\section{eEF Class Reference}
\label{classeEF}\index{eEF@{eEF}}
General conjugate exponential family posterior density.  


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

Inheritance diagram for eEF:\nopagebreak
\begin{figure}[H]
\begin{center}
\leavevmode
\includegraphics[width=400pt]{classeEF__inherit__graph}
\end{center}
\end{figure}
Collaboration diagram for eEF:\nopagebreak
\begin{figure}[H]
\begin{center}
\leavevmode
\includegraphics[width=39pt]{classeEF__coll__graph}
\end{center}
\end{figure}
\subsection*{Public Member Functions}
\begin{CompactItemize}
\item 
{\bf eEF} (const {\bf RV} \&{\bf rv})\label{classeEF_7e3c63655e8375c76bf1f421245427a7}

\begin{CompactList}\small\item\em default constructor \item\end{CompactList}\item 
virtual double {\bf lognc} () const =0\label{classeEF_69e5680dac10375d62520d26c672477d}

\begin{CompactList}\small\item\em logarithm of the normalizing constant, $\mathcal{I}$ \item\end{CompactList}\item 
virtual void {\bf tupdate} (double phi, mat \&vbar, double nubar)\label{classeEF_fd88bc35550ec8fe9281d358216d0fcf}

\begin{CompactList}\small\item\em TODO decide if it is really needed. \item\end{CompactList}\item 
virtual void {\bf dupdate} (mat \&v, double nu=1.0)\label{classeEF_5863718c3b2fb1496dece10c5b745d5c}

\begin{CompactList}\small\item\em TODO decide if it is really needed. \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 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 
{\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}
General conjugate exponential family posterior density. 

More?... 

\subsection{Member Function Documentation}
\index{eEF@{eEF}!sample@{sample}}
\index{sample@{sample}!eEF@{eEF}}
\subsubsection{\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 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/mixpp/bdm/stat/{\bf libEF.h}\end{CompactItemize}