\hypertarget{classbdm_1_1MixEF}{ \section{bdm::MixEF Class Reference} \label{classbdm_1_1MixEF}\index{bdm::MixEF@{bdm::MixEF}} } {\tt \#include $<$mixef.h$>$} Inheritance diagram for bdm::MixEF:\nopagebreak \begin{figure}[H] \begin{center} \leavevmode \includegraphics[width=64pt]{classbdm_1_1MixEF__inherit__graph} \end{center} \end{figure} \subsection{Detailed Description} Mixture of Exponential Family Densities. An approximate estimation method for models with latent discrete variable, such as mixture models of the following kind: \[ f(y_t|\psi_t, \Theta) = \sum_{i=1}^{n} w_i f(y_t|\psi_t, \theta_i) \] where $\psi$ is a known function of past outputs, $w=[w_1,\ldots,w_n]$ are component weights, and component parameters $\theta_i$ are assumed to be mutually independent. $\Theta$ is an aggregation af all component parameters and weights, i.e. $\Theta = [\theta_1,\ldots,\theta_n,w]$. The characteristic feature of this model is that if the exact values of the latent variable were known, estimation of the parameters can be handled by a single model. For example, for the case of mixture models, posterior density for each component parameters would be a BayesianModel from Exponential Family. This class uses EM-style type algorithms for estimation of its parameters. Under this simplification, the posterior density is a product of exponential family members, hence under EM-style approximate estimation this class itself belongs to the exponential family. TODO: Extend \hyperlink{classbdm_1_1BM}{BM} to use rvc. \subsection*{Public Member Functions} \begin{CompactItemize} \item \hypertarget{classbdm_1_1MixEF_4efe67d414ff34a1e7534004fd061241}{ \hyperlink{classbdm_1_1MixEF_4efe67d414ff34a1e7534004fd061241}{MixEF} (const Array$<$ \hyperlink{classbdm_1_1BMEF}{BMEF} $\ast$ $>$ \&Coms0, const vec \&alpha0)} \label{classbdm_1_1MixEF_4efe67d414ff34a1e7534004fd061241} \begin{CompactList}\small\item\em Full constructor. \item\end{CompactList}\item \hypertarget{classbdm_1_1MixEF_0266854387338ba757e6192d62907984}{ \hyperlink{classbdm_1_1MixEF_0266854387338ba757e6192d62907984}{MixEF} ()} \label{classbdm_1_1MixEF_0266854387338ba757e6192d62907984} \begin{CompactList}\small\item\em Constructor of empty mixture. \item\end{CompactList}\item \hypertarget{classbdm_1_1MixEF_9577de85c3e3481f7c0e23cf8f87c482}{ \hyperlink{classbdm_1_1MixEF_9577de85c3e3481f7c0e23cf8f87c482}{MixEF} (const \hyperlink{classbdm_1_1MixEF}{MixEF} \&M2)} \label{classbdm_1_1MixEF_9577de85c3e3481f7c0e23cf8f87c482} \begin{CompactList}\small\item\em Copy constructor. \item\end{CompactList}\item void \hyperlink{classbdm_1_1MixEF_0c2a50789b30769964a909d217125ed2}{init} (\hyperlink{classbdm_1_1BMEF}{BMEF} $\ast$Com0, const mat \&Data, int c=5) \item \hypertarget{classbdm_1_1MixEF_5bd7da667da183eed1577f11dff0c1f1}{ void \hyperlink{classbdm_1_1MixEF_5bd7da667da183eed1577f11dff0c1f1}{bayes} (const vec \&dt)} \label{classbdm_1_1MixEF_5bd7da667da183eed1577f11dff0c1f1} \begin{CompactList}\small\item\em Recursive EM-like algorithm (QB-variant), see Karny et. al, 2006. \item\end{CompactList}\item \hypertarget{classbdm_1_1MixEF_5c41d5a4403da6e629f6bdfc70c43d20}{ void \hyperlink{classbdm_1_1MixEF_5c41d5a4403da6e629f6bdfc70c43d20}{bayes} (const mat \&dt)} \label{classbdm_1_1MixEF_5c41d5a4403da6e629f6bdfc70c43d20} \begin{CompactList}\small\item\em EM algorithm. \item\end{CompactList}\item \hypertarget{classbdm_1_1MixEF_5de521c395e93478df00d881ab8dac81}{ void \textbf{bayesB} (const mat \&dt, const vec \&wData)} \label{classbdm_1_1MixEF_5de521c395e93478df00d881ab8dac81} \item double \hyperlink{classbdm_1_1MixEF_da724da464a75e07521941e430929efa}{logpred} (const vec \&dt) const \item \hypertarget{classbdm_1_1MixEF_33d0b3da1d10bf149d41ee74f6284a19}{ const \hyperlink{classbdm_1_1epdf}{epdf} \& \textbf{\_\-epdf} () const } \label{classbdm_1_1MixEF_33d0b3da1d10bf149d41ee74f6284a19} \item \hypertarget{classbdm_1_1MixEF_ea8be6f0703d87b7c4c3e77fd07e28c8}{ const \hyperlink{classbdm_1_1eprod}{eprod} $\ast$ \textbf{\_\-e} () const } \label{classbdm_1_1MixEF_ea8be6f0703d87b7c4c3e77fd07e28c8} \item \hypertarget{classbdm_1_1MixEF_edc50e9640f049b846084748b18469a2}{ \hyperlink{classbdm_1_1emix}{emix} $\ast$ \hyperlink{classbdm_1_1MixEF_edc50e9640f049b846084748b18469a2}{epredictor} () const } \label{classbdm_1_1MixEF_edc50e9640f049b846084748b18469a2} \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_1MixEF_f0dfb4375fef4e61c4cb062e5bac7c8c}{ void \hyperlink{classbdm_1_1MixEF_f0dfb4375fef4e61c4cb062e5bac7c8c}{flatten} (const \hyperlink{classbdm_1_1BMEF}{BMEF} $\ast$M2)} \label{classbdm_1_1MixEF_f0dfb4375fef4e61c4cb062e5bac7c8c} \begin{CompactList}\small\item\em Flatten the density as if it was not estimated from the data. \item\end{CompactList}\item \hypertarget{classbdm_1_1MixEF_251ef6fc51757712693da5faae5317c9}{ \hyperlink{classbdm_1_1BMEF}{BMEF} $\ast$ \hyperlink{classbdm_1_1MixEF_251ef6fc51757712693da5faae5317c9}{\_\-Coms} (int i)} \label{classbdm_1_1MixEF_251ef6fc51757712693da5faae5317c9} \begin{CompactList}\small\item\em Access function. \item\end{CompactList}\item \hypertarget{classbdm_1_1MixEF_664529d52cc667383b39eeb440ccd577}{ void \hyperlink{classbdm_1_1MixEF_664529d52cc667383b39eeb440ccd577}{set\_\-method} (MixEF\_\-METHOD M)} \label{classbdm_1_1MixEF_664529d52cc667383b39eeb440ccd577} \begin{CompactList}\small\item\em Set which method is to be used. \item\end{CompactList}\item \hypertarget{classbdm_1_1BMEF_d2b528b7a41ca67163152142f5404051}{ virtual void \hyperlink{classbdm_1_1BMEF_d2b528b7a41ca67163152142f5404051}{set\_\-statistics} (const \hyperlink{classbdm_1_1BMEF}{BMEF} $\ast$BM0)} \label{classbdm_1_1BMEF_d2b528b7a41ca67163152142f5404051} \begin{CompactList}\small\item\em get statistics from another model \item\end{CompactList}\item \hypertarget{classbdm_1_1BMEF_bf58deb99af2a6cc674f13ff90300de6}{ virtual void \hyperlink{classbdm_1_1BMEF_bf58deb99af2a6cc674f13ff90300de6}{bayes} (const vec \&data, const double w)} \label{classbdm_1_1BMEF_bf58deb99af2a6cc674f13ff90300de6} \begin{CompactList}\small\item\em Weighted update of sufficient statistics (Bayes rule). \item\end{CompactList}\item \hypertarget{classbdm_1_1BMEF_5912dbcf28ae711e30b08c2fa766a3e6}{ \hyperlink{classbdm_1_1BMEF}{BMEF} $\ast$ \hyperlink{classbdm_1_1BMEF_5912dbcf28ae711e30b08c2fa766a3e6}{\_\-copy\_\-} (bool changerv=false)} \label{classbdm_1_1BMEF_5912dbcf28ae711e30b08c2fa766a3e6} \begin{CompactList}\small\item\em Flatten the posterior as if to keep nu0 data. \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 \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_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 Member Functions} \begin{CompactItemize} \item \hypertarget{classbdm_1_1MixEF_d74a8d1370c63c93ec554908ae3e6006}{ void \hyperlink{classbdm_1_1MixEF_d74a8d1370c63c93ec554908ae3e6006}{build\_\-est} ()} \label{classbdm_1_1MixEF_d74a8d1370c63c93ec554908ae3e6006} \begin{CompactList}\small\item\em Auxiliary function for use in constructors. \item\end{CompactList}\end{CompactItemize} \subsection*{Protected Attributes} \begin{CompactItemize} \item \hypertarget{classbdm_1_1MixEF_38ca1d86e977d1c38810a3c95bf074a5}{ int \hyperlink{classbdm_1_1MixEF_38ca1d86e977d1c38810a3c95bf074a5}{n}} \label{classbdm_1_1MixEF_38ca1d86e977d1c38810a3c95bf074a5} \begin{CompactList}\small\item\em Number of components. \item\end{CompactList}\item \hypertarget{classbdm_1_1MixEF_90c21ab5a2af56d4b49e2eaef6eccc08}{ Array$<$ \hyperlink{classbdm_1_1BMEF}{BMEF} $\ast$ $>$ \hyperlink{classbdm_1_1MixEF_90c21ab5a2af56d4b49e2eaef6eccc08}{Coms}} \label{classbdm_1_1MixEF_90c21ab5a2af56d4b49e2eaef6eccc08} \begin{CompactList}\small\item\em