mprod mpdf emix.h int int mprod::n n Array< epdf * > Array<epdf*> mprod::epdfs epdfs Array< mpdf * > Array<mpdf*> mprod::mpdfs mpdfs Array< ivec > Array<ivec> mprod::rvinds rvinds Indeces of rvs in common rv. mprod Array< ivec > Array<ivec> mprod::rvcinrv rvcinrv Indeces of rvc in common rv. mprod Array< ivec > Array<ivec> mprod::rvcinds rvcinds Indeces of rvc in common rvc. mprod bool bool mprod::independent independent Indicate independence of its factors. mprod RV RV mpdf::rv rv modeled random variable mpdf::_rv mprod mlnorm< sq_T >::samplecond mpdf::samplecond mlnorm< sq_T >::set_parameters mgamma::set_parameters RV RV mpdf::rvc rvc random variable in condition mpdf::_rvc mprod epdf * epdf* mpdf::ep ep pointer to internal epdf mpdf::_epdf mpdf::evalcond mepdf::mepdf mlnorm< sq_T >::mlnorm mmix::mmix mpdf::samplecond mgamma::set_parameters mprod::mprod (Array< mpdf * > mFacs) mprod Array< mpdf * > mFacs Constructor from list of eFacs or list of mFacs. mpdf::_rv RV::add independent mpdf::rv mpdf::rvc rvcinds rvcinrv rvinds double double mprod::evalpdflog (const vec &val) const evalpdflog const vec & val vec vec mprod::samplecond (const vec &cond, vec &ll) const samplecond const vec & cond vec & ll mprod::~mprod () ~mprod vec virtual vec mpdf::samplecond (const vec &cond, double &ll) samplecond const vec & cond double & ll Returns the required moment of the epdf. Returns a sample from the density conditioned on cond, $x \sim epdf(rv|cond)$. cond is numeric value of rv ll is a return value of log-likelihood of the sample. mpdf::condition mpdf::ep epdf::evalpdflog epdf::sample MPF< BM_T >::bayes PF::bayes mat virtual mat mpdf::samplecond (const vec &cond, vec &ll, int N) samplecond const vec & cond vec & ll int N Returns. N samples from the density conditioned on cond, $x \sim epdf(rv|cond)$. cond is numeric value of rv ll is a return value of log-likelihood of the sample. mpdf::condition RV::count mpdf::ep epdf::evalpdflog mpdf::rv epdf::sample void virtual void mpdf::condition (const vec &cond) condition condition condition condition const vec & cond Update ep so that it represents this mpdf conditioned on rvc = cond. mpdf::evalcond mpdf::samplecond double virtual double mpdf::evalcond (const vec &dt, const vec &cond) evalcond const vec & dt const vec & cond Shortcut for conditioning and evaluation of the internal epdf. In some cases, this operation can be implemented efficiently. mpdf::condition mpdf::ep epdf::eval PF::bayes RV RV mpdf::_rvc () _rvc access function mpdf::rvc merger::merger RV RV mpdf::_rv () _rv access function mpdf::rv mprod epdf & epdf& mpdf::_epdf () _epdf access function mpdf::ep Chain rule decomposition of epdf. Probability density in the form of Chain-rule decomposition: \[ f(x_1,x_2,x_3) = f(x_1|x_2,x_3)f(x_2,x_3)f(x_3) \] Note that mprod mpdf epdf rv mprod RV mpdf rv rvc ep mprod_epdf mprod_rv mprod_rvc mprodcondition mprodep mprodepdfs mprodevalcond mprodevalpdflog mprodindependent mprodmpdf mprodmpdfs mprodmprod mprodn mprodrv mprodrvc mprodrvcinds mprodrvcinrv mprodrvinds mprodsamplecond mprodsamplecond mprodsamplecond mprod~mpdf mprod~mprod