\section{eprod Class Reference}
\label{classeprod}\index{eprod@{eprod}}
Chain rule decomposition of \doxyref{epdf}{p.}{classepdf}.  


{\tt \#include $<$emix.h$>$}

Inheritance diagram for eprod:\nopagebreak
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Collaboration diagram for eprod:\nopagebreak
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\subsection*{Public Member Functions}
\begin{CompactItemize}
\item 
\textbf{eprod} (Array$<$ {\bf epdf} $>$ Facs)\label{classeprod_6c76cb1658c345cc30374c340608006c}

\item 
virtual vec {\bf sample} () const =0
\begin{CompactList}\small\item\em Returns the required moment of the \doxyref{epdf}{p.}{classepdf}. \item\end{CompactList}\item 
virtual mat {\bf sampleN} (int N) const \label{classepdf_54d7dd53a641b618771cd9bee135181f}

\begin{CompactList}\small\item\em Returns N samples from density $epdf(rv)$. \item\end{CompactList}\item 
virtual double {\bf eval} (const vec \&val) const \label{classepdf_3ea597362e11a0040fe7c990269d072c}

\begin{CompactList}\small\item\em Compute probability of argument {\tt val}. \item\end{CompactList}\item 
virtual double {\bf evalpdflog} (const vec \&val) const =0\label{classepdf_6aef3eca74899692503769c18add1a4c}

\begin{CompactList}\small\item\em Compute log-probability of argument {\tt val}. \item\end{CompactList}\item 
virtual vec {\bf mean} () const =0\label{classepdf_bf0a070a8f3e67a93604ca724638b870}

\begin{CompactList}\small\item\em return expected value \item\end{CompactList}\item 
{\bf RV} {\bf \_\-rv} () const \label{classepdf_b89143f12c9b49282e30841e4fb5f337}

\begin{CompactList}\small\item\em access function \item\end{CompactList}\end{CompactItemize}
\subsection*{Protected Attributes}
\begin{CompactItemize}
\item 
Array$<$ {\bf epdf} $\ast$ $>$ \textbf{epdfs}\label{classeprod_5307a27aaf48be8213294b05ac533c39}

\item 
Array$<$ {\bf mpdf} $\ast$ $>$ \textbf{mpdfs}\label{classeprod_a4387c81276ca66c1ca9336cf8bf74a8}

\item 
ivec \textbf{sizes}\label{classeprod_68b66b05b3b6987472247f541846a366}

\item 
{\bf RV} {\bf rv}\label{classepdf_74da992e3f5d598da8850b646b79b9d9}

\begin{CompactList}\small\item\em Identified of the random variable. \item\end{CompactList}\end{CompactItemize}


\subsection{Detailed Description}
Chain rule decomposition of \doxyref{epdf}{p.}{classepdf}. 

Probability density in the form of Chain-rule decomposition: $\backslash$[ f(x\_\-1,x\_\-2,x\_\-3) = f(x\_\-1$|$x\_\-2,x\_\-3)f(x\_\-2,x\_\-3)f(x\_\-3) $\backslash$] Note that 

\subsection{Member Function Documentation}
\index{eprod@{eprod}!sample@{sample}}
\index{sample@{sample}!eprod@{eprod}}
\subsubsection[sample]{\setlength{\rightskip}{0pt plus 5cm}virtual vec epdf::sample () const\hspace{0.3cm}{\tt  [pure virtual, inherited]}}\label{classepdf_8019654e494bf5e458f6fb947e11b262}


Returns the required moment of the \doxyref{epdf}{p.}{classepdf}. 

Returns a sample, $x$ from density $epdf(rv)$ 

Implemented in {\bf emix} \doxyref{}{p.}{classemix_0650601f24e633e0ab09aa1e46c14483}, {\bf enorm$<$ sq\_\-T $>$} \doxyref{}{p.}{classenorm_60b47544f6181ffd4530d3e415ce12c5}, {\bf egiw} \doxyref{}{p.}{classegiw_3d2c1f2ba0f9966781f1e0ae695e8a6f}, {\bf egamma} \doxyref{}{p.}{classegamma_8e10c0021b5dfdd9cb62c6959b5ef425}, {\bf euni} \doxyref{}{p.}{classeuni_4a0e09392be17beaee120ba98fc038cd}, {\bf eEmp} \doxyref{}{p.}{classeEmp_83f9283f92b805508d896479dc1ccf12}, {\bf enorm$<$ ldmat $>$} \doxyref{}{p.}{classenorm_60b47544f6181ffd4530d3e415ce12c5}, {\bf enorm$<$ chmat $>$} \doxyref{}{p.}{classenorm_60b47544f6181ffd4530d3e415ce12c5}, and {\bf enorm$<$ fsqmat $>$} \doxyref{}{p.}{classenorm_60b47544f6181ffd4530d3e415ce12c5}.

Referenced by mpdf::samplecond(), PF::set\_\-est(), and eEmp::set\_\-parameters().

The documentation for this class was generated from the following file:\begin{CompactItemize}
\item 
work/git/mixpp/bdm/stat/{\bf emix.h}\end{CompactItemize}