root/doc/latex/stat_2arx_8h.tex @ 109

\section{work/mixpp/bdm/stat/arx.h File Reference}
\label{stat_2arx_8h}\index{work/mixpp/bdm/stat/arx.h@{work/mixpp/bdm/stat/arx.h}}
Bayesian Models (bm) that use Bayes rule to learn from observations. 

{\tt \#include $<$itpp/itbase.h$>$}\par
{\tt \#include $<$libBM.h$>$}\par


Include dependency graph for arx.h:\nopagebreak
\begin{figure}[H]
\begin{center}
\leavevmode
\includegraphics[width=88pt]{stat_2arx_8h__incl}
\end{center}
\end{figure}
\subsection*{Classes}
\begin{CompactItemize}
\item 
class {\bf ARX}
\begin{CompactList}\small\item\em Linear Autoregressive model with Gaussian noise. \item\end{CompactList}\item 
class {\bf BMcond}
\begin{CompactList}\small\item\em Conditional Bayesian Filter. \item\end{CompactList}\end{CompactItemize}


\subsection{Detailed Description}
Bayesian Models (bm) that use Bayes rule to learn from observations. 

\begin{Desc}
\item[Author:]Vaclav Smidl.\end{Desc}
----------------------------------- BDM++ - C++ library for Bayesian Decision Making under Uncertainty

Using IT++ for numerical operations -----------------------------------