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1\section{mpdf Class Reference}
2\label{classmpdf}\index{mpdf@{mpdf}}
3Conditional probability density, e.g. modeling some dependencies. 
4
5
6{\tt \#include $<$libBM.h$>$}
7
8Inheritance diagram for mpdf:\nopagebreak
9\begin{figure}[H]
10\begin{center}
11\leavevmode
12\includegraphics[width=170pt]{classmpdf__inherit__graph}
13\end{center}
14\end{figure}
15Collaboration diagram for mpdf:\nopagebreak
16\begin{figure}[H]
17\begin{center}
18\leavevmode
19\includegraphics[width=56pt]{classmpdf__coll__graph}
20\end{center}
21\end{figure}
22\subsection*{Public Member Functions}
23\begin{CompactItemize}
24\item 
25virtual vec {\bf samplecond} (const vec \&cond, double \&ll)
26\begin{CompactList}\small\item\em Returns the required moment of the \doxyref{epdf}{p.}{classepdf}. \item\end{CompactList}\item 
27virtual mat {\bf samplecond} (const vec \&cond, vec \&ll, int N)
28\begin{CompactList}\small\item\em Returns. \item\end{CompactList}\item 
29virtual void {\bf condition} (const vec \&cond)\label{classmpdf_0f95a0cc6ab40611f46804682446ed83}
30
31\begin{CompactList}\small\item\em Update {\tt ep} so that it represents this \doxyref{mpdf}{p.}{classmpdf} conditioned on {\tt rvc} = cond. \item\end{CompactList}\item 
32virtual double {\bf evalcond} (const vec \&dt, const vec \&cond)\label{classmpdf_80b738ece5bd4f8c4edaee4b38906f91}
33
34\begin{CompactList}\small\item\em Shortcut for conditioning and evaluation of the internal \doxyref{epdf}{p.}{classepdf}. In some cases, this operation can be implemented efficiently. \item\end{CompactList}\item 
35virtual {\bf $\sim$mpdf} ()\label{classmpdf_6788be9f3a888796499c5293a318fcfb}
36
37\begin{CompactList}\small\item\em Destructor for future use;. \item\end{CompactList}\item 
38{\bf mpdf} (const {\bf RV} \&rv0, const {\bf RV} \&rvc0)\label{classmpdf_581ecf362185d37c08bb31cb9d046d6f}
39
40\begin{CompactList}\small\item\em Default constructor. \item\end{CompactList}\item 
41{\bf RV} {\bf \_\-rvc} ()\label{classmpdf_ec9c850305984582548e8deb64f0ffe8}
42
43\begin{CompactList}\small\item\em access function \item\end{CompactList}\item 
44{\bf RV} {\bf \_\-rv} ()\label{classmpdf_1e71ad4c66d5884c82d4a3b06b42fe32}
45
46\begin{CompactList}\small\item\em access function \item\end{CompactList}\item 
47{\bf epdf} \& {\bf \_\-epdf} ()\label{classmpdf_e17780ee5b2cfe05922a6c56af1462f8}
48
49\begin{CompactList}\small\item\em access function \item\end{CompactList}\end{CompactItemize}
50\subsection*{Protected Attributes}
51\begin{CompactItemize}
52\item 
53{\bf RV} {\bf rv}\label{classmpdf_f6687c07ff07d47812dd565368ca59eb}
54
55\begin{CompactList}\small\item\em modeled random variable \item\end{CompactList}\item 
56{\bf RV} {\bf rvc}\label{classmpdf_acb7dda792b3cd5576f39fa3129abbab}
57
58\begin{CompactList}\small\item\em random variable in condition \item\end{CompactList}\item 
59{\bf epdf} $\ast$ {\bf ep}\label{classmpdf_7aa894208a32f3487827df6d5054424c}
60
61\begin{CompactList}\small\item\em pointer to internal \doxyref{epdf}{p.}{classepdf} \item\end{CompactList}\end{CompactItemize}
62
63
64\subsection{Detailed Description}
65Conditional probability density, e.g. modeling some dependencies.
66
67\subsection{Member Function Documentation}
68\index{mpdf@{mpdf}!samplecond@{samplecond}}
69\index{samplecond@{samplecond}!mpdf@{mpdf}}
70\subsubsection[samplecond]{\setlength{\rightskip}{0pt plus 5cm}virtual vec mpdf::samplecond (const vec \& {\em cond}, \/  double \& {\em ll})\hspace{0.3cm}{\tt  [inline, virtual]}}\label{classmpdf_3f172b79ec4a5ebc87898a5381141f1b}
71
72
73Returns the required moment of the \doxyref{epdf}{p.}{classepdf}.
74
75Returns a sample from the density conditioned on {\tt cond}, $x \sim epdf(rv|cond)$. \begin{Desc}
76\item[Parameters:]
77\begin{description}
78\item[{\em cond}]is numeric value of {\tt rv} \item[{\em ll}]is a return value of log-likelihood of the sample. \end{description}
79\end{Desc}
80
81
82References condition(), ep, epdf::evalpdflog(), and epdf::sample().
83
84Referenced by MPF$<$ BM\_\-T $>$::bayes(), and PF::bayes().\index{mpdf@{mpdf}!samplecond@{samplecond}}
85\index{samplecond@{samplecond}!mpdf@{mpdf}}
86\subsubsection[samplecond]{\setlength{\rightskip}{0pt plus 5cm}virtual mat mpdf::samplecond (const vec \& {\em cond}, \/  vec \& {\em ll}, \/  int {\em N})\hspace{0.3cm}{\tt  [inline, virtual]}}\label{classmpdf_0e37163660f93df2a4d723cedb1da89c}
87
88
89Returns.
90
91\begin{Desc}
92\item[Parameters:]
93\begin{description}
94\item[{\em N}]samples from the density conditioned on {\tt cond}, $x \sim epdf(rv|cond)$. \item[{\em cond}]is numeric value of {\tt rv} \item[{\em ll}]is a return value of log-likelihood of the sample. \end{description}
95\end{Desc}
96
97
98References condition(), RV::count(), ep, epdf::evalpdflog(), rv, and epdf::sample().
99
100The documentation for this class was generated from the following file:\begin{CompactItemize}
101\item 
102work/git/mixpp/bdm/stat/{\bf libBM.h}\end{CompactItemize}
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