Index: doc/latex/classbdm_1_1egiw.tex
===================================================================
--- doc/latex/classbdm_1_1egiw.tex (revision 261)
+++ doc/latex/classbdm_1_1egiw.tex (revision 270)
@@ -3,7 +3,4 @@
 \label{classbdm_1_1egiw}\index{bdm::egiw@{bdm::egiw}}
 }
-Gauss-inverse-Wishart density stored in LD form.  
-
-
 {\tt \#include $<$libEF.h$>$}
 
@@ -15,29 +12,17 @@
 \end{center}
 \end{figure}
-Collaboration diagram for bdm::egiw:\nopagebreak
-\begin{figure}[H]
-\begin{center}
-\leavevmode
-\includegraphics[width=89pt]{classbdm_1_1egiw__coll__graph}
-\end{center}
-\end{figure}
-\subsection*{Public Member Functions}
-\begin{CompactItemize}
-\item 
-\hypertarget{classbdm_1_1egiw_a60e072c191acf65ab480deeb11c5b88}{
-\hyperlink{classbdm_1_1egiw_a60e072c191acf65ab480deeb11c5b88}{egiw} (\hyperlink{classbdm_1_1RV}{RV} \hyperlink{classbdm_1_1epdf_62c5b8ff71d9ebe6cd58d3c342eb1dc8}{rv}, mat V0, double nu0=-1.0)}
-\label{classbdm_1_1egiw_a60e072c191acf65ab480deeb11c5b88}
-
-\begin{CompactList}\small\item\em Default constructor, if nu0$<$0 a minimal nu0 will be computed. \item\end{CompactList}\item 
-\hypertarget{classbdm_1_1egiw_bc3db93cb60dd29187eb3c6cfd557f97}{
-\hyperlink{classbdm_1_1egiw_bc3db93cb60dd29187eb3c6cfd557f97}{egiw} (\hyperlink{classbdm_1_1RV}{RV} \hyperlink{classbdm_1_1epdf_62c5b8ff71d9ebe6cd58d3c342eb1dc8}{rv}, \hyperlink{classldmat}{ldmat} V0, double nu0=-1.0)}
-\label{classbdm_1_1egiw_bc3db93cb60dd29187eb3c6cfd557f97}
-
-\begin{CompactList}\small\item\em Full constructor for V in \hyperlink{classldmat}{ldmat} form. \item\end{CompactList}\item 
+
+
+\subsection{Detailed Description}
+Gauss-inverse-Wishart density stored in LD form. 
+
+For $p$-variate densities, given rv.count() should be $p\times$ V.rows(). \subsection*{Public Member Functions}
+\begin{CompactItemize}
+\item 
 \hypertarget{classbdm_1_1egiw_920f21548b7a3723923dd108fe514c61}{
 vec \hyperlink{classbdm_1_1egiw_920f21548b7a3723923dd108fe514c61}{sample} () const }
 \label{classbdm_1_1egiw_920f21548b7a3723923dd108fe514c61}
 
-\begin{CompactList}\small\item\em Returns a sample, $x$ from density $epdf(rv)$. \item\end{CompactList}\item 
+\begin{CompactList}\small\item\em Returns a sample, $ x $ from density $ f_x()$. \item\end{CompactList}\item 
 \hypertarget{classbdm_1_1egiw_df70c05f918c3a6f86d60f10c1fd6ba2}{
 vec \hyperlink{classbdm_1_1egiw_df70c05f918c3a6f86d60f10c1fd6ba2}{mean} () const }
@@ -65,24 +50,4 @@
 
