\hypertarget{classMPF}{
\section{MPF$<$ BM\_\-T $>$ Class Template Reference}
\label{classMPF}\index{MPF@{MPF}}
}
Marginalized Particle filter.  


{\tt \#include $<$libPF.h$>$}

Inheritance diagram for MPF$<$ BM\_\-T $>$:\nopagebreak
\begin{figure}[H]
\begin{center}
\leavevmode
\includegraphics[width=62pt]{classMPF__inherit__graph}
\end{center}
\end{figure}
Collaboration diagram for MPF$<$ BM\_\-T $>$:\nopagebreak
\begin{figure}[H]
\begin{center}
\leavevmode
\includegraphics[width=159pt]{classMPF__coll__graph}
\end{center}
\end{figure}
\subsection*{Public Member Functions}
\begin{CompactItemize}
\item 
\hypertarget{classMPF_fc5e11e11eec3195e3c6503937bf02bd}{
\hyperlink{classMPF_fc5e11e11eec3195e3c6503937bf02bd}{MPF} (const \hyperlink{classRV}{RV} \&rvlin, const \hyperlink{classRV}{RV} \&rvpf, \hyperlink{classmpdf}{mpdf} \&par0, \hyperlink{classmpdf}{mpdf} \&obs0, int \hyperlink{classPF_2c2f44ed7a4eaa42e07bdb58d503f280}{n}, const BM\_\-T \&BMcond0)}
\label{classMPF_fc5e11e11eec3195e3c6503937bf02bd}

\begin{CompactList}\small\item\em Default constructor. \item\end{CompactList}\item 
void \hyperlink{classMPF_55daf8e4b6553dd9f47c692de7931623}{bayes} (const vec \&dt)
\begin{CompactList}\small\item\em Incremental Bayes rule. \item\end{CompactList}\item 
\hypertarget{classMPF_992e01bb8f06c814cda036796e4a55ae}{
const \hyperlink{classepdf}{epdf} \& \hyperlink{classMPF_992e01bb8f06c814cda036796e4a55ae}{\_\-epdf} () const }
\label{classMPF_992e01bb8f06c814cda036796e4a55ae}

\begin{CompactList}\small\item\em Returns a pointer to the \hyperlink{classepdf}{epdf} representing posterior density on parameters. Use with care! \item\end{CompactList}\item 
\hypertarget{classMPF_7c66e1c1c0e45fc4ae765133cb3a1553}{
void \hyperlink{classMPF_7c66e1c1c0e45fc4ae765133cb3a1553}{set\_\-est} (const \hyperlink{classepdf}{epdf} \&epdf0)}
\label{classMPF_7c66e1c1c0e45fc4ae765133cb3a1553}

\begin{CompactList}\small\item\em Set postrior of {\tt rvc} to samples from epdf0. Statistics of Bms are not re-computed! Use only for initialization! \item\end{CompactList}\item 
\hypertarget{classBM_0186270f75189677f390fe088a9947e9}{
virtual void \hyperlink{classBM_0186270f75189677f390fe088a9947e9}{bayesB} (const mat \&Dt)}
\label{classBM_0186270f75189677f390fe088a9947e9}

\begin{CompactList}\small\item\em Batch Bayes rule (columns of Dt are observations). \item\end{CompactList}\item 
virtual double \hyperlink{classBM_8a8ce6df431689964c41cc6c849cfd06}{logpred} (const vec \&dt) const 
\item 
\hypertarget{classBM_cd0660f2a1a344b56ac39802708ff165}{
vec \hyperlink{classBM_cd0660f2a1a344b56ac39802708ff165}{logpred\_\-m} (const mat \&dt) const }
\label{classBM_cd0660f2a1a344b56ac39802708ff165}

\begin{CompactList}\small\item\em Matrix version of logpred. \item\end{CompactList}\item 
\hypertarget{classBM_a627c5a79cc6f5221b7e09675525e032}{
virtual \hyperlink{classepdf}{epdf} $\ast$ \hyperlink{classBM_a627c5a79cc6f5221b7e09675525e032}{predictor} (const \hyperlink{classRV}{RV} \&\hyperlink{classBM_af00f0612fabe66241dd507188cdbf88}{rv})}
\label{classBM_a627c5a79cc6f5221b7e09675525e032}

\begin{CompactList}\small\item\em Constructs a predictive density (marginal density on data). \item\end{CompactList}\item 
\hypertarget{classBM_126bd2595c48e311fc2a7ab72876092a}{
const \hyperlink{classRV}{RV} \& \hyperlink{classBM_126bd2595c48e311fc2a7ab72876092a}{\_\-rv} () const }
\label{classBM_126bd2595c48e311fc2a7ab72876092a}

