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[172]1\hypertarget{libBM_8h}{
[145]2\section{work/git/mixpp/bdm/stat/libBM.h File Reference}
3\label{libBM_8h}\index{work/git/mixpp/bdm/stat/libBM.h@{work/git/mixpp/bdm/stat/libBM.h}}
[172]4}
[3]5Bayesian Models (bm) that use Bayes rule to learn from observations.
6
7{\tt \#include $<$itpp/itbase.h$>$}\par
[210]8{\tt \#include \char`\"{}../itpp\_\-ext.h\char`\"{}}\par
[19]9
10
11Include dependency graph for libBM.h:\nopagebreak
12\begin{figure}[H]
13\begin{center}
14\leavevmode
[145]15\includegraphics[width=106pt]{libBM_8h__incl}
[19]16\end{center}
17\end{figure}
18
19
20This graph shows which files directly or indirectly include this file:\nopagebreak
21\begin{figure}[H]
22\begin{center}
23\leavevmode
[106]24\includegraphics[width=420pt]{libBM_8h__dep__incl}
[19]25\end{center}
26\end{figure}
[3]27\subsection*{Classes}
28\begin{CompactItemize}
29\item 
[172]30class \hyperlink{classstr}{str}
[181]31\begin{CompactList}\small\item\em Structure of \hyperlink{classRV}{RV} (used internally), i.e. expanded RVs. \item\end{CompactList}\item 
[172]32class \hyperlink{classRV}{RV}
[4]33\begin{CompactList}\small\item\em Class representing variables, most often random variables. \item\end{CompactList}\item 
[172]34class \hyperlink{classfnc}{fnc}
[91]35\begin{CompactList}\small\item\em Class representing function $f(x)$ of variable $x$ represented by {\tt rv}. \item\end{CompactList}\item 
[172]36class \hyperlink{classepdf}{epdf}
[4]37\begin{CompactList}\small\item\em Probability density function with numerical statistics, e.g. posterior density. \item\end{CompactList}\item 
[172]38class \hyperlink{classmpdf}{mpdf}
[19]39\begin{CompactList}\small\item\em Conditional probability density, e.g. modeling some dependencies. \item\end{CompactList}\item 
[210]40class \hyperlink{classdatalink__e2e}{datalink\_\-e2e}
41\item 
42class \hyperlink{classdatalink__m2e}{datalink\_\-m2e}
43\begin{CompactList}\small\item\em data link between \item\end{CompactList}\item 
44class \hyperlink{classdatalink__m2m}{datalink\_\-m2m}
45\item 
[172]46class \hyperlink{classmepdf}{mepdf}
47\begin{CompactList}\small\item\em Unconditional \hyperlink{classmpdf}{mpdf}, allows using \hyperlink{classepdf}{epdf} in the role of \hyperlink{classmpdf}{mpdf}. \item\end{CompactList}\item 
[180]48class \hyperlink{classcompositepdf}{compositepdf}
[210]49\begin{CompactList}\small\item\em Abstract composition of pdfs, a base for specific classes this abstract class is common to \hyperlink{classepdf}{epdf} and \hyperlink{classmpdf}{mpdf}. \item\end{CompactList}\item 
[172]50class \hyperlink{classDS}{DS}
[32]51\begin{CompactList}\small\item\em Abstract class for discrete-time sources of data. \item\end{CompactList}\item 
[172]52class \hyperlink{classBM}{BM}
[32]53\begin{CompactList}\small\item\em Bayesian Model of the world, i.e. all uncertainty is modeled by probabilities. \item\end{CompactList}\item 
[172]54class \hyperlink{classBMcond}{BMcond}
[32]55\begin{CompactList}\small\item\em Conditional Bayesian Filter. \item\end{CompactList}\end{CompactItemize}
[162]56\subsection*{Functions}
57\begin{CompactItemize}
58\item 
[219]59\hypertarget{group__core_g33c114e83980d883c5b211c47d5322a4}{
60\hyperlink{classRV}{RV} \hyperlink{group__core_g33c114e83980d883c5b211c47d5322a4}{concat} (const \hyperlink{classRV}{RV} \&rv1, const \hyperlink{classRV}{RV} \&rv2)}
61\label{group__core_g33c114e83980d883c5b211c47d5322a4}
[3]62
[162]63\begin{CompactList}\small\item\em Concat two random variables. \item\end{CompactList}\end{CompactItemize}
[219]64\subsection*{Variables}
65\begin{CompactItemize}
66\item 
67\hypertarget{group__core_g9ea0562597470f6058ec209ee72db5fa}{
68\hyperlink{classRV}{RV} \hyperlink{group__core_g9ea0562597470f6058ec209ee72db5fa}{RV0}}
69\label{group__core_g9ea0562597470f6058ec209ee72db5fa}
[3]70
[219]71\begin{CompactList}\small\item\em Default empty \hyperlink{classRV}{RV} that can be used as default argument. \item\end{CompactList}\end{CompactItemize}
[162]72
[219]73
[3]74\subsection{Detailed Description}
75Bayesian Models (bm) that use Bayes rule to learn from observations.
76
77\begin{Desc}
78\item[Author:]Vaclav Smidl.\end{Desc}
79----------------------------------- BDM++ - C++ library for Bayesian Decision Making under Uncertainty
80
81Using IT++ for numerical operations -----------------------------------
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