\hypertarget{classeDirich}{
\section{eDirich Class Reference}
\label{classeDirich}\index{eDirich@{eDirich}}
}
Dirichlet posterior density.  


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

Inheritance diagram for eDirich:\nopagebreak
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Collaboration diagram for eDirich:\nopagebreak
\begin{figure}[H]
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\subsection*{Public Member Functions}
\begin{CompactItemize}
\item 
\hypertarget{classeDirich_ac7e6116f3575c3860d07355e96cd4af}{
\hyperlink{classeDirich_ac7e6116f3575c3860d07355e96cd4af}{eDirich} (const \hyperlink{classRV}{RV} \&\hyperlink{classepdf_74da992e3f5d598da8850b646b79b9d9}{rv}, const vec \&beta0)}
\label{classeDirich_ac7e6116f3575c3860d07355e96cd4af}

\begin{CompactList}\small\item\em Default constructor. \item\end{CompactList}\item 
\hypertarget{classeDirich_55cccbc5eb44764dce722567acf5fd58}{
\hyperlink{classeDirich_55cccbc5eb44764dce722567acf5fd58}{eDirich} (const \hyperlink{classeDirich}{eDirich} \&D0)}
\label{classeDirich_55cccbc5eb44764dce722567acf5fd58}

\begin{CompactList}\small\item\em Copy constructor. \item\end{CompactList}\item 
\hypertarget{classeDirich_23dff79110822e9639343fe8e177fd80}{
vec \hyperlink{classeDirich_23dff79110822e9639343fe8e177fd80}{sample} () const }
\label{classeDirich_23dff79110822e9639343fe8e177fd80}

\begin{CompactList}\small\item\em Returns a sample, $x$ from density $epdf(rv)$. \item\end{CompactList}\item 
\hypertarget{classeDirich_4206e1da149d51ff3b663c9241096b73}{
vec \hyperlink{classeDirich_4206e1da149d51ff3b663c9241096b73}{mean} () const }
\label{classeDirich_4206e1da149d51ff3b663c9241096b73}

\begin{CompactList}\small\item\em return expected value \item\end{CompactList}\item 
\hypertarget{classeDirich_688a24f04be6d80d4769cf0e4ded7acc}{
double \hyperlink{classeDirich_688a24f04be6d80d4769cf0e4ded7acc}{evalpdflog\_\-nn} (const vec \&val) const }
\label{classeDirich_688a24f04be6d80d4769cf0e4ded7acc}

\begin{CompactList}\small\item\em In this instance, val is ... \item\end{CompactList}\item 
\hypertarget{classeDirich_7ce60be7119ffc639ede4e583c1f6e77}{
double \hyperlink{classeDirich_7ce60be7119ffc639ede4e583c1f6e77}{lognc} () const }
\label{classeDirich_7ce60be7119ffc639ede4e583c1f6e77}

\begin{CompactList}\small\item\em logarithm of the normalizing constant, $\mathcal{I}$ \item\end{CompactList}\item 
\hypertarget{classeDirich_6409d0362143a23976b43641ff19e53a}{
vec \& \hyperlink{classeDirich_6409d0362143a23976b43641ff19e53a}{\_\-beta} ()}
\label{classeDirich_6409d0362143a23976b43641ff19e53a}

\begin{CompactList}\small\item\em access function \item\end{CompactList}\item 
\hypertarget{classeDirich_c842acb2e1cce5cc9000769ff06c086d}{
void \hyperlink{classeDirich_c842acb2e1cce5cc9000769ff06c086d}{set\_\-parameters} (const vec \&beta0)}
\label{classeDirich_c842acb2e1cce5cc9000769ff06c086d}

\begin{CompactList}\small\item\em Set internal parameters. \item\end{CompactList}\item 
\hypertarget{classeEF_a89bef8996410609004fa019b5b48964}{
virtual void \hyperlink{classeEF_a89bef8996410609004fa019b5b48964}{dupdate} (mat \&v)}
\label{classeEF_a89bef8996410609004fa019b5b48964}

\begin{CompactList}\small\item\em TODO decide if it is really needed. \item\end{CompactList}\item 
\hypertarget{classeEF_6466e8d4aa9dd64698ed288cbb1afc03}{
virtual double \hyperlink{classeEF_6466e8d4aa9dd64698ed288cbb1afc03}{evalpdflog} (const vec \&val) const }
\label{classeEF_6466e8d4aa9dd64698ed288cbb1afc03}

