\hypertarget{classenorm}{
\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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\begin{center}
\leavevmode
\includegraphics[width=171pt]{classenorm__inherit__graph}
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Collaboration diagram for enorm$<$ sq\_\-T $>$:\nopagebreak
\begin{figure}[H]
\begin{center}
\leavevmode
\includegraphics[width=69pt]{classenorm__coll__graph}
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\subsection*{Public Member Functions}
\begin{CompactItemize}
\item 
\hypertarget{classenorm_0caf54fed9e48f9fe28b534b2027df2f}{
\hyperlink{classenorm_0caf54fed9e48f9fe28b534b2027df2f}{enorm} (const \hyperlink{classRV}{RV} \&\hyperlink{classepdf_74da992e3f5d598da8850b646b79b9d9}{rv})}
\label{classenorm_0caf54fed9e48f9fe28b534b2027df2f}

\begin{CompactList}\small\item\em Default constructor. \item\end{CompactList}\item 
\hypertarget{classenorm_1394a65caa6e00d42e00cc99b12227af}{
void \hyperlink{classenorm_1394a65caa6e00d42e00cc99b12227af}{set\_\-parameters} (const vec \&\hyperlink{classenorm_71fde0d54bba147e00f612577f95ad20}{mu}, const sq\_\-T \&\hyperlink{classenorm_4ccc8d8514d644ef1c98d8ab023748a1}{R})}
\label{classenorm_1394a65caa6e00d42e00cc99b12227af}

\begin{CompactList}\small\item\em Set mean value {\tt mu} and covariance {\tt R}. \item\end{CompactList}\item 
\hypertarget{classenorm_5bf185e31e5954fceb90ada3debd2ff2}{
void \hyperlink{classenorm_5bf185e31e5954fceb90ada3debd2ff2}{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 
\hypertarget{classenorm_60b47544f6181ffd4530d3e415ce12c5}{
vec \hyperlink{classenorm_60b47544f6181ffd4530d3e415ce12c5}{sample} () const }
\label{classenorm_60b47544f6181ffd4530d3e415ce12c5}

\begin{CompactList}\small\item\em Returns a sample, $x$ from density $epdf(rv)$. \item\end{CompactList}\item 
\hypertarget{classenorm_60f0f3bfa53d6e65843eea9532b16d36}{
mat \hyperlink{classenorm_60f0f3bfa53d6e65843eea9532b16d36}{sample} (int N) const }
\label{classenorm_60f0f3bfa53d6e65843eea9532b16d36}

\begin{CompactList}\small\item\em TODO is it used? \item\end{CompactList}\item 
\hypertarget{classenorm_50cb0a083d97a7adbbd97c92e712c46c}{
double \hyperlink{classenorm_50cb0a083d97a7adbbd97c92e712c46c}{evallog\_\-nn} (const vec \&val) const }
\label{classenorm_50cb0a083d97a7adbbd97c92e712c46c}

\begin{CompactList}\small\item\em Evaluate normalized log-probability. \item\end{CompactList}\item 
\hypertarget{classenorm_b289a36a69db59d182bb6eba9c05d4a8}{
double \hyperlink{classenorm_b289a36a69db59d182bb6eba9c05d4a8}{lognc} () const }
\label{classenorm_b289a36a69db59d182bb6eba9c05d4a8}

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

\begin{CompactList}\small\item\em return expected value \item\end{CompactList}\item 
\hypertarget{classenorm_921024bd6d5a0e65f2af2e39bf38dfca}{
\hyperlink{classmpdf}{mpdf} $\ast$ \hyperlink{classenorm_921024bd6d5a0e65f2af2e39bf38dfca}{condition} (const \hyperlink{classRV}{RV} \&rvn) const }
\label{classenorm_921024bd6d5a0e65f2af2e39bf38dfca}

\begin{CompactList}\small\item\em Return conditional density on the given \hyperlink{classRV}{RV}, the remaining rvs will be in conditioning. \item\end{CompactList}\item 
\hypertarget{classenorm_af50a6102846060bcb23a670bf38117b}{
\hyperlink{classepdf}{epdf} $\ast$ \hyperlink{classenorm_af50a6102846060bcb23a670bf38117b}{marginal} (const \hyperlink{classRV}{RV} \&\hyperlink{classepdf_74da992e3f5d598da8850b646b79b9d9}{rv}) const }
\label{classenorm_af50a6102846060bcb23a670bf38117b}

\begin{CompactList}\small\item\em Return marginal density on the given \hyperlink{classRV}{RV}, the remainig rvs are intergrated out. \item\end{CompactList}\item 
\hypertarget{classenorm_0b8cb284e5af920a1b64a21d057ec5ac}{
vec \& \hyperlink{classenorm_0b8cb284e5af920a1b64a21d057ec5ac}{\_\-mu} ()}
\label{classenorm_0b8cb284e5af920a1b64a21d057ec5ac}

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

\begin{CompactList}\small\item\em access function \item\end{CompactList}\item 
\hypertarget{classenorm_7a5034b25771a84450a990d10fc40ac9}{
sq\_\-T \& \hyperlink{classenorm_7a5034b25771a84450a990d10fc40ac9}{\_\-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 
\hypertarget{classenorm_d01385983048ece700b426549bbaee56}{
const sq\_\-T \& \textbf{\_\-R} () const }
\label{classenorm_d01385983048ece700b426549bbaee56}

\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_357512dd565e199904d367294b7dd862}{
virtual double \hyperlink{classeEF_357512dd565e199904d367294b7dd862}{evallog} (const vec \&val) const }
\label{classeEF_357512dd565e199904d367294b7dd862}

\begin{CompactList}\small\item\em Evaluate normalized log-probability. \item\end{CompactList}\item 
\hypertarget{classeEF_cff03a658aec11b806c3e3d48f37b81f}{
virtual vec \hyperlink{classeEF_cff03a658aec11b806c3e3d48f37b81f}{evallog} (const mat \&Val) const }
\label{classeEF_cff03a658aec11b806c3e3d48f37b81f}

\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_76608914c3b19e150292d5c56e93e508}{
virtual mat \hyperlink{classepdf_76608914c3b19e150292d5c56e93e508}{sample\_\-m} (int N) const }
\label{classepdf_76608914c3b19e150292d5c56e93e508}

\begin{CompactList}\small\item\em Returns N samples from density $epdf(rv)$. \item\end{CompactList}\item 
\hypertarget{classepdf_2495a04bbacb9b55fe5a3a59b78affca}{
virtual vec \hyperlink{classepdf_2495a04bbacb9b55fe5a3a59b78affca}{evallog\_\-m} (const mat \&Val) const }
\label{classepdf_2495a04bbacb9b55fe5a3a59b78affca}

\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{classenorm_71fde0d54bba147e00f612577f95ad20}{
vec \hyperlink{classenorm_71fde0d54bba147e00f612577f95ad20}{mu}}
\label{classenorm_71fde0d54bba147e00f612577f95ad20}

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

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

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

Gaussian density with positive definite (decomposed) covariance matrix. 

More?... 

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}
