root/doc/latex/classbdm_1_1MPF.tex @ 270

\hypertarget{classbdm_1_1MPF}{
\section{bdm::MPF$<$ BM\_\-T $>$ Class Template Reference}
\label{classbdm_1_1MPF}\index{bdm::MPF@{bdm::MPF}}
}
{\tt \#include $<$libPF.h$>$}

Inheritance diagram for bdm::MPF$<$ BM\_\-T $>$:\nopagebreak
\begin{figure}[H]
\begin{center}
\leavevmode
\includegraphics[width=77pt]{classbdm_1_1MPF__inherit__graph}
\end{center}
\end{figure}


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

Marginalized Particle filter. 

Trivial version: proposal = parameter evolution, observation model is not used. (it is assumed to be part of \hyperlink{classbdm_1_1BM}{BM}). \subsection*{Public Member Functions}
\begin{CompactItemize}
\item 
\hypertarget{classbdm_1_1MPF_e2a00c2399599c3613ab632fc36a1f79}{
\hyperlink{classbdm_1_1MPF_e2a00c2399599c3613ab632fc36a1f79}{MPF} (const \hyperlink{classbdm_1_1RV}{RV} \&rvlin, const \hyperlink{classbdm_1_1RV}{RV} \&rvpf, \hyperlink{classbdm_1_1mpdf}{mpdf} \&par0, \hyperlink{classbdm_1_1mpdf}{mpdf} \&obs0, int \hyperlink{classbdm_1_1PF_eeafaf9b8ad75fe62ee9fd6369e3f7fe}{n}, const BM\_\-T \&BMcond0)}
\label{classbdm_1_1MPF_e2a00c2399599c3613ab632fc36a1f79}

\begin{CompactList}\small\item\em Default constructor. \item\end{CompactList}\item 
void \hyperlink{classbdm_1_1MPF_286d040770d08bd7ff416cea617b1b14}{bayes} (const vec \&dt)
\begin{CompactList}\small\item\em Incremental Bayes rule. \item\end{CompactList}\item 
\hypertarget{classbdm_1_1MPF_2da4cbf7645da52ad5630ada411e3f9f}{
const \hyperlink{classbdm_1_1epdf}{epdf} \& \textbf{\_\-epdf} () const }
\label{classbdm_1_1MPF_2da4cbf7645da52ad5630ada411e3f9f}

\item 
\hypertarget{classbdm_1_1MPF_1401874aa88a7a3f2593070646779af2}{
const \hyperlink{classbdm_1_1epdf}{epdf} $\ast$ \textbf{\_\-e} () const }
\label{classbdm_1_1MPF_1401874aa88a7a3f2593070646779af2}

\item 
\hypertarget{classbdm_1_1MPF_dcecdaf2acbbee51acf3018a70989a7e}{
void \hyperlink{classbdm_1_1MPF_dcecdaf2acbbee51acf3018a70989a7e}{set\_\-est} (const \hyperlink{classbdm_1_1epdf}{epdf} \&epdf0)}
\label{classbdm_1_1MPF_dcecdaf2acbbee51acf3018a70989a7e}

\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{classbdm_1_1MPF_82b5a34d9ed0e78452f98d2ecbf1e93c}{
\hyperlink{classbdm_1_1BM}{BM} $\ast$ \hyperlink{classbdm_1_1MPF_82b5a34d9ed0e78452f98d2ecbf1e93c}{\_\-BM} (int i)}
\label{classbdm_1_1MPF_82b5a34d9ed0e78452f98d2ecbf1e93c}

\begin{CompactList}\small\item\em Access function. \item\end{CompactList}\item 
\hypertarget{classbdm_1_1PF_78a9f6809827be1d9bfe215d03b1c6ed}{
vec $\ast$ \hyperlink{classbdm_1_1PF_78a9f6809827be1d9bfe215d03b1c6ed}{\_\-\_\-w} ()}
\label{classbdm_1_1PF_78a9f6809827be1d9bfe215d03b1c6ed}

