\section{epdf Class Reference}
\label{classepdf}\index{epdf@{epdf}}
Probability density function with numerical statistics, e.g. posterior density.  


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

Inheritance diagram for epdf:\nopagebreak
\begin{figure}[H]
\begin{center}
\leavevmode
\includegraphics[width=400pt]{classepdf__inherit__graph}
\end{center}
\end{figure}
Collaboration diagram for epdf:\nopagebreak
\begin{figure}[H]
\begin{center}
\leavevmode
\includegraphics[width=39pt]{classepdf__coll__graph}
\end{center}
\end{figure}
\subsection*{Public Member Functions}
\begin{CompactItemize}
\item 
{\bf epdf} ()\label{classepdf_d8eb760037b3bad5a0d64081606697cd}

\begin{CompactList}\small\item\em default constructor \item\end{CompactList}\item 
{\bf epdf} (const {\bf RV} \&rv0)\label{classepdf_c95b1a27a8dd9507bb9a5a3cb2809c7a}

\begin{CompactList}\small\item\em default constructor \item\end{CompactList}\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 
virtual {\bf $\sim$epdf} ()\label{classepdf_0a322dd106f04c0a2915e3d4f4227396}

\begin{CompactList}\small\item\em Destructor for future use;. \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 
{\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}
Probability density function with numerical statistics, e.g. posterior density. 

\subsection{Member Function Documentation}
\index{epdf@{epdf}!sample@{sample}}
\index{sample@{sample}!epdf@{epdf}}
\subsubsection[sample]{\setlength{\rightskip}{0pt plus 5cm}virtual vec epdf::sample () const\hspace{0.3cm}{\tt  [pure virtual]}}\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 files:\begin{CompactItemize}
\item 
work/git/mixpp/bdm/stat/{\bf libBM.h}\item 
work/git/mixpp/bdm/stat/libBM.cpp\end{CompactItemize}
