eprod epdf emix.h Array< epdf * > Array<epdf*> eprod::epdfs epdfs Array< mpdf * > Array<mpdf*> eprod::mpdfs mpdfs ivec ivec eprod::sizes sizes RV RV epdf::rv rv Identified of the random variable. epdf::_rv egamma::evalpdflog egiw::evalpdflog egamma::lognc eEmp::mean emix::mean euni::sample egamma::sample epdf::sampleN emix::set_parameters eprod::eprod (Array< epdf > Facs) eprod Array< epdf > Facs vec virtual vec epdf::sample () const =0 sample sample sample sample sample sample sample sample sample sample Returns the required moment of the epdf. Returns a sample, $x$ from density $epdf(rv)$ mpdf::samplecond PF::set_est eEmp::set_parameters mat mat epdf::sampleN (int N) const sampleN int N Returns N samples from density $epdf(rv)$. RV::count epdf::rv double virtual double epdf::eval (const vec &val) const eval eval eval eval eval eval const vec & val Compute probability of argument val. epdf::evalpdflog mpdf::evalcond double virtual double epdf::evalpdflog (const vec &val) const =0 evalpdflog evalpdflog evalpdflog evalpdflog evalpdflog evalpdflog evalpdflog evalpdflog evalpdflog evalpdflog const vec & val Compute log-probability of argument val. epdf::eval mpdf::samplecond vec virtual vec epdf::mean () const =0 mean mean mean mean mean mean mean mean mean mean return expected value main RV RV epdf::_rv () const _rv access function epdf::rv emix::set_parameters 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 epdf eprod epdf rv RV eprod eprod_rv eprodepdf eprodepdf eprodepdfs eprodeprod eprodeval eprodevalpdflog eprodmean eprodmpdfs eprodrv eprodsample eprodsampleN eprodsizes eprod~epdf