double GenericGaussianVarianceSampler::draw(
RNG &rng,
double data_df,
double data_ss) const {
double DF = data_df + 2 * prior_->alpha();
double SS = data_ss + 2 * prior_->beta();
if (sigma_max_ == 0.0) {
return 0.0;
} else if(sigma_max_ == infinity()){
return 1.0 / rgamma_mt(rng, DF/2, SS/2);
} else {
return 1.0 / rtrun_gamma_mt(rng, DF/2, SS/2, 1.0/square(sigma_max_));
}
}
// Draws sigma given phi and observed data.
void ArPosteriorSampler::draw_sigma(){
// ss = y - xb y - xb
// = yty - 2 bt xty + bt xtx b
const Vec &phi(model_->phi());
const Vec &xty(model_->suf()->xty());
const Spd &xtx(model_->suf()->xtx());
double ss = 2 * siginv_prior_->beta();
ss += xtx.Mdist(phi) - 2 * phi.dot(xty) + model_->suf()->yty();
double df = 2 * siginv_prior_->alpha();
df += model_->suf()->n();
double siginv;
if (upper_sigma_truncation_point_ == BOOM::infinity()) {
siginv = rgamma_mt(rng(), df/2, ss/2);
} else {
siginv = rtrun_gamma_mt(rng(), df/2, ss/2,
1.0/pow(upper_sigma_truncation_point_, 2));
}
model_->set_sigsq(1.0 / siginv);
}