\begin{CompactList}\small\item\em access function \item\end{CompactList}\item 
\hypertarget{classBM_87f4a547d2c29180be88175e5eab9c88}{
double \hyperlink{classBM_87f4a547d2c29180be88175e5eab9c88}{\_\-ll} () const }
\label{classBM_87f4a547d2c29180be88175e5eab9c88}

\begin{CompactList}\small\item\em access function \item\end{CompactList}\item 
\hypertarget{classBM_1ffa9f23669aabecc3760c06c6987522}{
void \hyperlink{classBM_1ffa9f23669aabecc3760c06c6987522}{set\_\-evalll} (bool evl0)}
\label{classBM_1ffa9f23669aabecc3760c06c6987522}

\begin{CompactList}\small\item\em access function \item\end{CompactList}\item 
virtual \hyperlink{classBM}{BM} $\ast$ \hyperlink{classBM_eb58c81d6a7b75b05fc6f276eed78887}{\_\-copy\_\-} (bool changerv=false)
\end{CompactItemize}
\subsection*{Public Attributes}
\begin{CompactItemize}
\item 
\hypertarget{classMPF_65b869f3cde2e8d3cfcc2752d14d1ca6}{
double \textbf{SSAT}}
\label{classMPF_65b869f3cde2e8d3cfcc2752d14d1ca6}

\end{CompactItemize}
\subsection*{Protected Attributes}
\begin{CompactItemize}
\item 
\hypertarget{classPF_2c2f44ed7a4eaa42e07bdb58d503f280}{
int \hyperlink{classPF_2c2f44ed7a4eaa42e07bdb58d503f280}{n}}
\label{classPF_2c2f44ed7a4eaa42e07bdb58d503f280}

\begin{CompactList}\small\item\em number of particles; \item\end{CompactList}\item 
\hypertarget{classPF_1a0a09e309da997f63ae8e30d1e9806b}{
\hyperlink{classeEmp}{eEmp} \hyperlink{classPF_1a0a09e309da997f63ae8e30d1e9806b}{est}}
\label{classPF_1a0a09e309da997f63ae8e30d1e9806b}

\begin{CompactList}\small\item\em posterior density \item\end{CompactList}\item 
\hypertarget{classPF_5c87aba508df321ff26536ced64dbb3a}{
vec \& \hyperlink{classPF_5c87aba508df321ff26536ced64dbb3a}{\_\-w}}
\label{classPF_5c87aba508df321ff26536ced64dbb3a}

\begin{CompactList}\small\item\em pointer into {\tt \hyperlink{classeEmp}{eEmp}} \item\end{CompactList}\item 
\hypertarget{classPF_cf7dad75e31215780a746c30e71ad9c5}{
Array$<$ vec $>$ \& \hyperlink{classPF_cf7dad75e31215780a746c30e71ad9c5}{\_\-samples}}
\label{classPF_cf7dad75e31215780a746c30e71ad9c5}

\begin{CompactList}\small\item\em pointer into {\tt \hyperlink{classeEmp}{eEmp}} \item\end{CompactList}\item 
\hypertarget{classPF_d92ac103f88f8c21e197e90af5695a09}{
\hyperlink{classmpdf}{mpdf} \& \hyperlink{classPF_d92ac103f88f8c21e197e90af5695a09}{par}}
\label{classPF_d92ac103f88f8c21e197e90af5695a09}

\begin{CompactList}\small\item\em Parameter evolution model. \item\end{CompactList}\item 
\hypertarget{classPF_dd0a687a4515333d6809147335854e77}{
\hyperlink{classmpdf}{mpdf} \& \hyperlink{classPF_dd0a687a4515333d6809147335854e77}{obs}}
\label{classPF_dd0a687a4515333d6809147335854e77}

\begin{CompactList}\small\item\em Observation model. \item\end{CompactList}\item 
\hypertarget{classBM_af00f0612fabe66241dd507188cdbf88}{
\hyperlink{classRV}{RV} \hyperlink{classBM_af00f0612fabe66241dd507188cdbf88}{rv}}
\label{classBM_af00f0612fabe66241dd507188cdbf88}

\begin{CompactList}\small\item\em Random variable of the posterior. \item\end{CompactList}\item 
\hypertarget{classBM_5623fef6572a08c2b53b8c87b82dc979}{
double \hyperlink{classBM_5623fef6572a08c2b53b8c87b82dc979}{ll}}
\label{classBM_5623fef6572a08c2b53b8c87b82dc979}