 \begin{CompactList}\small\item\em logarithm of the normalizing constant, $\mathcal{I}$ \item\end{CompactList}\item 
-\hypertarget{classbdm_1_1egiw_15792f3112e5cf67d572f491b09324c8}{
-\hyperlink{classldmat}{ldmat} \& \hyperlink{classbdm_1_1egiw_15792f3112e5cf67d572f491b09324c8}{\_\-V} ()}
-\label{classbdm_1_1egiw_15792f3112e5cf67d572f491b09324c8}
-
-\begin{CompactList}\small\item\em returns a pointer to the internal statistics. Use with Care! \item\end{CompactList}\item 
-\hypertarget{classbdm_1_1egiw_ad9c539a80a552e837245ddcebcbbba4}{
-const \hyperlink{classldmat}{ldmat} \& \hyperlink{classbdm_1_1egiw_ad9c539a80a552e837245ddcebcbbba4}{\_\-V} () const }
-\label{classbdm_1_1egiw_ad9c539a80a552e837245ddcebcbbba4}
-
-\begin{CompactList}\small\item\em returns a pointer to the internal statistics. Use with Care! \item\end{CompactList}\item 
-\hypertarget{classbdm_1_1egiw_a025ee710274ca142dd0ae978735ad4a}{
-double \& \hyperlink{classbdm_1_1egiw_a025ee710274ca142dd0ae978735ad4a}{\_\-nu} ()}
-\label{classbdm_1_1egiw_a025ee710274ca142dd0ae978735ad4a}
-
-\begin{CompactList}\small\item\em returns a pointer to the internal statistics. Use with Care! \item\end{CompactList}\item 
-\hypertarget{classbdm_1_1egiw_cf3b2bcb158c15c24788bba90e4154e4}{
-const double \& \textbf{\_\-nu} () const }
-\label{classbdm_1_1egiw_cf3b2bcb158c15c24788bba90e4154e4}
-
-\item 
 \hypertarget{classbdm_1_1egiw_8e610e95401a11baf34f65e16ecd87be}{
 void \hyperlink{classbdm_1_1egiw_8e610e95401a11baf34f65e16ecd87be}{pow} (double p)}
@@ -104,10 +69,56 @@
 \label{classbdm_1_1eEF_79a7c8ea8c02e45d410bd1d7ffd72b41}
 
-\begin{CompactList}\small\item\em Evaluate normalized log-probability for many samples. \item\end{CompactList}\item 
+\begin{CompactList}\small\item\em Evaluate normalized log-probability for many samples. \item\end{CompactList}\end{CompactItemize}
+\begin{Indent}{\bf Constructors}\par
+\begin{CompactItemize}
+\item 
+\hypertarget{classbdm_1_1egiw_50149cf136c9120b4fff71c117f0bb2e}{
+\textbf{egiw} ()}
+\label{classbdm_1_1egiw_50149cf136c9120b4fff71c117f0bb2e}
+
+\item 
+\hypertarget{classbdm_1_1egiw_79037e048e717a076f342eb1d276870e}{
+\textbf{egiw} (int dimx0, \hyperlink{classldmat}{ldmat} V0, double nu0=-1.0)}
+\label{classbdm_1_1egiw_79037e048e717a076f342eb1d276870e}
+
+\item 
+\hypertarget{classbdm_1_1egiw_40b04f8ef133d089c4be2c7983e18b5c}{
+void \textbf{set\_\-parameters} (int dimx0, \hyperlink{classldmat}{ldmat} V0, double nu0=-1.0)}
+\label{classbdm_1_1egiw_40b04f8ef133d089c4be2c7983e18b5c}
+
+\end{CompactItemize}
+\end{Indent}
+\begin{Indent}{\bf Access attributes}\par
+\begin{CompactItemize}
+\item 
+\hypertarget{classbdm_1_1egiw_15792f3112e5cf67d572f491b09324c8}{
+\hyperlink{classldmat}{ldmat} \& \textbf{\_\-V} ()}
+\label{classbdm_1_1egiw_15792f3112e5cf67d572f491b09324c8}
+
+\item 
+\hypertarget{classbdm_1_1egiw_ad9c539a80a552e837245ddcebcbbba4}{
+const \hyperlink{classldmat}{ldmat} \& \textbf{\_\-V} () const }
+\label{classbdm_1_1egiw_ad9c539a80a552e837245ddcebcbbba4}
+
+\item 
+\hypertarget{classbdm_1_1egiw_a025ee710274ca142dd0ae978735ad4a}{
+double \& \textbf{\_\-nu} ()}
+\label{classbdm_1_1egiw_a025ee710274ca142dd0ae978735ad4a}
+
+\item 
+\hypertarget{classbdm_1_1egiw_cf3b2bcb158c15c24788bba90e4154e4}{
+const double \& \textbf{\_\-nu} () const }
+\label{classbdm_1_1egiw_cf3b2bcb158c15c24788bba90e4154e4}
+
+\end{CompactItemize}
+\end{Indent}
+\begin{Indent}{\bf Matematical Operations}\par
+\begin{CompactItemize}
+\item 
 \hypertarget{classbdm_1_1epdf_b4cf45fd83cc7573ede9fe1215256058}{
 virtual mat \hyperlink{classbdm_1_1epdf_b4cf45fd83cc7573ede9fe1215256058}{sample\_\-m} (int N) const }
 \label{classbdm_1_1epdf_b4cf45fd83cc7573ede9fe1215256058}
 
