[8] | 1 | \section{TrivialPF Class Reference} |
---|
| 2 | \label{classTrivialPF}\index{TrivialPF@{TrivialPF}} |
---|
| 3 | Trivial particle filter with proposal density that is not conditioned on the data. |
---|
| 4 | |
---|
| 5 | |
---|
| 6 | {\tt \#include $<$libPF.h$>$} |
---|
| 7 | |
---|
[19] | 8 | Inheritance diagram for TrivialPF:\nopagebreak |
---|
| 9 | \begin{figure}[H] |
---|
[8] | 10 | \begin{center} |
---|
| 11 | \leavevmode |
---|
[19] | 12 | \includegraphics[width=49pt]{classTrivialPF__inherit__graph} |
---|
[8] | 13 | \end{center} |
---|
| 14 | \end{figure} |
---|
[19] | 15 | Collaboration diagram for TrivialPF:\nopagebreak |
---|
| 16 | \begin{figure}[H] |
---|
| 17 | \begin{center} |
---|
| 18 | \leavevmode |
---|
| 19 | \includegraphics[width=67pt]{classTrivialPF__coll__graph} |
---|
| 20 | \end{center} |
---|
| 21 | \end{figure} |
---|
[8] | 22 | \subsection*{Public Member Functions} |
---|
| 23 | \begin{CompactItemize} |
---|
| 24 | \item |
---|
| 25 | \textbf{TrivialPF} ({\bf mpdf} \&par, {\bf mpdf} \&obs, {\bf mpdf} \&prop, int n0)\label{classTrivialPF_e6d9e3506da221a10a517bd5712b5a84} |
---|
| 26 | |
---|
| 27 | \item |
---|
| 28 | \textbf{TrivialPF} ({\bf mpdf} \&par, {\bf mpdf} \&obs, int n0)\label{classTrivialPF_59fc4c55a2d5fbb6bc9a17a9dd9a2e13} |
---|
| 29 | |
---|
| 30 | \item |
---|
| 31 | void {\bf bayes} (const vec \&dt, bool evalll) |
---|
| 32 | \begin{CompactList}\small\item\em Incremental Bayes rule. \item\end{CompactList}\end{CompactItemize} |
---|
| 33 | |
---|
| 34 | |
---|
| 35 | \subsection{Detailed Description} |
---|
| 36 | Trivial particle filter with proposal density that is not conditioned on the data. |
---|
| 37 | |
---|
| 38 | \subsection{Member Function Documentation} |
---|
| 39 | \index{TrivialPF@{TrivialPF}!bayes@{bayes}} |
---|
| 40 | \index{bayes@{bayes}!TrivialPF@{TrivialPF}} |
---|
| 41 | \subsubsection{\setlength{\rightskip}{0pt plus 5cm}void TrivialPF::bayes (const vec \& {\em dt}, bool {\em evall})\hspace{0.3cm}{\tt [virtual]}}\label{classTrivialPF_77a92bf054d763f806d27fc37a058389} |
---|
| 42 | |
---|
| 43 | |
---|
| 44 | Incremental Bayes rule. |
---|
| 45 | |
---|
| 46 | \begin{Desc} |
---|
| 47 | \item[Parameters:] |
---|
| 48 | \begin{description} |
---|
| 49 | \item[{\em dt}]vector of input data \item[{\em evall}]If true, the filter will compute likelihood of the data record and store it in {\tt ll} \end{description} |
---|
| 50 | \end{Desc} |
---|
| 51 | |
---|
| 52 | |
---|
[19] | 53 | Reimplemented from {\bf PF} \doxyref{}{p.}{classPF_eb06bd7d4325f22f54233967295793b9}. |
---|
[8] | 54 | |
---|
| 55 | The documentation for this class was generated from the following files:\begin{CompactItemize} |
---|
| 56 | \item |
---|
[19] | 57 | work/mixpp/bdm/estim/{\bf libPF.h}\item |
---|
| 58 | work/mixpp/bdm/estim/libPF.cpp\end{CompactItemize} |
---|