\begin{CompactList}\small\item\em access function \item\end{CompactList}\end{CompactItemize}
\begin{Indent}{\bf Constructors}\par
\begin{CompactItemize}
\item 
virtual \hyperlink{classbdm_1_1BM}{BM} $\ast$ \hyperlink{classbdm_1_1BM_c0f027ff91d8459937c6f60ff8e553ff}{\_\-copy\_\-} ()
\end{CompactItemize}
\end{Indent}
\begin{Indent}{\bf Mathematical operations}\par
\begin{CompactItemize}
\item 
\hypertarget{classbdm_1_1BM_1dee3fddaf021e62d925289660a707dc}{
virtual void \hyperlink{classbdm_1_1BM_1dee3fddaf021e62d925289660a707dc}{bayesB} (const mat \&Dt)}
\label{classbdm_1_1BM_1dee3fddaf021e62d925289660a707dc}

\begin{CompactList}\small\item\em Batch Bayes rule (columns of Dt are observations). \item\end{CompactList}\item 
virtual double \hyperlink{classbdm_1_1BM_50257e0c1e5b5c73153ea6e716ad8ae0}{logpred} (const vec \&dt) const 
\item 
\hypertarget{classbdm_1_1BM_0e8ebe61fb14990abe1254bd3dda5fae}{
vec \hyperlink{classbdm_1_1BM_0e8ebe61fb14990abe1254bd3dda5fae}{logpred\_\-m} (const mat \&dt) const }
\label{classbdm_1_1BM_0e8ebe61fb14990abe1254bd3dda5fae}

\begin{CompactList}\small\item\em Matrix version of logpred. \item\end{CompactList}\item 
\hypertarget{classbdm_1_1BM_688d7a2aced1e06aa1c468d73a9e5eba}{
virtual \hyperlink{classbdm_1_1epdf}{epdf} $\ast$ \hyperlink{classbdm_1_1BM_688d7a2aced1e06aa1c468d73a9e5eba}{epredictor} () const }
\label{classbdm_1_1BM_688d7a2aced1e06aa1c468d73a9e5eba}

\begin{CompactList}\small\item\em Constructs a predictive density $ f(d_{t+1} |d_{t}, \ldots d_{0}) $. \item\end{CompactList}\item 
\hypertarget{classbdm_1_1BM_598b25e3f3d96a5bc00a5faeb5b3c912}{
virtual \hyperlink{classbdm_1_1mpdf}{mpdf} $\ast$ \hyperlink{classbdm_1_1BM_598b25e3f3d96a5bc00a5faeb5b3c912}{predictor} () const }
\label{classbdm_1_1BM_598b25e3f3d96a5bc00a5faeb5b3c912}

\begin{CompactList}\small\item\em Constructs a conditional density 1-step ahead predictor. \item\end{CompactList}\end{CompactItemize}
\end{Indent}
\begin{Indent}{\bf Access to attributes}\par
\begin{CompactItemize}
\item 
\hypertarget{classbdm_1_1BM_ff2d8755ba0b3def927d31305c03b09c}{
const \hyperlink{classbdm_1_1RV}{RV} \& \textbf{\_\-drv} () const }
\label{classbdm_1_1BM_ff2d8755ba0b3def927d31305c03b09c}

\item 
\hypertarget{classbdm_1_1BM_f135ae6dce7e9f30c9f88229c7930b96}{
void \textbf{set\_\-drv} (const \hyperlink{classbdm_1_1RV}{RV} \&rv)}
\label{classbdm_1_1BM_f135ae6dce7e9f30c9f88229c7930b96}

\item 
\hypertarget{classbdm_1_1BM_5be65d37dedfe33a3671e7065f523a70}{
double \textbf{\_\-ll} () const }
\label{classbdm_1_1BM_5be65d37dedfe33a3671e7065f523a70}

