1 | \hypertarget{libBM_8h}{ |
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2 | \section{work/git/mixpp/bdm/stat/libBM.h File Reference} |
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3 | \label{libBM_8h}\index{work/git/mixpp/bdm/stat/libBM.h@{work/git/mixpp/bdm/stat/libBM.h}} |
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4 | } |
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5 | Bayesian Models (bm) that use Bayes rule to learn from observations. |
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6 | |
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7 | {\tt \#include $<$itpp/itbase.h$>$}\par |
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8 | {\tt \#include \char`\"{}../itpp\_\-ext.h\char`\"{}}\par |
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9 | |
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10 | |
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11 | Include dependency graph for libBM.h:\nopagebreak |
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12 | \begin{figure}[H] |
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13 | \begin{center} |
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14 | \leavevmode |
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15 | \includegraphics[width=106pt]{libBM_8h__incl} |
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16 | \end{center} |
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17 | \end{figure} |
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18 | |
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19 | |
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20 | This graph shows which files directly or indirectly include this file:\nopagebreak |
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21 | \begin{figure}[H] |
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22 | \begin{center} |
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23 | \leavevmode |
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24 | \includegraphics[width=420pt]{libBM_8h__dep__incl} |
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25 | \end{center} |
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26 | \end{figure} |
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27 | \subsection*{Namespaces} |
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28 | \begin{CompactItemize} |
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29 | \item |
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30 | namespace \textbf{bdm} |
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31 | \end{CompactItemize} |
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32 | \subsection*{Classes} |
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33 | \begin{CompactItemize} |
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34 | \item |
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35 | class \hyperlink{classbdm_1_1base}{bdm::base} |
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36 | \begin{CompactList}\small\item\em Root class of BDM objects. \item\end{CompactList}\item |
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37 | class \hyperlink{classbdm_1_1str}{bdm::str} |
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38 | \begin{CompactList}\small\item\em Structure of \hyperlink{classbdm_1_1RV}{RV} (used internally), i.e. expanded RVs. \item\end{CompactList}\item |
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39 | class \hyperlink{classbdm_1_1RV}{bdm::RV} |
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40 | \begin{CompactList}\small\item\em Class representing variables, most often random variables. \item\end{CompactList}\item |
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41 | class \hyperlink{classbdm_1_1fnc}{bdm::fnc} |
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42 | \begin{CompactList}\small\item\em Class representing function $f(x)$ of variable $x$ represented by {\tt rv}. \item\end{CompactList}\item |
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43 | class \hyperlink{classbdm_1_1epdf}{bdm::epdf} |
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44 | \begin{CompactList}\small\item\em Probability density function with numerical statistics, e.g. posterior density. \item\end{CompactList}\item |
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45 | class \hyperlink{classbdm_1_1mpdf}{bdm::mpdf} |
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46 | \begin{CompactList}\small\item\em Conditional probability density, e.g. modeling some dependencies. \item\end{CompactList}\item |
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47 | class \hyperlink{classbdm_1_1datalink__e2e}{bdm::datalink\_\-e2e} |
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48 | \item |
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49 | class \hyperlink{classbdm_1_1datalink__m2e}{bdm::datalink\_\-m2e} |
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50 | \begin{CompactList}\small\item\em data link between \item\end{CompactList}\item |
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51 | class \hyperlink{classbdm_1_1datalink__m2m}{bdm::datalink\_\-m2m} |
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52 | \item |
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53 | class \hyperlink{classbdm_1_1mepdf}{bdm::mepdf} |
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54 | \begin{CompactList}\small\item\em Unconditional \hyperlink{classbdm_1_1mpdf}{mpdf}, allows using \hyperlink{classbdm_1_1epdf}{epdf} in the role of \hyperlink{classbdm_1_1mpdf}{mpdf}. \item\end{CompactList}\item |
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55 | class \hyperlink{classbdm_1_1compositepdf}{bdm::compositepdf} |
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56 | \begin{CompactList}\small\item\em Abstract composition of pdfs, a \hyperlink{classbdm_1_1base}{base} for specific classes this abstract class is common to \hyperlink{classbdm_1_1epdf}{epdf} and \hyperlink{classbdm_1_1mpdf}{mpdf}. \item\end{CompactList}\item |
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57 | class \hyperlink{classbdm_1_1DS}{bdm::DS} |
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58 | \begin{CompactList}\small\item\em Abstract class for discrete-time sources of data. \item\end{CompactList}\item |
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59 | class \hyperlink{classbdm_1_1BM}{bdm::BM} |
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60 | \begin{CompactList}\small\item\em Bayesian Model of the world, i.e. all uncertainty is modeled by probabilities. \item\end{CompactList}\item |
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61 | class \hyperlink{classbdm_1_1BMcond}{bdm::BMcond} |
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62 | \begin{CompactList}\small\item\em Conditional Bayesian Filter. \item\end{CompactList}\end{CompactItemize} |
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63 | \subsection*{Functions} |
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64 | \begin{CompactItemize} |
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65 | \item |
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66 | \hypertarget{namespacebdm_b9016687c0e874ca5cdcf75ae28811aa}{ |
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67 | RV \hyperlink{namespacebdm_b9016687c0e874ca5cdcf75ae28811aa}{bdm::concat} (const RV \&rv1, const RV \&rv2)} |
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68 | \label{namespacebdm_b9016687c0e874ca5cdcf75ae28811aa} |
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69 | |
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70 | \begin{CompactList}\small\item\em Concat two random variables. \item\end{CompactList}\end{CompactItemize} |
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71 | |
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72 | |
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73 | \subsection{Detailed Description} |
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74 | Bayesian Models (bm) that use Bayes rule to learn from observations. |
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75 | |
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76 | \begin{Desc} |
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77 | \item[Author:]Vaclav Smidl.\end{Desc} |
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78 | ----------------------------------- BDM++ - C++ library for Bayesian Decision Making under Uncertainty |
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79 | |
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80 | Using IT++ for numerical operations ----------------------------------- |
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