void MMS::draw(){
Ptr<MvnSuf> s = mvn->suf();
double n = s->n();
const Spd &siginv(mvn->siginv());
const Spd &ominv(mu_prior_->siginv());
Spd Ivar = n*siginv + ominv;
Vec mu = Ivar.solve(n*(siginv*s->ybar()) + ominv*mu_prior_->mu());
mu = rmvn_ivar(mu, Ivar);
mvn->set_mu(mu);
}
void ArPosteriorSampler::draw_phi(){
const Spd &xtx(model_->suf()->xtx());
const Vec &xty(model_->suf()->xty());
Vec phi_hat = xtx.solve(xty);
bool ok = false;
int attempts = 0;
while (!ok && ++attempts <= max_number_of_regression_proposals_) {
Vec phi = rmvn_ivar(phi_hat, xtx / model_->sigsq());
ok = ArModel::check_stationary(phi);
if(ok) model_->set_phi(phi);
}
if(!ok){
draw_phi_univariate();
}
}
void BLSSS::draw_beta() {
Selector g = m_->coef().inc();
if(g.nvars() == 0) {
m_->drop_all();
return;
}
SpdMatrix ivar = g.select(pri_->siginv());
Vector ivar_mu = ivar * g.select(pri_->mu());
ivar += g.select(suf().xtx());
ivar_mu += g.select(suf().xty());
Vector b = ivar.solve(ivar_mu);
b = rmvn_ivar(b, ivar);
// If model selection is turned off and some elements of beta
// happen to be zero (because, e.g., of a failed MH step) we don't
// want the dimension of beta to change.
m_->set_included_coefficients(b, g);
}