-\begin{CompactList}\small\item\em Returns N samples from density $epdf(rv)$. \item\end{CompactList}\item 
+\begin{CompactList}\small\item\em Returns N samples, $ [x_1 , x_2 , \ldots \ $ from density $ f_x(rv)$. \item\end{CompactList}\item 
 \hypertarget{classbdm_1_1epdf_34956d4dd3176eeb5937cf48a1546b62}{
 virtual vec \hyperlink{classbdm_1_1epdf_34956d4dd3176eeb5937cf48a1546b62}{evallog\_\-m} (const mat \&Val) const }
@@ -124,15 +135,34 @@
 \label{classbdm_1_1epdf_3fb2ece54f720b62ad325e61214fa0a1}
 
-\begin{CompactList}\small\item\em Return marginal density on the given \hyperlink{classbdm_1_1RV}{RV}, the remainig rvs are intergrated out. \item\end{CompactList}\item 
+\begin{CompactList}\small\item\em Return marginal density on the given \hyperlink{classbdm_1_1RV}{RV}, the remainig rvs are intergrated out. \item\end{CompactList}\end{CompactItemize}
+\end{Indent}
+\begin{Indent}{\bf Connection to other classes}\par
+{\em Description of the random quantity via attribute {\tt rv} is optional. For operations such as sampling {\tt rv} does not need to be set. However, for {\tt marginalization} and {\tt conditioning} {\tt rv} has to be set. NB: }\begin{CompactItemize}
+\item 
+\hypertarget{classbdm_1_1epdf_f423e28448dbb69ef4905295ec8de8ff}{
+void \hyperlink{classbdm_1_1epdf_f423e28448dbb69ef4905295ec8de8ff}{set\_\-rv} (const \hyperlink{classbdm_1_1RV}{RV} \&rv0)}
+\label{classbdm_1_1epdf_f423e28448dbb69ef4905295ec8de8ff}
+
+\begin{CompactList}\small\item\em Name its rv. \item\end{CompactList}\item 
+\hypertarget{classbdm_1_1epdf_c4b863ff84c7a4882fb3ad18556027f9}{
+bool \hyperlink{classbdm_1_1epdf_c4b863ff84c7a4882fb3ad18556027f9}{isnamed} () const }
+\label{classbdm_1_1epdf_c4b863ff84c7a4882fb3ad18556027f9}
+
+\begin{CompactList}\small\item\em True if rv is assigned. \item\end{CompactList}\item 
 \hypertarget{classbdm_1_1epdf_a4ab378d5e004c3ff3e2d4e64f7bba21}{
 const \hyperlink{classbdm_1_1RV}{RV} \& \hyperlink{classbdm_1_1epdf_a4ab378d5e004c3ff3e2d4e64f7bba21}{\_\-rv} () const }
 \label{classbdm_1_1epdf_a4ab378d5e004c3ff3e2d4e64f7bba21}
 
