[172] | 1 | \hypertarget{libBM_8h}{ |
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[261] | 2 | \section{libBM.h File Reference} |
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| 3 | \label{libBM_8h}\index{libBM.h@{libBM.h}} |
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[172] | 4 | } |
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[3] | 5 | Bayesian Models (bm) that use Bayes rule to learn from observations. |
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| 6 | |
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[210] | 7 | {\tt \#include \char`\"{}../itpp\_\-ext.h\char`\"{}}\par |
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[19] | 8 | |
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| 9 | |
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| 10 | Include dependency graph for libBM.h:\nopagebreak |
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| 11 | \begin{figure}[H] |
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| 12 | \begin{center} |
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| 13 | \leavevmode |
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[261] | 14 | \includegraphics[width=59pt]{libBM_8h__incl} |
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[19] | 15 | \end{center} |
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| 16 | \end{figure} |
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| 17 | |
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| 18 | |
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| 19 | This graph shows which files directly or indirectly include this file:\nopagebreak |
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| 20 | \begin{figure}[H] |
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| 21 | \begin{center} |
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| 22 | \leavevmode |
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[261] | 23 | \includegraphics[width=272pt]{libBM_8h__dep__incl} |
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[19] | 24 | \end{center} |
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| 25 | \end{figure} |
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[255] | 26 | \subsection*{Namespaces} |
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| 27 | \begin{CompactItemize} |
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| 28 | \item |
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[261] | 29 | namespace \hyperlink{namespacebdm}{bdm} |
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[255] | 30 | \end{CompactItemize} |
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[3] | 31 | \subsection*{Classes} |
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| 32 | \begin{CompactItemize} |
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| 33 | \item |
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[261] | 34 | class \hyperlink{classbdm_1_1bdmroot}{bdm::bdmroot} |
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[255] | 35 | \begin{CompactList}\small\item\em Root class of BDM objects. \item\end{CompactList}\item |
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| 36 | class \hyperlink{classbdm_1_1str}{bdm::str} |
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| 37 | \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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| 38 | class \hyperlink{classbdm_1_1RV}{bdm::RV} |
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[4] | 39 | \begin{CompactList}\small\item\em Class representing variables, most often random variables. \item\end{CompactList}\item |
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[255] | 40 | class \hyperlink{classbdm_1_1fnc}{bdm::fnc} |
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[91] | 41 | \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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[255] | 42 | class \hyperlink{classbdm_1_1epdf}{bdm::epdf} |
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[4] | 43 | \begin{CompactList}\small\item\em Probability density function with numerical statistics, e.g. posterior density. \item\end{CompactList}\item |
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[255] | 44 | class \hyperlink{classbdm_1_1mpdf}{bdm::mpdf} |
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[19] | 45 | \begin{CompactList}\small\item\em Conditional probability density, e.g. modeling some dependencies. \item\end{CompactList}\item |
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[255] | 46 | class \hyperlink{classbdm_1_1datalink__e2e}{bdm::datalink\_\-e2e} |
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[261] | 47 | \begin{CompactList}\small\item\em DataLink is a connection between two data vectors Up and Down. \item\end{CompactList}\item |
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[255] | 48 | class \hyperlink{classbdm_1_1datalink__m2e}{bdm::datalink\_\-m2e} |
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[210] | 49 | \begin{CompactList}\small\item\em data link between \item\end{CompactList}\item |
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[255] | 50 | class \hyperlink{classbdm_1_1datalink__m2m}{bdm::datalink\_\-m2m} |
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[210] | 51 | \item |
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[255] | 52 | class \hyperlink{classbdm_1_1mepdf}{bdm::mepdf} |
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| 53 | \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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| 54 | class \hyperlink{classbdm_1_1compositepdf}{bdm::compositepdf} |
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[261] | 55 | \begin{CompactList}\small\item\em Abstract composition of pdfs, will be used 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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[255] | 56 | class \hyperlink{classbdm_1_1DS}{bdm::DS} |
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[32] | 57 | \begin{CompactList}\small\item\em Abstract class for discrete-time sources of data. \item\end{CompactList}\item |
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[255] | 58 | class \hyperlink{classbdm_1_1BM}{bdm::BM} |
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[32] | 59 | \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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[255] | 60 | class \hyperlink{classbdm_1_1BMcond}{bdm::BMcond} |
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[32] | 61 | \begin{CompactList}\small\item\em Conditional Bayesian Filter. \item\end{CompactList}\end{CompactItemize} |
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[162] | 62 | \subsection*{Functions} |
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| 63 | \begin{CompactItemize} |
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| 64 | \item |
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[255] | 65 | \hypertarget{namespacebdm_b9016687c0e874ca5cdcf75ae28811aa}{ |
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| 66 | RV \hyperlink{namespacebdm_b9016687c0e874ca5cdcf75ae28811aa}{bdm::concat} (const RV \&rv1, const RV \&rv2)} |
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| 67 | \label{namespacebdm_b9016687c0e874ca5cdcf75ae28811aa} |
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[3] | 68 | |
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[162] | 69 | \begin{CompactList}\small\item\em Concat two random variables. \item\end{CompactList}\end{CompactItemize} |
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[3] | 70 | |
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[162] | 71 | |
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[3] | 72 | \subsection{Detailed Description} |
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| 73 | Bayesian Models (bm) that use Bayes rule to learn from observations. |
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| 74 | |
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| 75 | \begin{Desc} |
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| 76 | \item[Author:]Vaclav Smidl.\end{Desc} |
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| 77 | ----------------------------------- BDM++ - C++ library for Bayesian Decision Making under Uncertainty |
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| 78 | |
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| 79 | Using IT++ for numerical operations ----------------------------------- |
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