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[261]1\hypertarget{classbdm_1_1MPF}{
2\section{bdm::MPF$<$ BM\_\-T $>$ Class Template Reference}
3\label{classbdm_1_1MPF}\index{bdm::MPF@{bdm::MPF}}
4}
5Marginalized Particle filter. 
6
7
8{\tt \#include $<$libPF.h$>$}
9
10Inheritance diagram for bdm::MPF$<$ BM\_\-T $>$:\nopagebreak
11\begin{figure}[H]
12\begin{center}
13\leavevmode
14\includegraphics[width=77pt]{classbdm_1_1MPF__inherit__graph}
15\end{center}
16\end{figure}
17Collaboration diagram for bdm::MPF$<$ BM\_\-T $>$:\nopagebreak
18\begin{figure}[H]
19\begin{center}
20\leavevmode
21\includegraphics[height=400pt]{classbdm_1_1MPF__coll__graph}
22\end{center}
23\end{figure}
24\subsection*{Public Member Functions}
25\begin{CompactItemize}
26\item 
27\hypertarget{classbdm_1_1MPF_e2a00c2399599c3613ab632fc36a1f79}{
28\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)}
29\label{classbdm_1_1MPF_e2a00c2399599c3613ab632fc36a1f79}
30
31\begin{CompactList}\small\item\em Default constructor. \item\end{CompactList}\item 
32void \hyperlink{classbdm_1_1MPF_286d040770d08bd7ff416cea617b1b14}{bayes} (const vec \&dt)
33\begin{CompactList}\small\item\em Incremental Bayes rule. \item\end{CompactList}\item 
34\hypertarget{classbdm_1_1MPF_2da4cbf7645da52ad5630ada411e3f9f}{
35const \hyperlink{classbdm_1_1epdf}{epdf} \& \hyperlink{classbdm_1_1MPF_2da4cbf7645da52ad5630ada411e3f9f}{\_\-epdf} () const }
36\label{classbdm_1_1MPF_2da4cbf7645da52ad5630ada411e3f9f}
37
38\begin{CompactList}\small\item\em Returns a reference to the \hyperlink{classbdm_1_1epdf}{epdf} representing posterior density on parameters. \item\end{CompactList}\item 
39\hypertarget{classbdm_1_1MPF_1401874aa88a7a3f2593070646779af2}{
40const \hyperlink{classbdm_1_1epdf}{epdf} $\ast$ \hyperlink{classbdm_1_1MPF_1401874aa88a7a3f2593070646779af2}{\_\-e} () const }
41\label{classbdm_1_1MPF_1401874aa88a7a3f2593070646779af2}
42
43\begin{CompactList}\small\item\em Returns a pointer to the \hyperlink{classbdm_1_1epdf}{epdf} representing posterior density on parameters. Use with care! \item\end{CompactList}\item 
44\hypertarget{classbdm_1_1MPF_dcecdaf2acbbee51acf3018a70989a7e}{
45void \hyperlink{classbdm_1_1MPF_dcecdaf2acbbee51acf3018a70989a7e}{set\_\-est} (const \hyperlink{classbdm_1_1epdf}{epdf} \&epdf0)}
46\label{classbdm_1_1MPF_dcecdaf2acbbee51acf3018a70989a7e}
47
48\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 
49\hypertarget{classbdm_1_1MPF_82b5a34d9ed0e78452f98d2ecbf1e93c}{
50\hyperlink{classbdm_1_1BM}{BM} $\ast$ \hyperlink{classbdm_1_1MPF_82b5a34d9ed0e78452f98d2ecbf1e93c}{\_\-BM} (int i)}
51\label{classbdm_1_1MPF_82b5a34d9ed0e78452f98d2ecbf1e93c}
52
53\begin{CompactList}\small\item\em Access function. \item\end{CompactList}\item 
54\hypertarget{classbdm_1_1PF_78a9f6809827be1d9bfe215d03b1c6ed}{
55vec $\ast$ \hyperlink{classbdm_1_1PF_78a9f6809827be1d9bfe215d03b1c6ed}{\_\-\_\-w} ()}
