double WeightedMvnModel::pdf(Ptr<WeightedVectorData> dp, bool logscale)const{
double w = dp->weight();
const Vector &y(dp->value());
uint p = mu().size();
double wldsi = p*log(w) + ldsi();
return dmvn(y, mu(), w*siginv(), wldsi, logscale);
}
double MVTR::pdf(dPtr dp, bool logscale)const{
Ptr<DataType> d = DAT(dp);
const Vec &y(d->y());
const Vec &X(d->x());
double ans = dmvt(y, X*Beta(), Siginv(), nu(), ldsi(), true);
return logscale ? ans : exp(ans);
}
double ZMMM::loglike()const{
const double log2pi = 1.83787706641;
double dim = mu_.size();
double n = suf()->n();
const Vec ybar = suf()->ybar();
const Spd sumsq = suf()->center_sumsq();
double qform = n*(siginv().Mdist(ybar));
qform+= traceAB(siginv(), sumsq);
double nc = 0.5*n*( -dim*log2pi + ldsi());
double ans = nc - .5*qform;
return ans;
}
double MGSS::pdf(Ptr<Data> dp, bool logscale)const{
const Vec &y(DAT(dp)->value());
return dmvn(y, mu(), siginv(), ldsi(), logscale);
}
double MVT::pdf(const Vector &x, bool logscale) const {
return dmvt(x, mu(), siginv(), nu(), ldsi(), logscale);
}
double MvReg::pdf(const Ptr<Data> &dptr, bool logscale) const {
Ptr<MvRegData> dp = DAT(dptr);
Vector mu = predict(dp->x());
return dmvn(dp->y(), mu, Siginv(), ldsi(), logscale);
}
double ZMMM::pdf(Ptr<Data> dp, bool logscale)const{
Ptr<VectorData> dpp = DAT(dp);
return dmvn_zero_mean(dpp->value(), siginv(), ldsi(), logscale);
}
