_pg;
out = qgamma(temp, g_shape, g_scale, 1, 0);
} else {/* rejection sampling method */
for (i = 0; i < 10000; i++) {
out = rgamma(g_shape, g_scale);
if (out > 1 / max ) break;
if (temp == 9999) {
/* error("Too many rejections. Try the inverse-CDF method"); */
/* If there are too many rejections, inverse-CDF method */
temp = runif(0, 1);
temp_pg = pgamma(1 / max, g_shape, g_scale, 1, 0);
temp = (temp * ((double)1 - temp_pg)) + temp_pg;
out = qgamma(temp, g_shape, g_scale, 1, 0);
}
}
}
return (1 / out);
}
Type objective_function<Type>::operator() ()
{
DATA_VECTOR(y);
PARAMETER(phi);
PARAMETER(shape);
PARAMETER(scale);
PARAMETER(sd);
PARAMETER_VECTOR(u);
Type res=0;
res += density::AR1(phi)(u);
vector<Type> unif = pnorm(u,Type(0),Type(1));
vector<Type> x = qgamma(unif,shape,scale);
res -= dnorm(y,x,sd,true).sum();
return res;
}
double qchisq(double p, double df, int lower_tail, int log_p)
{
return qgamma(p, 0.5 * df, 2.0, lower_tail, log_p);
}
void printpts( double r, int k1, int k2 ) {
double d1 = qgamma(C, (double)k1, 1/r, 1, 0);
double d2 = qgamma(C, (double)k2, 1/r, 1, 0);
double d = qgamma(C, (double)(k1+k2), 1/r, 1, 0);
printf("%.5f\t%.5f\t%.5f\n", d1, d2, d);
}
double qerlang( double area, int shape, double rate, int lower ) {
return qgamma(area, (double)shape, 1/rate, lower, 0);
}