56\label{classbdm_1_1PF_78a9f6809827be1d9bfe215d03b1c6ed}
57
58\begin{CompactList}\small\item\em access function \item\end{CompactList}\item 
59\hypertarget{classbdm_1_1BM_1dee3fddaf021e62d925289660a707dc}{
60virtual void \hyperlink{classbdm_1_1BM_1dee3fddaf021e62d925289660a707dc}{bayesB} (const mat \&Dt)}
61\label{classbdm_1_1BM_1dee3fddaf021e62d925289660a707dc}
62
63\begin{CompactList}\small\item\em Batch Bayes rule (columns of Dt are observations). \item\end{CompactList}\item 
64virtual double \hyperlink{classbdm_1_1BM_50257e0c1e5b5c73153ea6e716ad8ae0}{logpred} (const vec \&dt) const
65\item 
66\hypertarget{classbdm_1_1BM_0e8ebe61fb14990abe1254bd3dda5fae}{
67vec \hyperlink{classbdm_1_1BM_0e8ebe61fb14990abe1254bd3dda5fae}{logpred\_\-m} (const mat \&dt) const }
68\label{classbdm_1_1BM_0e8ebe61fb14990abe1254bd3dda5fae}
69
70\begin{CompactList}\small\item\em Matrix version of logpred. \item\end{CompactList}\item 
71\hypertarget{classbdm_1_1BM_710e7d69c0d8791fb41a7cd4683cca2c}{
72virtual \hyperlink{classbdm_1_1epdf}{epdf} $\ast$ \hyperlink{classbdm_1_1BM_710e7d69c0d8791fb41a7cd4683cca2c}{predictor} (const \hyperlink{classbdm_1_1RV}{RV} \&\hyperlink{classbdm_1_1BM_18d6db4af8ee42077741d9e3618153ca}{rv}) const }
73\label{classbdm_1_1BM_710e7d69c0d8791fb41a7cd4683cca2c}
74
75\begin{CompactList}\small\item\em Constructs a predictive density (marginal density on data). \item\end{CompactList}\item 
76\hypertarget{classbdm_1_1BM_40a3c891996391e3135518053a917793}{
77const \hyperlink{classbdm_1_1RV}{RV} \& \hyperlink{classbdm_1_1BM_40a3c891996391e3135518053a917793}{\_\-rv} () const }
78\label{classbdm_1_1BM_40a3c891996391e3135518053a917793}
79
80\begin{CompactList}\small\item\em access function \item\end{CompactList}\item 
81\hypertarget{classbdm_1_1BM_5be65d37dedfe33a3671e7065f523a70}{
82double \hyperlink{classbdm_1_1BM_5be65d37dedfe33a3671e7065f523a70}{\_\-ll} () const }
83\label{classbdm_1_1BM_5be65d37dedfe33a3671e7065f523a70}
84
85\begin{CompactList}\small\item\em access function \item\end{CompactList}\item 
86\hypertarget{classbdm_1_1BM_236b3abbcc93594fc97cd86d82c1a83f}{
87void \hyperlink{classbdm_1_1BM_236b3abbcc93594fc97cd86d82c1a83f}{set\_\-evalll} (bool evl0)}
88\label{classbdm_1_1BM_236b3abbcc93594fc97cd86d82c1a83f}
89
90\begin{CompactList}\small\item\em access function \item\end{CompactList}\item 
91virtual \hyperlink{classbdm_1_1BM}{BM} $\ast$ \hyperlink{classbdm_1_1BM_3efb3098172f1f67564a312fe732473e}{\_\-copy\_\-} (bool changerv=false)
92\end{CompactItemize}
93\subsection*{Protected Attributes}
94\begin{CompactItemize}
95\item 
96\hypertarget{classbdm_1_1PF_eeafaf9b8ad75fe62ee9fd6369e3f7fe}{
97int \hyperlink{classbdm_1_1PF_eeafaf9b8ad75fe62ee9fd6369e3f7fe}{n}}
98\label{classbdm_1_1PF_eeafaf9b8ad75fe62ee9fd6369e3f7fe}
99
100\begin{CompactList}\small\item\em number of particles; \item\end{CompactList}\item 
