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1\section{emix Class Reference}
2\label{classemix}\index{emix@{emix}}
3Mixture of epdfs. 
4
5
6{\tt \#include $<$emix.h$>$}
7
8Inheritance diagram for emix:\nopagebreak
9\begin{figure}[H]
10\begin{center}
11\leavevmode
12\includegraphics[width=40pt]{classemix__inherit__graph}
13\end{center}
14\end{figure}
15Collaboration diagram for emix:\nopagebreak
16\begin{figure}[H]
17\begin{center}
18\leavevmode
19\includegraphics[width=40pt]{classemix__coll__graph}
20\end{center}
21\end{figure}
22\subsection*{Public Member Functions}
23\begin{CompactItemize}
24\item 
25{\bf emix} ({\bf RV} \&{\bf rv})\label{classemix_3a10c8481115a5460877272ddb6532a6}
26
27\begin{CompactList}\small\item\em Default constructor. \item\end{CompactList}\item 
28void {\bf set\_\-parameters} (const vec \&{\bf w}, const Array$<$ {\bf epdf} $\ast$ $>$ \&{\bf Coms})\label{classemix_6ce82b24d7fe540ddbf44b472a005555}
29
30\begin{CompactList}\small\item\em Set weights {\tt w} and components {\tt R}. \item\end{CompactList}\item 
31vec {\bf sample} () const
32\begin{CompactList}\small\item\em Returns the required moment of the \doxyref{epdf}{p.}{classepdf}. \item\end{CompactList}\item 
33vec {\bf mean} () const \label{classemix_b662a51d042b062020460e64bff4e9e8}
34
35\begin{CompactList}\small\item\em return expected value \item\end{CompactList}\item 
36double {\bf evalpdflog} (const vec \&val) const \label{classemix_469e910479b3402589104ef3bb1b5741}
37
38\begin{CompactList}\small\item\em Compute log-probability of argument {\tt val}. \item\end{CompactList}\item 
39vec \& {\bf \_\-w} ()\label{classemix_35baf0f62307455cebfbf462144b4dd8}
40
41\begin{CompactList}\small\item\em returns a pointer to the internal mean value. Use with Care! \item\end{CompactList}\item 
42virtual mat {\bf sampleN} (int N) const \label{classepdf_54d7dd53a641b618771cd9bee135181f}
43
44\begin{CompactList}\small\item\em Returns N samples from density $epdf(rv)$. \item\end{CompactList}\item 
45virtual double {\bf eval} (const vec \&val) const \label{classepdf_3ea597362e11a0040fe7c990269d072c}
46
47\begin{CompactList}\small\item\em Compute probability of argument {\tt val}. \item\end{CompactList}\item 
48{\bf RV} {\bf \_\-rv} () const \label{classepdf_b89143f12c9b49282e30841e4fb5f337}
49
50\begin{CompactList}\small\item\em access function \item\end{CompactList}\end{CompactItemize}
51\subsection*{Protected Attributes}
52\begin{CompactItemize}
53\item 
54vec {\bf w}\label{classemix_cdc8f4e2a5e43595ac5450d8a7f9d1ab}
55
56\begin{CompactList}\small\item\em weights of the components \item\end{CompactList}\item 
57Array$<$ {\bf epdf} $\ast$ $>$ {\bf Coms}\label{classemix_7155d827417b53fb6aa5cff1459e6eb4}
58
59\begin{CompactList}\small\item\em Component (epdfs). \item\end{CompactList}\item 
60{\bf RV} {\bf rv}\label{classepdf_74da992e3f5d598da8850b646b79b9d9}
61
62\begin{CompactList}\small\item\em Identified of the random variable. \item\end{CompactList}\end{CompactItemize}
63
64
65\subsection{Detailed Description}
66Mixture of epdfs.
67
68Density function: \[ f(x) = \sum_{i=1}^{n} w_{i} f_i(x), \quad \sum_{i=1}^n w_i = 1. \] where $f_i(x)$ is any density on random variable $x$, called {\em component\/},
69
70\subsection{Member Function Documentation}
71\index{emix@{emix}!sample@{sample}}
72\index{sample@{sample}!emix@{emix}}
73\subsubsection[sample]{\setlength{\rightskip}{0pt plus 5cm}vec emix::sample () const\hspace{0.3cm}{\tt  [virtual]}}\label{classemix_0650601f24e633e0ab09aa1e46c14483}
74
75
76Returns the required moment of the \doxyref{epdf}{p.}{classepdf}.
77
78Returns a sample, $x$ from density $epdf(rv)$ 
79
80Implements {\bf epdf} \doxyref{}{p.}{classepdf_8019654e494bf5e458f6fb947e11b262}.
81
82References Coms, and w.
83
84The documentation for this class was generated from the following files:\begin{CompactItemize}
85\item 
86work/mixpp/bdm/stat/{\bf emix.h}\item 
87work/mixpp/bdm/stat/emix.cpp\end{CompactItemize}
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