\section{enorm$<$ sq\_\-T $>$ Class Template Reference}
\label{classenorm}\index{enorm@{enorm}}
Gaussian density with positive definite (decomposed) covariance matrix.  


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

Inheritance diagram for enorm$<$ sq\_\-T $>$:\nopagebreak
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Collaboration diagram for enorm$<$ sq\_\-T $>$:\nopagebreak
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\subsection*{Public Member Functions}
\begin{CompactItemize}
\item 
{\bf enorm} ({\bf RV} \&{\bf rv})\label{classenorm_7b5cb487a2570e8109bfdc0df149aa06}

\begin{CompactList}\small\item\em Default constructor. \item\end{CompactList}\item 
void {\bf set\_\-parameters} (const vec \&{\bf mu}, const sq\_\-T \&{\bf R})\label{classenorm_1394a65caa6e00d42e00cc99b12227af}

\begin{CompactList}\small\item\em Set mean value {\tt mu} and covariance {\tt R}. \item\end{CompactList}\item 
void {\bf tupdate} (double phi, mat \&vbar, double nubar)\label{classenorm_5b5fd142b6b17ea334597960e3fe126a}

\begin{CompactList}\small\item\em tupdate in exponential form (not really handy) \item\end{CompactList}\item 
void {\bf dupdate} (mat \&v, double nu=1.0)\label{classenorm_5bf185e31e5954fceb90ada3debd2ff2}

\begin{CompactList}\small\item\em dupdate in exponential form (not really handy) \item\end{CompactList}\item 
vec {\bf sample} () const 
\begin{CompactList}\small\item\em Returns the required moment of the \doxyref{epdf}{p.}{classepdf}. \item\end{CompactList}\item 
mat {\bf sample} (int N) const \label{classenorm_60f0f3bfa53d6e65843eea9532b16d36}

\begin{CompactList}\small\item\em TODO is it used? \item\end{CompactList}\item 
double {\bf eval} (const vec \&val) const \label{classenorm_b9e1dfd33692d7b3f1a59f17b0e61bd0}

\begin{CompactList}\small\item\em Compute probability of argument {\tt val}. \item\end{CompactList}\item 
double {\bf evalpdflog} (const vec \&val) const \label{classenorm_609a7c33dbb4fdfab050f3bdd1122401}

\begin{CompactList}\small\item\em Compute log-probability of argument {\tt val}. \item\end{CompactList}\item 
double {\bf lognc} () const \label{classenorm_b289a36a69db59d182bb6eba9c05d4a8}

\begin{CompactList}\small\item\em logarithm of the normalizing constant, $\mathcal{I}$ \item\end{CompactList}\item 
vec {\bf mean} () const \label{classenorm_50fa84da7bae02f7af17a98f37566899}

\begin{CompactList}\small\item\em return expected value \item\end{CompactList}\item 
vec \& {\bf \_\-mu} ()\label{classenorm_0b8cb284e5af920a1b64a21d057ec5ac}

\begin{CompactList}\small\item\em returns a pointer to the internal mean value. Use with Care! \item\end{CompactList}\item 
void {\bf set\_\-mu} (const vec mu0)\label{classenorm_d892a38f03be12e572ea57d9689cef6b}

\begin{CompactList}\small\item\em access function \item\end{CompactList}\item 
sq\_\-T \& {\bf \_\-R} ()\label{classenorm_7a5034b25771a84450a990d10fc40ac9}

\begin{CompactList}\small\item\em returns pointers to the internal variance and its inverse. Use with Care! \item\end{CompactList}\item 
mat {\bf getR} ()\label{classenorm_9b9f58dc86affa23511c246887420658}

\begin{CompactList}\small\item\em access method \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 
{\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 
vec {\bf mu}\label{classenorm_71fde0d54bba147e00f612577f95ad20}

\begin{CompactList}\small\item\em mean value \item\end{CompactList}\item 
sq\_\-T {\bf R}\label{classenorm_4ccc8d8514d644ef1c98d8ab023748a1}

\begin{CompactList}\small\item\em Covariance matrix in decomposed form. \item\end{CompactList}\item 
int {\bf dim}\label{classenorm_6938fc390a19cdaf6ad4503fcbaada4e}

\begin{CompactList}\small\item\em dimension (redundant from rv.count() for easier coding ) \item\end{CompactList}\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}
\subsubsection*{template$<$class sq\_\-T$>$ class enorm$<$ sq\_\-T $>$}

Gaussian density with positive definite (decomposed) covariance matrix. 

More?... 

\subsection{Member Function Documentation}
\index{enorm@{enorm}!sample@{sample}}
\index{sample@{sample}!enorm@{enorm}}
\subsubsection[sample]{\setlength{\rightskip}{0pt plus 5cm}template$<$class sq\_\-T$>$ vec {\bf enorm}$<$ sq\_\-T $>$::sample () const\hspace{0.3cm}{\tt  [inline, virtual]}}\label{classenorm_60b47544f6181ffd4530d3e415ce12c5}


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

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

Implements {\bf epdf} \doxyref{}{p.}{classepdf_8019654e494bf5e458f6fb947e11b262}.

References enorm$<$ sq\_\-T $>$::dim, enorm$<$ sq\_\-T $>$::mu, and enorm$<$ sq\_\-T $>$::R.

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