101\hypertarget{classbdm_1_1PF_dc049265b9086cad7071f98d00a2b9af}{
102\hyperlink{classbdm_1_1eEmp}{eEmp} \hyperlink{classbdm_1_1PF_dc049265b9086cad7071f98d00a2b9af}{est}}
103\label{classbdm_1_1PF_dc049265b9086cad7071f98d00a2b9af}
104
105\begin{CompactList}\small\item\em posterior density \item\end{CompactList}\item 
106\hypertarget{classbdm_1_1PF_f5149d5522d1095d39240c4c607f61a3}{
107vec \& \hyperlink{classbdm_1_1PF_f5149d5522d1095d39240c4c607f61a3}{\_\-w}}
108\label{classbdm_1_1PF_f5149d5522d1095d39240c4c607f61a3}
109
110\begin{CompactList}\small\item\em pointer into {\tt \hyperlink{classbdm_1_1eEmp}{eEmp}} \item\end{CompactList}\item 
111\hypertarget{classbdm_1_1PF_914bd66025692c4018dbd482cb3c47c1}{
112Array$<$ vec $>$ \& \hyperlink{classbdm_1_1PF_914bd66025692c4018dbd482cb3c47c1}{\_\-samples}}
113\label{classbdm_1_1PF_914bd66025692c4018dbd482cb3c47c1}
114
115\begin{CompactList}\small\item\em pointer into {\tt \hyperlink{classbdm_1_1eEmp}{eEmp}} \item\end{CompactList}\item 
116\hypertarget{classbdm_1_1PF_cf3a1b2a407012e47ac878e3aa2fbf34}{
117\hyperlink{classbdm_1_1mpdf}{mpdf} \& \hyperlink{classbdm_1_1PF_cf3a1b2a407012e47ac878e3aa2fbf34}{par}}
118\label{classbdm_1_1PF_cf3a1b2a407012e47ac878e3aa2fbf34}
119
120\begin{CompactList}\small\item\em Parameter evolution model. \item\end{CompactList}\item 
121\hypertarget{classbdm_1_1PF_c58b8fa634272c3f48845a9020ba55aa}{
122\hyperlink{classbdm_1_1mpdf}{mpdf} \& \hyperlink{classbdm_1_1PF_c58b8fa634272c3f48845a9020ba55aa}{obs}}
123\label{classbdm_1_1PF_c58b8fa634272c3f48845a9020ba55aa}
124
125\begin{CompactList}\small\item\em Observation model. \item\end{CompactList}\item 
126\hypertarget{classbdm_1_1BM_18d6db4af8ee42077741d9e3618153ca}{
127\hyperlink{classbdm_1_1RV}{RV} \hyperlink{classbdm_1_1BM_18d6db4af8ee42077741d9e3618153ca}{rv}}
128\label{classbdm_1_1BM_18d6db4af8ee42077741d9e3618153ca}
129
130\begin{CompactList}\small\item\em Random variable of the posterior. \item\end{CompactList}\item 
131\hypertarget{classbdm_1_1BM_4064b6559d962633e4372b12f4cd204a}{
132double \hyperlink{classbdm_1_1BM_4064b6559d962633e4372b12f4cd204a}{ll}}
133\label{classbdm_1_1BM_4064b6559d962633e4372b12f4cd204a}
134
135\begin{CompactList}\small\item\em Logarithm of marginalized data likelihood. \item\end{CompactList}\item 
136\hypertarget{classbdm_1_1BM_faff0ad12556fe7dc0e2807d4fd938ee}{
137bool \hyperlink{classbdm_1_1BM_faff0ad12556fe7dc0e2807d4fd938ee}{evalll}}
138\label{classbdm_1_1BM_faff0ad12556fe7dc0e2807d4fd938ee}
139
140\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}
141\subsection*{Classes}
142\begin{CompactItemize}
143\item 
144class \textbf{mpfepdf}
145\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}
146
147
148\subsection{Detailed Description}
149\subsubsection*{template$<$class BM\_\-T$>$ class bdm::MPF$<$ BM\_\-T $>$}
150
151Marginalized Particle filter.