\item 
\hypertarget{classbdm_1_1BM_236b3abbcc93594fc97cd86d82c1a83f}{
void \textbf{set\_\-evalll} (bool evl0)}
\label{classbdm_1_1BM_236b3abbcc93594fc97cd86d82c1a83f}

\end{CompactItemize}
\end{Indent}
\subsection*{Protected Attributes}
\begin{CompactItemize}
\item 
\hypertarget{classbdm_1_1PF_eeafaf9b8ad75fe62ee9fd6369e3f7fe}{
int \hyperlink{classbdm_1_1PF_eeafaf9b8ad75fe62ee9fd6369e3f7fe}{n}}
\label{classbdm_1_1PF_eeafaf9b8ad75fe62ee9fd6369e3f7fe}

\begin{CompactList}\small\item\em number of particles; \item\end{CompactList}\item 
\hypertarget{classbdm_1_1PF_dc049265b9086cad7071f98d00a2b9af}{
\hyperlink{classbdm_1_1eEmp}{eEmp} \hyperlink{classbdm_1_1PF_dc049265b9086cad7071f98d00a2b9af}{est}}
\label{classbdm_1_1PF_dc049265b9086cad7071f98d00a2b9af}

\begin{CompactList}\small\item\em posterior density \item\end{CompactList}\item 
\hypertarget{classbdm_1_1PF_f5149d5522d1095d39240c4c607f61a3}{
vec \& \hyperlink{classbdm_1_1PF_f5149d5522d1095d39240c4c607f61a3}{\_\-w}}
\label{classbdm_1_1PF_f5149d5522d1095d39240c4c607f61a3}

\begin{CompactList}\small\item\em pointer into {\tt \hyperlink{classbdm_1_1eEmp}{eEmp}} \item\end{CompactList}\item 
\hypertarget{classbdm_1_1PF_914bd66025692c4018dbd482cb3c47c1}{
Array$<$ vec $>$ \& \hyperlink{classbdm_1_1PF_914bd66025692c4018dbd482cb3c47c1}{\_\-samples}}
\label{classbdm_1_1PF_914bd66025692c4018dbd482cb3c47c1}

\begin{CompactList}\small\item\em pointer into {\tt \hyperlink{classbdm_1_1eEmp}{eEmp}} \item\end{CompactList}\item 
\hypertarget{classbdm_1_1PF_cf3a1b2a407012e47ac878e3aa2fbf34}{
\hyperlink{classbdm_1_1mpdf}{mpdf} \& \hyperlink{classbdm_1_1PF_cf3a1b2a407012e47ac878e3aa2fbf34}{par}}
\label{classbdm_1_1PF_cf3a1b2a407012e47ac878e3aa2fbf34}

\begin{CompactList}\small\item\em Parameter evolution model. \item\end{CompactList}\item 
\hypertarget{classbdm_1_1PF_c58b8fa634272c3f48845a9020ba55aa}{
\hyperlink{classbdm_1_1mpdf}{mpdf} \& \hyperlink{classbdm_1_1PF_c58b8fa634272c3f48845a9020ba55aa}{obs}}
\label{classbdm_1_1PF_c58b8fa634272c3f48845a9020ba55aa}

\begin{CompactList}\small\item\em Observation model. \item\end{CompactList}\item 
\hypertarget{classbdm_1_1BM_c400357e37d27a4834b2b1d9211009ed}{
\hyperlink{classbdm_1_1RV}{RV} \hyperlink{classbdm_1_1BM_c400357e37d27a4834b2b1d9211009ed}{drv}}
\label{classbdm_1_1BM_c400357e37d27a4834b2b1d9211009ed}

\begin{CompactList}\small\item\em Random variable of the data (optional). \item\end{CompactList}\item 
\hypertarget{classbdm_1_1BM_4064b6559d962633e4372b12f4cd204a}{
double \hyperlink{classbdm_1_1BM_4064b6559d962633e4372b12f4cd204a}{ll}}
\label{classbdm_1_1BM_4064b6559d962633e4372b12f4cd204a}

\begin{CompactList}\small\item\em Logarithm of marginalized data likelihood. \item\end{CompactList}\item 
\hypertarget{classbdm_1_1BM_faff0ad12556fe7dc0e2807d4fd938ee}{
bool \hyperlink{classbdm_1_1BM_faff0ad12556fe7dc0e2807d4fd938ee}{evalll}}
\label{classbdm_1_1BM_faff0ad12556fe7dc0e2807d4fd938ee}

