\section{mEF Class Reference} \label{classmEF}\index{mEF@{mEF}} Exponential family model. {\tt \#include $<$libEF.h$>$} Inheritance diagram for mEF:\nopagebreak \begin{figure}[H] \begin{center} \leavevmode \includegraphics[width=107pt]{classmEF__inherit__graph} \end{center} \end{figure} Collaboration diagram for mEF:\nopagebreak \begin{figure}[H] \begin{center} \leavevmode \includegraphics[width=56pt]{classmEF__coll__graph} \end{center} \end{figure} \subsection*{Public Member Functions} \begin{CompactItemize} \item {\bf mEF} (const {\bf RV} \&rv0, const {\bf RV} \&rvc0)\label{classmEF_8bf51fe8654d7b83c8c8afeb19409d4f} \begin{CompactList}\small\item\em Default constructor. \item\end{CompactList}\item virtual vec {\bf samplecond} (vec \&cond, double \&ll) \begin{CompactList}\small\item\em Returns the required moment of the \doxyref{epdf}{p.}{classepdf}. \item\end{CompactList}\item virtual mat {\bf samplecond} (vec \&cond, vec \&ll, int N) \begin{CompactList}\small\item\em Returns N samples from the density conditioned on {\tt cond}, $x \sim epdf(rv|cond)$. \item\end{CompactList}\item virtual void {\bf condition} (const vec \&cond)\label{classmpdf_0f95a0cc6ab40611f46804682446ed83} \begin{CompactList}\small\item\em Update {\tt ep} so that it represents this \doxyref{mpdf}{p.}{classmpdf} conditioned on {\tt rvc} = cond. \item\end{CompactList}\item virtual double {\bf evalcond} (const vec \&dt, const vec \&cond)\label{classmpdf_80b738ece5bd4f8c4edaee4b38906f91} \begin{CompactList}\small\item\em Shortcut for conditioning and evaluation of the internal \doxyref{epdf}{p.}{classepdf}. In some cases, this operation can be implemented efficiently. \item\end{CompactList}\item {\bf RV} {\bf \_\-rvc} ()\label{classmpdf_ec9c850305984582548e8deb64f0ffe8} \begin{CompactList}\small\item\em access function \item\end{CompactList}\item {\bf epdf} \& {\bf \_\-epdf} ()\label{classmpdf_e17780ee5b2cfe05922a6c56af1462f8} \begin{CompactList}\small\item\em access function \item\end{CompactList}\end{CompactItemize} \subsection*{Protected Attributes} \begin{CompactItemize} \item {\bf RV} {\bf rv}\label{classmpdf_f6687c07ff07d47812dd565368ca59eb} \begin{CompactList}\small\item\em modeled random variable \item\end{CompactList}\item {\bf RV} {\bf rvc}\label{classmpdf_acb7dda792b3cd5576f39fa3129abbab} \begin{CompactList}\small\item\em random variable in condition \item\end{CompactList}\item {\bf epdf} $\ast$ {\bf ep}\label{classmpdf_7aa894208a32f3487827df6d5054424c} \begin{CompactList}\small\item\em pointer to internal \doxyref{epdf}{p.}{classepdf} \item\end{CompactList}\end{CompactItemize} \subsection{Detailed Description} Exponential family model. More?... \subsection{Member Function Documentation} \index{mEF@{mEF}!samplecond@{samplecond}} \index{samplecond@{samplecond}!mEF@{mEF}} \subsubsection[samplecond]{\setlength{\rightskip}{0pt plus 5cm}virtual vec mpdf::samplecond (vec \& {\em cond}, \/ double \& {\em ll})\hspace{0.3cm}{\tt [inline, virtual, inherited]}}\label{classmpdf_b0193a350c97933ddf15b15a130da352} Returns the required moment of the \doxyref{epdf}{p.}{classepdf}. Returns a sample from the density conditioned on {\tt cond}, $x \sim epdf(rv|cond)$. \begin{Desc} \item[Parameters:] \begin{description} \item[{\em cond}]is numeric value of {\tt rv} \item[{\em ll}]is a return value of log-likelihood of the sample. \end{description} \end{Desc} Reimplemented in {\bf mlnorm$<$ sq\_\-T $>$} \doxyref{}{p.}{classmlnorm_decf3e3b5c8e0812e5b4dbe94fa2ae18}, and {\bf mgamma} \doxyref{}{p.}{classmgamma_9f40dc43885085fad8e3d6652b79e139}. References mpdf::condition(), mpdf::ep, epdf::evalpdflog(), and epdf::sample(). Referenced by MPF$<$ BM\_\-T $>$::bayes(), and PF::bayes().\index{mEF@{mEF}!samplecond@{samplecond}} \index{samplecond@{samplecond}!mEF@{mEF}} \subsubsection[samplecond]{\setlength{\rightskip}{0pt plus 5cm}virtual mat mpdf::samplecond (vec \& {\em cond}, \/ vec \& {\em ll}, \/ int {\em N})\hspace{0.3cm}{\tt [inline, virtual, inherited]}}\label{classmpdf_6bf806badfdac606c847e458e8fce18c} Returns N samples from the density conditioned on {\tt cond}, $x \sim epdf(rv|cond)$. \begin{Desc} \item[Parameters:] \begin{description} \item[{\em cond}]is numeric value of {\tt rv} \item[{\em ll}]is a return value of log-likelihood of the sample. \end{description} \end{Desc} Reimplemented in {\bf mlnorm$<$ sq\_\-T $>$} \doxyref{}{p.}{classmlnorm_215fb88cc8b95d64cdefd6849abdd1e8}, and {\bf mgamma} \doxyref{}{p.}{classmgamma_e9d52749793f40aad85b70c6db4435ae}. References mpdf::condition(), RV::count(), mpdf::ep, epdf::evalpdflog(), mpdf::rv, and epdf::sample(). The documentation for this class was generated from the following file:\begin{CompactItemize} \item work/mixpp/bdm/stat/{\bf libEF.h}\end{CompactItemize}