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1\section{work/mixpp/bdm/stat/arx.h File Reference}
2\label{stat_2arx_8h}\index{work/mixpp/bdm/stat/arx.h@{work/mixpp/bdm/stat/arx.h}}
3Bayesian Models (bm) that use Bayes rule to learn from observations.
4
5{\tt \#include $<$itpp/itbase.h$>$}\par
6{\tt \#include $<$libBM.h$>$}\par
7
8
9Include dependency graph for arx.h:\nopagebreak
10\begin{figure}[H]
11\begin{center}
12\leavevmode
13\includegraphics[width=88pt]{stat_2arx_8h__incl}
14\end{center}
15\end{figure}
16\subsection*{Classes}
17\begin{CompactItemize}
18\item 
19class {\bf ARX}
20\begin{CompactList}\small\item\em Linear Autoregressive model with Gaussian noise. \item\end{CompactList}\item 
21class {\bf BMcond}
22\begin{CompactList}\small\item\em Conditional Bayesian Filter. \item\end{CompactList}\end{CompactItemize}
23
24
25\subsection{Detailed Description}
26Bayesian Models (bm) that use Bayes rule to learn from observations.
27
28\begin{Desc}
29\item[Author:]Vaclav Smidl.\end{Desc}
30----------------------------------- BDM++ - C++ library for Bayesian Decision Making under Uncertainty
31
32Using IT++ for numerical operations -----------------------------------
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