\begin{CompactList}\small\item\em Evaluate normalized log-probability. \item\end{CompactList}\item 
\hypertarget{classeEF_c71faf4b2d153efda14bf1f87dca1507}{
virtual vec \hyperlink{classeEF_c71faf4b2d153efda14bf1f87dca1507}{evalpdflog} (const mat \&Val) const }
\label{classeEF_c71faf4b2d153efda14bf1f87dca1507}

\begin{CompactList}\small\item\em Evaluate normalized log-probability for many samples. \item\end{CompactList}\item 
\hypertarget{classeEF_4f8385dd1cc9740522dc373b1dc3cbf5}{
virtual void \hyperlink{classeEF_4f8385dd1cc9740522dc373b1dc3cbf5}{pow} (double p)}
\label{classeEF_4f8385dd1cc9740522dc373b1dc3cbf5}

\begin{CompactList}\small\item\em Power of the density, used e.g. to flatten the density. \item\end{CompactList}\item 
\hypertarget{classepdf_54d7dd53a641b618771cd9bee135181f}{
virtual mat \hyperlink{classepdf_54d7dd53a641b618771cd9bee135181f}{sampleN} (int N) const }
\label{classepdf_54d7dd53a641b618771cd9bee135181f}

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

\begin{CompactList}\small\item\em Compute probability of argument {\tt val}. \item\end{CompactList}\item 
\hypertarget{classepdf_cebbdd7a85e6328f7358fc0ba8eee06c}{
virtual vec \hyperlink{classepdf_cebbdd7a85e6328f7358fc0ba8eee06c}{evalpdflog\_\-m} (const mat \&Val) const }
\label{classepdf_cebbdd7a85e6328f7358fc0ba8eee06c}

\begin{CompactList}\small\item\em Compute log-probability of multiple values argument {\tt val}. \item\end{CompactList}\item 
\hypertarget{classepdf_ca0d32aabb4cbba347e0c37fe8607562}{
const \hyperlink{classRV}{RV} \& \hyperlink{classepdf_ca0d32aabb4cbba347e0c37fe8607562}{\_\-rv} () const }
\label{classepdf_ca0d32aabb4cbba347e0c37fe8607562}

\begin{CompactList}\small\item\em access function, possibly dangerous! \item\end{CompactList}\item 
\hypertarget{classepdf_7fb94ce90d1ac7077d29f7d6a6c3e0a5}{
void \hyperlink{classepdf_7fb94ce90d1ac7077d29f7d6a6c3e0a5}{\_\-renewrv} (const \hyperlink{classRV}{RV} \&in\_\-rv)}
\label{classepdf_7fb94ce90d1ac7077d29f7d6a6c3e0a5}

\begin{CompactList}\small\item\em modifier function - useful when copying epdfs \item\end{CompactList}\end{CompactItemize}
\subsection*{Protected Attributes}
\begin{CompactItemize}
\item 
\hypertarget{classeDirich_15e6b65e9595eedc8a1286c6cecd36d7}{
vec \hyperlink{classeDirich_15e6b65e9595eedc8a1286c6cecd36d7}{beta}}
\label{classeDirich_15e6b65e9595eedc8a1286c6cecd36d7}

\begin{CompactList}\small\item\em sufficient statistics \item\end{CompactList}\item 
\hypertarget{classepdf_74da992e3f5d598da8850b646b79b9d9}{
\hyperlink{classRV}{RV} \hyperlink{classepdf_74da992e3f5d598da8850b646b79b9d9}{rv}}
\label{classepdf_74da992e3f5d598da8850b646b79b9d9}

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


\subsection{Detailed Description}
Dirichlet posterior density. 

Continuous Dirichlet density of $n$-dimensional variable $x$ \[ f(x|\beta) = \frac{\Gamma[\gamma]}{\prod_{i=1}^{n}\Gamma(\beta_i)} \prod_{i=1}^{n}x_i^{\beta_i-1} \] where $\gamma=\sum_i \beta_i$. 

The documentation for this class was generated from the following file:\begin{CompactItemize}
\item 
work/git/mixpp/bdm/stat/\hyperlink{libEF_8h}{libEF.h}\end{CompactItemize}
