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[172]1\hypertarget{classeEmp}{
[30]2\section{eEmp Class Reference}
3\label{classeEmp}\index{eEmp@{eEmp}}
[172]4}
[30]5Weighted empirical density. 
6
7
8{\tt \#include $<$libEF.h$>$}
9
10Inheritance diagram for eEmp:\nopagebreak
11\begin{figure}[H]
12\begin{center}
13\leavevmode
[91]14\includegraphics[width=43pt]{classeEmp__inherit__graph}
[30]15\end{center}
16\end{figure}
17Collaboration diagram for eEmp:\nopagebreak
18\begin{figure}[H]
19\begin{center}
20\leavevmode
[91]21\includegraphics[width=43pt]{classeEmp__coll__graph}
[30]22\end{center}
23\end{figure}
24\subsection*{Public Member Functions}
25\begin{CompactItemize}
26\item 
[172]27\hypertarget{classeEmp_0c04b073ecd0dae3d498e680ae27e9e4}{
28\hyperlink{classeEmp_0c04b073ecd0dae3d498e680ae27e9e4}{eEmp} (const \hyperlink{classRV}{RV} \&rv0, int n0)}
29\label{classeEmp_0c04b073ecd0dae3d498e680ae27e9e4}
[30]30
[33]31\begin{CompactList}\small\item\em Default constructor. \item\end{CompactList}\item 
[180]32\hypertarget{classeEmp_eab03bd3381aaea11ce34d5a26556353}{
33void \hyperlink{classeEmp_eab03bd3381aaea11ce34d5a26556353}{set\_\-parameters} (const vec \&w0, const \hyperlink{classepdf}{epdf} $\ast$pdf0)}
34\label{classeEmp_eab03bd3381aaea11ce34d5a26556353}
[30]35
[180]36\begin{CompactList}\small\item\em Set samples and weights. \item\end{CompactList}\item 
37\hypertarget{classeEmp_e31bc9e6196173c3480b06a761a3e716}{
38void \hyperlink{classeEmp_e31bc9e6196173c3480b06a761a3e716}{set\_\-samples} (const \hyperlink{classepdf}{epdf} $\ast$pdf0)}
39\label{classeEmp_e31bc9e6196173c3480b06a761a3e716}
40
[33]41\begin{CompactList}\small\item\em Set sample. \item\end{CompactList}\item 
[172]42\hypertarget{classeEmp_31b2bfb73b72486a5c89f2ab850c7a9b}{
43vec \& \hyperlink{classeEmp_31b2bfb73b72486a5c89f2ab850c7a9b}{\_\-w} ()}
44\label{classeEmp_31b2bfb73b72486a5c89f2ab850c7a9b}
[30]45
46\begin{CompactList}\small\item\em Potentially dangerous, use with care. \item\end{CompactList}\item 
[172]47\hypertarget{classeEmp_31b747eca73b16f30370827ba4cc3575}{
48Array$<$ vec $>$ \& \hyperlink{classeEmp_31b747eca73b16f30370827ba4cc3575}{\_\-samples} ()}
49\label{classeEmp_31b747eca73b16f30370827ba4cc3575}
[30]50
[33]51\begin{CompactList}\small\item\em access function \item\end{CompactList}\item 
[172]52\hypertarget{classeEmp_77268292fc4465cb73ddbfb1f2932a59}{
53ivec \hyperlink{classeEmp_77268292fc4465cb73ddbfb1f2932a59}{resample} (\hyperlink{libEF_8h_99497a3ff630f761cf6bff7babd23212}{RESAMPLING\_\-METHOD} method=SYSTEMATIC)}
54\label{classeEmp_77268292fc4465cb73ddbfb1f2932a59}
[30]55
56\begin{CompactList}\small\item\em Function performs resampling, i.e. removal of low-weight samples and duplication of high-weight samples such that the new samples represent the same density. \item\end{CompactList}\item 
[172]57\hypertarget{classeEmp_83f9283f92b805508d896479dc1ccf12}{
58vec \hyperlink{classeEmp_83f9283f92b805508d896479dc1ccf12}{sample} () const }
59\label{classeEmp_83f9283f92b805508d896479dc1ccf12}
[30]60
[33]61\begin{CompactList}\small\item\em inherited operation : NOT implemneted \item\end{CompactList}\item 
[172]62\hypertarget{classeEmp_23e7358995400865ad2e278945922fb3}{
63double \hyperlink{classeEmp_23e7358995400865ad2e278945922fb3}{evalpdflog} (const vec \&val) const }
64\label{classeEmp_23e7358995400865ad2e278945922fb3}
[33]65
66\begin{CompactList}\small\item\em inherited operation : NOT implemneted \item\end{CompactList}\item 
[172]67\hypertarget{classeEmp_ba055c19038cc72628d98e25197e982d}{
68vec \hyperlink{classeEmp_ba055c19038cc72628d98e25197e982d}{mean} () const }
69\label{classeEmp_ba055c19038cc72628d98e25197e982d}
[33]70
[30]71\begin{CompactList}\small\item\em return expected value \item\end{CompactList}\item 
[172]72\hypertarget{classepdf_54d7dd53a641b618771cd9bee135181f}{
73virtual mat \hyperlink{classepdf_54d7dd53a641b618771cd9bee135181f}{sampleN} (int N) const }
74\label{classepdf_54d7dd53a641b618771cd9bee135181f}
[106]75
76\begin{CompactList}\small\item\em Returns N samples from density $epdf(rv)$. \item\end{CompactList}\item 