\begin{CompactList}\small\item\em Logarithm of marginalized data likelihood. \item\end{CompactList}\item 
\hypertarget{classBM_bf6fb59b30141074f8ee1e2f43d03129}{
bool \hyperlink{classBM_bf6fb59b30141074f8ee1e2f43d03129}{evalll}}
\label{classBM_bf6fb59b30141074f8ee1e2f43d03129}

\begin{CompactList}\small\item\em If true, the filter will compute likelihood of the data record and store it in {\tt ll} . Set to false if you want to save computational time. \item\end{CompactList}\end{CompactItemize}
\subsection*{Classes}
\begin{CompactItemize}
\item 
class \textbf{mpfepdf}
\begin{CompactList}\small\item\em internal class for MPDF providing composition of \hyperlink{classeEmp}{eEmp} with external components \item\end{CompactList}\end{CompactItemize}


\subsection{Detailed Description}
\subsubsection*{template$<$class BM\_\-T$>$ class MPF$<$ BM\_\-T $>$}

Marginalized Particle filter. 

Trivial version: proposal = parameter evolution, observation model is not used. (it is assumed to be part of \hyperlink{classBM}{BM}). 

\subsection{Member Function Documentation}
\hypertarget{classMPF_55daf8e4b6553dd9f47c692de7931623}{
\index{MPF@{MPF}!bayes@{bayes}}
\index{bayes@{bayes}!MPF@{MPF}}
\subsubsection[bayes]{\setlength{\rightskip}{0pt plus 5cm}template$<$class BM\_\-T$>$ void {\bf MPF}$<$ BM\_\-T $>$::bayes (const vec \& {\em dt})\hspace{0.3cm}{\tt  \mbox{[}inline, virtual\mbox{]}}}}
\label{classMPF_55daf8e4b6553dd9f47c692de7931623}


Incremental Bayes rule. 

\begin{Desc}
\item[Parameters:]
\begin{description}
\item[{\em dt}]vector of input data \end{description}
\end{Desc}


Reimplemented from \hyperlink{classPF_64f636bbd63bea9efd778214e6b631d3}{PF}.

References PF::\_\-samples, PF::\_\-w, PF::est, PF::n, PF::par, eEmp::resample(), and mpdf::samplecond().\hypertarget{classBM_8a8ce6df431689964c41cc6c849cfd06}{
\index{MPF@{MPF}!logpred@{logpred}}
\index{logpred@{logpred}!MPF@{MPF}}
\subsubsection[logpred]{\setlength{\rightskip}{0pt plus 5cm}virtual double BM::logpred (const vec \& {\em dt}) const\hspace{0.3cm}{\tt  \mbox{[}inline, virtual, inherited\mbox{]}}}}
\label{classBM_8a8ce6df431689964c41cc6c849cfd06}


Evaluates predictive log-likelihood of the given data record I.e. marginal likelihood of the data with the posterior integrated out. 

Reimplemented in \hyperlink{classARX_e7f9e7823aec9bf7ddc3b42d9b3304c4}{ARX}, \hyperlink{classMixEF_424ca64f36d4e41de7a7e7ae921d35ea}{MixEF}, and \hyperlink{classmultiBM_13e26a61757278981fd8cac9a7ef91eb}{multiBM}.

Referenced by BM::logpred\_\-m().\hypertarget{classBM_eb58c81d6a7b75b05fc6f276eed78887}{
\index{MPF@{MPF}!\_\-copy\_\-@{\_\-copy\_\-}}
\index{\_\-copy\_\-@{\_\-copy\_\-}!MPF@{MPF}}
\subsubsection[\_\-copy\_\-]{\setlength{\rightskip}{0pt plus 5cm}virtual {\bf BM}$\ast$ BM::\_\-copy\_\- (bool {\em changerv} = {\tt false})\hspace{0.3cm}{\tt  \mbox{[}inline, virtual, inherited\mbox{]}}}}
\label{classBM_eb58c81d6a7b75b05fc6f276eed78887}


Copy function required in vectors, Arrays of \hyperlink{classBM}{BM} etc. Have to be DELETED manually! Prototype: BM$\ast$ \hyperlink{classBM_eb58c81d6a7b75b05fc6f276eed78887}{\_\-copy\_\-()}\{\hyperlink{classBM}{BM} Tmp$\ast$=new Tmp(this$\ast$); return Tmp; \} 

Reimplemented in \hyperlink{classARX_5de61fbd4f97fa3216760b1f733f5af0}{ARX}.

Referenced by MixEF::init().

The documentation for this class was generated from the following file:\begin{CompactItemize}
\item 
work/git/mixpp/bdm/estim/\hyperlink{libPF_8h}{libPF.h}\end{CompactItemize}