152
153Trivial version: proposal = parameter evolution, observation model is not used. (it is assumed to be part of \hyperlink{classbdm_1_1BM}{BM}).
154
155\subsection{Member Function Documentation}
156\hypertarget{classbdm_1_1MPF_286d040770d08bd7ff416cea617b1b14}{
157\index{bdm::MPF@{bdm::MPF}!bayes@{bayes}}
158\index{bayes@{bayes}!bdm::MPF@{bdm::MPF}}
159\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{]}}}}
160\label{classbdm_1_1MPF_286d040770d08bd7ff416cea617b1b14}
161
162
163Incremental Bayes rule.
164
165\begin{Desc}
166\item[Parameters:]
167\begin{description}
168\item[{\em dt}]vector of input data \end{description}
169\end{Desc}
170
171
172Reimplemented from \hyperlink{classbdm_1_1PF_638946eea22d4964bf9350286bb4efd8}{bdm::PF}.
173
174References bdm::PF::\_\-samples, bdm::PF::\_\-w, bdm::PF::est, bdm::PF::n, bdm::PF::par, bdm::eEmp::resample(), and bdm::mpdf::samplecond().\hypertarget{classbdm_1_1BM_50257e0c1e5b5c73153ea6e716ad8ae0}{
175\index{bdm::MPF@{bdm::MPF}!logpred@{logpred}}
176\index{logpred@{logpred}!bdm::MPF@{bdm::MPF}}
177\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{]}}}}
178\label{classbdm_1_1BM_50257e0c1e5b5c73153ea6e716ad8ae0}
179
180
181Evaluates predictive log-likelihood of the given data record I.e. marginal likelihood of the data with the posterior integrated out.
182
183Reimplemented in \hyperlink{classbdm_1_1ARX_080a7e531e3aa06694112863b15bc6a4}{bdm::ARX}, \hyperlink{classbdm_1_1MixEF_da724da464a75e07521941e430929efa}{bdm::MixEF}, and \hyperlink{classbdm_1_1multiBM_e157b607c1e3fa91d42aeea44458e2bf}{bdm::multiBM}.
184
185Referenced by bdm::BM::logpred\_\-m().\hypertarget{classbdm_1_1BM_3efb3098172f1f67564a312fe732473e}{
186\index{bdm::MPF@{bdm::MPF}!\_\-copy\_\-@{\_\-copy\_\-}}
187\index{\_\-copy\_\-@{\_\-copy\_\-}!bdm::MPF@{bdm::MPF}}
188\subsubsection[\_\-copy\_\-]{\setlength{\rightskip}{0pt plus 5cm}virtual {\bf BM}$\ast$ bdm::BM::\_\-copy\_\- (bool {\em changerv} = {\tt false})\hspace{0.3cm}{\tt  \mbox{[}inline, virtual, inherited\mbox{]}}}}
189\label{classbdm_1_1BM_3efb3098172f1f67564a312fe732473e}
190
191
192Copy function required in vectors, Arrays of \hyperlink{classbdm_1_1BM}{BM} etc. Have to be DELETED manually! Prototype: BM$\ast$ \hyperlink{classbdm_1_1BM_3efb3098172f1f67564a312fe732473e}{\_\-copy\_\-()}\{\hyperlink{classbdm_1_1BM}{BM} Tmp$\ast$=new Tmp(this$\ast$); return Tmp; \} 
193
194Reimplemented in \hyperlink{classbdm_1_1ARX_20ff2de8d862f28de7da83444d65bcdb}{bdm::ARX}, and \hyperlink{classbdm_1_1BMEF_5912dbcf28ae711e30b08c2fa766a3e6}{bdm::BMEF}.
195
196The documentation for this class was generated from the following file:\begin{CompactItemize}
197\item 
198\hyperlink{libPF_8h}{libPF.h}\end{CompactItemize}
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