[172]77\hypertarget{classepdf_3ea597362e11a0040fe7c990269d072c}{
78virtual double \hyperlink{classepdf_3ea597362e11a0040fe7c990269d072c}{eval} (const vec \&val) const }
79\label{classepdf_3ea597362e11a0040fe7c990269d072c}
[30]80
81\begin{CompactList}\small\item\em Compute probability of argument {\tt val}. \item\end{CompactList}\item 
[180]82\hypertarget{classepdf_cebbdd7a85e6328f7358fc0ba8eee06c}{
83virtual vec \hyperlink{classepdf_cebbdd7a85e6328f7358fc0ba8eee06c}{evalpdflog\_\-m} (const mat \&Val) const }
84\label{classepdf_cebbdd7a85e6328f7358fc0ba8eee06c}
[30]85
[172]86\begin{CompactList}\small\item\em Compute log-probability of multiple values argument {\tt val}. \item\end{CompactList}\item 
[181]87\hypertarget{classepdf_3ba08c0e788deff22134c049b9269666}{
88\hyperlink{classmpdf}{mpdf} $\ast$ \hyperlink{classepdf_3ba08c0e788deff22134c049b9269666}{condition} (const \hyperlink{classRV}{RV} \&\hyperlink{classepdf_74da992e3f5d598da8850b646b79b9d9}{rv})}
89\label{classepdf_3ba08c0e788deff22134c049b9269666}
90
91\begin{CompactList}\small\item\em Return conditional density on the given \hyperlink{classRV}{RV}, the remaining rvs will be in conditioning. \item\end{CompactList}\item 
92\hypertarget{classepdf_bc0c171b6dafacd78d26263913b1d0c0}{
93\hyperlink{classepdf}{epdf} $\ast$ \hyperlink{classepdf_bc0c171b6dafacd78d26263913b1d0c0}{marginal} (const \hyperlink{classRV}{RV} \&\hyperlink{classepdf_74da992e3f5d598da8850b646b79b9d9}{rv})}
94\label{classepdf_bc0c171b6dafacd78d26263913b1d0c0}
95
96\begin{CompactList}\small\item\em Return marginal density on the given \hyperlink{classRV}{RV}, the remainig rvs are intergrated out. \item\end{CompactList}\item 
[172]97\hypertarget{classepdf_ca0d32aabb4cbba347e0c37fe8607562}{
98const \hyperlink{classRV}{RV} \& \hyperlink{classepdf_ca0d32aabb4cbba347e0c37fe8607562}{\_\-rv} () const }
99\label{classepdf_ca0d32aabb4cbba347e0c37fe8607562}
100
101\begin{CompactList}\small\item\em access function, possibly dangerous! \item\end{CompactList}\item 
102\hypertarget{classepdf_7fb94ce90d1ac7077d29f7d6a6c3e0a5}{
103void \hyperlink{classepdf_7fb94ce90d1ac7077d29f7d6a6c3e0a5}{\_\-renewrv} (const \hyperlink{classRV}{RV} \&in\_\-rv)}
104\label{classepdf_7fb94ce90d1ac7077d29f7d6a6c3e0a5}
105
106\begin{CompactList}\small\item\em modifier function - useful when copying epdfs \item\end{CompactList}\end{CompactItemize}
[30]107\subsection*{Protected Attributes}
108\begin{CompactItemize}
109\item 
[172]110\hypertarget{classeEmp_8c33034de0e35f03f8bb85d3d67438fd}{
111int \hyperlink{classeEmp_8c33034de0e35f03f8bb85d3d67438fd}{n}}
112\label{classeEmp_8c33034de0e35f03f8bb85d3d67438fd}
[30]113
114\begin{CompactList}\small\item\em Number of particles. \item\end{CompactList}\item 
[172]115\hypertarget{classeEmp_ae78d144404ddba843c93b171b215de8}{
116vec \hyperlink{classeEmp_ae78d144404ddba843c93b171b215de8}{w}}
117\label{classeEmp_ae78d144404ddba843c93b171b215de8}
[30]118
[91]119\begin{CompactList}\small\item\em Sample weights $w$. \item\end{CompactList}\item 
[172]120\hypertarget{classeEmp_a4d6f4bbd6a6824fc39f14676701279a}{
121Array$<$ vec $>$ \hyperlink{classeEmp_a4d6f4bbd6a6824fc39f14676701279a}{samples}}
122\label{classeEmp_a4d6f4bbd6a6824fc39f14676701279a}
[30]123
[33]124\begin{CompactList}\small\item\em Samples $x^{(i)}, i=1..n$. \item\end{CompactList}\item 
[172]125\hypertarget{classepdf_74da992e3f5d598da8850b646b79b9d9}{
126\hyperlink{classRV}{RV} \hyperlink{classepdf_74da992e3f5d598da8850b646b79b9d9}{rv}}
127\label{classepdf_74da992e3f5d598da8850b646b79b9d9}
[30]128
[33]129\begin{CompactList}\small\item\em Identified of the random variable. \item\end{CompactList}\end{CompactItemize}
[30]130
131
132\subsection{Detailed Description}
133Weighted empirical density.
134
135Used e.g. in particle filters.
136
137The documentation for this class was generated from the following files:\begin{CompactItemize}
138\item 
[172]139work/git/mixpp/bdm/stat/\hyperlink{libEF_8h}{libEF.h}\item 
[145]140work/git/mixpp/bdm/stat/libEF.cpp\end{CompactItemize}
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