Models for Components of $\theta_i$. \item\end{CompactList}\item \hypertarget{classbdm_1_1MixEF_e39faa70cebadc3296bd249040105e86}{ \hyperlink{classbdm_1_1multiBM}{multiBM} \hyperlink{classbdm_1_1MixEF_e39faa70cebadc3296bd249040105e86}{weights}} \label{classbdm_1_1MixEF_e39faa70cebadc3296bd249040105e86} \begin{CompactList}\small\item\em Statistics for weights. \item\end{CompactList}\item \hypertarget{classbdm_1_1MixEF_9413fb7f1836237aac807fb9f245e4f6}{ \hyperlink{classbdm_1_1eprod}{eprod} $\ast$ \hyperlink{classbdm_1_1MixEF_9413fb7f1836237aac807fb9f245e4f6}{est}} \label{classbdm_1_1MixEF_9413fb7f1836237aac807fb9f245e4f6} \begin{CompactList}\small\item\em Posterior on component parameters. \item\end{CompactList}\item \hypertarget{classbdm_1_1MixEF_a2376ddadb7573532404452d0c2dd28a}{ MixEF\_\-METHOD \hyperlink{classbdm_1_1MixEF_a2376ddadb7573532404452d0c2dd28a}{method}} \label{classbdm_1_1MixEF_a2376ddadb7573532404452d0c2dd28a} \begin{CompactList}\small\item\em Flag for a method that is used in the inference. \item\end{CompactList}\item \hypertarget{classbdm_1_1BMEF_1331865e10fb1ccef65bb4c47fa3be64}{ double \hyperlink{classbdm_1_1BMEF_1331865e10fb1ccef65bb4c47fa3be64}{frg}} \label{classbdm_1_1BMEF_1331865e10fb1ccef65bb4c47fa3be64} \begin{CompactList}\small\item\em forgetting factor \item\end{CompactList}\item \hypertarget{classbdm_1_1BMEF_06e7b3ac03e10017d4288c76888e2865}{ double \hyperlink{classbdm_1_1BMEF_06e7b3ac03e10017d4288c76888e2865}{last\_\-lognc}} \label{classbdm_1_1BMEF_06e7b3ac03e10017d4288c76888e2865} \begin{CompactList}\small\item\em cached value of lognc() in the previous step (used in evaluation of {\tt ll} ) \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{Member Function Documentation} \hypertarget{classbdm_1_1MixEF_0c2a50789b30769964a909d217125ed2}{ \index{bdm::MixEF@{bdm::MixEF}!init@{init}} \index{init@{init}!bdm::MixEF@{bdm::MixEF}} \subsubsection[init]{\setlength{\rightskip}{0pt plus 5cm}void bdm::MixEF::init ({\bf BMEF} $\ast$ {\em Com0}, \/ const mat \& {\em Data}, \/ int {\em c} = {\tt 5})}} \label{classbdm_1_1MixEF_0c2a50789b30769964a909d217125ed2} Initializing the mixture by a random pick of centroids from data \begin{Desc} \item[Parameters:] \begin{description} \item[{\em Com0}]Initial component - necessary to determine its type. \item[{\em Data}]Data on which the initialization will be done \item[{\em c}]Initial number of components, default=5 \end{description} \end{Desc} References bdm::BMEF::\_\-copy\_\-(), build\_\-est(), Coms, est, n, bdm::multiBM::set\_\-parameters(), bdm::UniRNG, and weights. Referenced by bdm::merger::merge().\hypertarget{classbdm_1_1MixEF_da724da464a75e07521941e430929efa}{ \index{bdm::MixEF@{bdm::MixEF}!logpred@{logpred}} \index{logpred@{logpred}!bdm::MixEF@{bdm::MixEF}} \subsubsection[logpred]{\setlength{\rightskip}{0pt plus 5cm}double bdm::MixEF::logpred (const vec \& {\em dt}) const\hspace{0.3cm}{\tt \mbox{[}virtual\mbox{]}}}} \label{classbdm_1_1MixEF_da724da464a75e07521941e430929efa} Evaluates predictive log-likelihood of the given data record I.e. marginal likelihood of the data with the posterior integrated out. Reimplemented from \hyperlink{classbdm_1_1BM_50257e0c1e5b5c73153ea6e716ad8ae0}{bdm::BM}. References bdm::multiBM::\_\-epdf(), Coms, bdm::epdf::mean(), and weights. Referenced by bdm::merger::evallog(), and bdm::merger::merge().\hypertarget{classbdm_1_1BM_c0f027ff91d8459937c6f60ff8e553ff}{ \index{bdm::MixEF@{bdm::MixEF}!\_\-copy\_\-@{\_\-copy\_\-}} \index{\_\-copy\_\-@{\_\-copy\_\-}!bdm::MixEF@{bdm::MixEF}} \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}. The documentation for this class was generated from the following files:\begin{CompactItemize} \item \hyperlink{mixef_8h}{mixef.h}\item mixef.cpp\end{CompactItemize}