[30] | 1 | \section{eEmp Class Reference} |
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| 2 | \label{classeEmp}\index{eEmp@{eEmp}} |
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| 3 | Weighted empirical density. |
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| 4 | |
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| 5 | |
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| 6 | {\tt \#include $<$libEF.h$>$} |
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| 7 | |
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| 8 | Inheritance diagram for eEmp:\nopagebreak |
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| 9 | \begin{figure}[H] |
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| 10 | \begin{center} |
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| 11 | \leavevmode |
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| 12 | \includegraphics[width=44pt]{classeEmp__inherit__graph} |
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| 13 | \end{center} |
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| 14 | \end{figure} |
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| 15 | Collaboration diagram for eEmp:\nopagebreak |
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| 16 | \begin{figure}[H] |
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| 17 | \begin{center} |
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| 18 | \leavevmode |
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| 19 | \includegraphics[width=44pt]{classeEmp__coll__graph} |
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| 20 | \end{center} |
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| 21 | \end{figure} |
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| 22 | \subsection*{Public Member Functions} |
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| 23 | \begin{CompactItemize} |
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| 24 | \item |
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| 25 | \textbf{eEmp} (const {\bf RV} \&rv0)\label{classeEmp_0b7235ea451df276dd2c57aae207fe34} |
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| 26 | |
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| 27 | \item |
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| 28 | void \textbf{set\_\-parameters} (const vec \&w0, {\bf epdf} $\ast$pdf0)\label{classeEmp_6606a656c1b28114f7384c25aaf80e8d} |
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| 29 | |
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| 30 | \item |
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| 31 | vec \& {\bf \_\-w} ()\label{classeEmp_31b2bfb73b72486a5c89f2ab850c7a9b} |
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| 32 | |
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| 33 | \begin{CompactList}\small\item\em Potentially dangerous, use with care. \item\end{CompactList}\item |
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| 34 | Array$<$ vec $>$ \& \textbf{\_\-samples} ()\label{classeEmp_31b747eca73b16f30370827ba4cc3575} |
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| 35 | |
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| 36 | \item |
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| 37 | ivec {\bf resample} ({\bf RESAMPLING\_\-METHOD} method=SYSTEMATIC)\label{classeEmp_77268292fc4465cb73ddbfb1f2932a59} |
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| 38 | |
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| 39 | \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 |
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| 40 | vec {\bf sample} () |
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| 41 | \begin{CompactList}\small\item\em Returns the required moment of the \doxyref{epdf}{p.}{classepdf}. \item\end{CompactList}\item |
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| 42 | vec {\bf mean} ()\label{classeEmp_de42454cb65a17fd8662d207dd59aacf} |
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| 43 | |
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| 44 | \begin{CompactList}\small\item\em return expected value \item\end{CompactList}\item |
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| 45 | virtual double {\bf eval} (const vec \&val)\label{classepdf_f333ceeb88ebc37d81fcd4cea4526bfc} |
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| 46 | |
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| 47 | \begin{CompactList}\small\item\em Compute probability of argument {\tt val}. \item\end{CompactList}\item |
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| 48 | virtual double {\bf evalpdflog} (const vec \&val)\label{classepdf_113c76c61d20e3f2a24ba322a73dfc51} |
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| 49 | |
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| 50 | \begin{CompactList}\small\item\em Compute log-probability of argument {\tt val}. \item\end{CompactList}\end{CompactItemize} |
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| 51 | \subsection*{Protected Attributes} |
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| 52 | \begin{CompactItemize} |
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| 53 | \item |
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| 54 | int {\bf n}\label{classeEmp_8c33034de0e35f03f8bb85d3d67438fd} |
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| 55 | |
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| 56 | \begin{CompactList}\small\item\em Number of particles. \item\end{CompactList}\item |
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| 57 | vec \textbf{w}\label{classeEmp_ae78d144404ddba843c93b171b215de8} |
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| 58 | |
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| 59 | \item |
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| 60 | Array$<$ vec $>$ \textbf{samples}\label{classeEmp_a4d6f4bbd6a6824fc39f14676701279a} |
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| 61 | |
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| 62 | \item |
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| 63 | {\bf RV} \textbf{rv}\label{classepdf_74da992e3f5d598da8850b646b79b9d9} |
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| 64 | |
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| 65 | \end{CompactItemize} |
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| 66 | |
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| 67 | |
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| 68 | \subsection{Detailed Description} |
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| 69 | Weighted empirical density. |
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| 70 | |
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| 71 | Used e.g. in particle filters. |
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| 72 | |
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| 73 | \subsection{Member Function Documentation} |
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| 74 | \index{eEmp@{eEmp}!sample@{sample}} |
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| 75 | \index{sample@{sample}!eEmp@{eEmp}} |
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| 76 | \subsubsection{\setlength{\rightskip}{0pt plus 5cm}vec eEmp::sample ()\hspace{0.3cm}{\tt [inline, virtual]}}\label{classeEmp_c9b44099a400579b88aff9f5afaf9c13} |
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| 77 | |
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| 78 | |
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| 79 | Returns the required moment of the \doxyref{epdf}{p.}{classepdf}. |
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| 80 | |
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| 81 | Returns a sample from the density, $x \sim epdf(rv)$ |
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| 82 | |
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| 83 | Implements {\bf epdf} \doxyref{}{p.}{classepdf_7f74d871d50b9ff360f1b3879092a9fa}. |
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| 84 | |
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| 85 | The documentation for this class was generated from the following files:\begin{CompactItemize} |
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| 86 | \item |
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| 87 | work/mixpp/bdm/stat/{\bf libEF.h}\item |
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| 88 | work/mixpp/bdm/stat/libEF.cpp\end{CompactItemize} |
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