-\begin{CompactList}\small\item\em access function, possibly dangerous! \item\end{CompactList}\item 
-\hypertarget{classbdm_1_1epdf_62e88cbce0ce77a8692f5e15d76e805f}{
-void \hyperlink{classbdm_1_1epdf_62e88cbce0ce77a8692f5e15d76e805f}{\_\-renewrv} (const \hyperlink{classbdm_1_1RV}{RV} \&in\_\-rv)}
-\label{classbdm_1_1epdf_62e88cbce0ce77a8692f5e15d76e805f}
-
-\begin{CompactList}\small\item\em modifier function - useful when copying epdfs \item\end{CompactList}\end{CompactItemize}
+\begin{CompactList}\small\item\em Return name (fails when isnamed is false). \item\end{CompactList}\end{CompactItemize}
+\end{Indent}
+\begin{Indent}{\bf Access to attributes}\par
+\begin{CompactItemize}
+\item 
+\hypertarget{classbdm_1_1epdf_46dfe100cd621716ee5c7ee25a20f24b}{
+bool \hyperlink{classbdm_1_1epdf_46dfe100cd621716ee5c7ee25a20f24b}{dimension} () const }
+\label{classbdm_1_1epdf_46dfe100cd621716ee5c7ee25a20f24b}
+
+\begin{CompactList}\small\item\em Size of the random variable. \item\end{CompactList}\end{CompactItemize}
+\end{Indent}
 \subsection*{Protected Attributes}
 \begin{CompactItemize}
@@ -148,7 +178,7 @@
 
 \begin{CompactList}\small\item\em Number of data records (degrees of freedom) of sufficient statistics. \item\end{CompactList}\item 
-\hypertarget{classbdm_1_1egiw_40b68a9c3b2120fba94cc4d2fcd291e1}{
-int \hyperlink{classbdm_1_1egiw_40b68a9c3b2120fba94cc4d2fcd291e1}{xdim}}
-\label{classbdm_1_1egiw_40b68a9c3b2120fba94cc4d2fcd291e1}
+\hypertarget{classbdm_1_1egiw_23e4d78bea7e98840f3da30e76a2b57a}{
+int \hyperlink{classbdm_1_1egiw_23e4d78bea7e98840f3da30e76a2b57a}{dimx}}
+\label{classbdm_1_1egiw_23e4d78bea7e98840f3da30e76a2b57a}
 
 \begin{CompactList}\small\item\em Dimension of the output. \item\end{CompactList}\item 
@@ -158,15 +188,15 @@
 
 \begin{CompactList}\small\item\em Dimension of the regressor. \item\end{CompactList}\item 
+\hypertarget{classbdm_1_1epdf_16adac20ec7fe07e1ea0b27d917788ce}{
+int \hyperlink{classbdm_1_1epdf_16adac20ec7fe07e1ea0b27d917788ce}{dim}}
+\label{classbdm_1_1epdf_16adac20ec7fe07e1ea0b27d917788ce}
+
+\begin{CompactList}\small\item\em dimension of the random variable \item\end{CompactList}\item 
 \hypertarget{classbdm_1_1epdf_62c5b8ff71d9ebe6cd58d3c342eb1dc8}{
 \hyperlink{classbdm_1_1RV}{RV} \hyperlink{classbdm_1_1epdf_62c5b8ff71d9ebe6cd58d3c342eb1dc8}{rv}}
 \label{classbdm_1_1epdf_62c5b8ff71d9ebe6cd58d3c342eb1dc8}
 
-\begin{CompactList}\small\item\em Identified of the random variable. \item\end{CompactList}\end{CompactItemize}
-
-
-\subsection{Detailed Description}
-Gauss-inverse-Wishart density stored in LD form. 
-
-For $p$-variate densities, given rv.count() should be $p\times$ V.rows(). 
+\begin{CompactList}\small\item\em Description of the random variable. \item\end{CompactList}\end{CompactItemize}
+
 
 The documentation for this class was generated from the following files:\begin{CompactItemize}