\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{classbdm_1_1eEmp}{eEmp} with external components \item\end{CompactList}\end{CompactItemize}


\subsection{Member Function Documentation}
\hypertarget{classbdm_1_1MPF_286d040770d08bd7ff416cea617b1b14}{
\index{bdm::MPF@{bdm::MPF}!bayes@{bayes}}
\index{bayes@{bayes}!bdm::MPF@{bdm::MPF}}
\subsubsection[bayes]{\setlength{\rightskip}{0pt plus 5cm}template$<$class BM\_\-T$>$ void {\bf bdm::MPF}$<$ BM\_\-T $>$::bayes (const vec \& {\em dt})\hspace{0.3cm}{\tt  \mbox{[}inline, virtual\mbox{]}}}}
\label{classbdm_1_1MPF_286d040770d08bd7ff416cea617b1b14}


Incremental Bayes rule. 

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


Reimplemented from \hyperlink{classbdm_1_1PF_638946eea22d4964bf9350286bb4efd8}{bdm::PF}.

References bdm::mpdf::\_\-e(), bdm::PF::\_\-samples, bdm::PF::\_\-w, bdm::PF::est, bdm::epdf::evallog(), bdm::PF::n, bdm::PF::par, bdm::eEmp::resample(), and bdm::mpdf::samplecond().\hypertarget{classbdm_1_1BM_c0f027ff91d8459937c6f60ff8e553ff}{
\index{bdm::MPF@{bdm::MPF}!\_\-copy\_\-@{\_\-copy\_\-}}
\index{\_\-copy\_\-@{\_\-copy\_\-}!bdm::MPF@{bdm::MPF}}
\subsubsection[\_\-copy\_\-]{\setlength{\rightskip}{0pt plus 5cm}virtual {\bf BM}$\ast$ bdm::BM::\_\-copy\_\- ()\hspace{0.3cm}{\tt  \mbox{[}inline, virtual, inherited\mbox{]}}}}
\label{classbdm_1_1BM_c0f027ff91d8459937c6f60ff8e553ff}


Copy function required in vectors, Arrays of \hyperlink{classbdm_1_1BM}{BM} etc. Have to be DELETED manually! Prototype: 

\begin{Code}\begin{verbatim} BM* _copy_(){return new BM(*this);} 
\end{verbatim}
\end{Code}

 

Reimplemented in \hyperlink{classbdm_1_1ARX_60c40b5c6abc4c7e464b4ccae64a5a61}{bdm::ARX}.\hypertarget{classbdm_1_1BM_50257e0c1e5b5c73153ea6e716ad8ae0}{
\index{bdm::MPF@{bdm::MPF}!logpred@{logpred}}
\index{logpred@{logpred}!bdm::MPF@{bdm::MPF}}
\subsubsection[logpred]{\setlength{\rightskip}{0pt plus 5cm}virtual double bdm::BM::logpred (const vec \& {\em dt}) const\hspace{0.3cm}{\tt  \mbox{[}inline, virtual, inherited\mbox{]}}}}
\label{classbdm_1_1BM_50257e0c1e5b5c73153ea6e716ad8ae0}


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

Reimplemented in \hyperlink{classbdm_1_1ARX_080a7e531e3aa06694112863b15bc6a4}{bdm::ARX}, \hyperlink{classbdm_1_1MixEF_da724da464a75e07521941e430929efa}{bdm::MixEF}, and \hyperlink{classbdm_1_1multiBM_e157b607c1e3fa91d42aeea44458e2bf}{bdm::multiBM}.

Referenced by bdm::BM::logpred\_\-m().

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