root/doc/latex/classbdm_1_1KalmanCh.tex @ 271

\hypertarget{classbdm_1_1KalmanCh}{
\section{bdm::KalmanCh Class Reference}
\label{classbdm_1_1KalmanCh}\index{bdm::KalmanCh@{bdm::KalmanCh}}
}
{\tt \#include $<$libKF.h$>$}

Inheritance diagram for bdm::KalmanCh::\begin{figure}[H]
\begin{center}
\leavevmode
\includegraphics[height=6cm]{classbdm_1_1KalmanCh}
\end{center}
\end{figure}


\subsection{Detailed Description}
\hyperlink{classbdm_1_1Kalman}{Kalman} filter in square root form. 

Trivial example: 

\begin{DocInclude}\begin{verbatim}#include <estim/libKF.h>
using namespace bdm;
        
// estimation of AR(0) model
int main() {
        //dimensions
        int dx=3, dy=3, du=1;
        // matrices
        mat A = eye(dx);
        mat B = zeros(dx,du);
        mat C = eye(dx);
        mat D = zeros(dy,du);
        mat Q = eye(dx);
        mat R = 0.1*eye(dy);
        //prior
        mat P0 = 100*eye(dx);
        vec mu0 = zeros(dx);
        // Estimator
        KalmanCh KF;
        KF.set_parameters(A,B,C,D,/*covariances*/ Q,R);
        KF.set_statistics(mu0,P0);
        // Estimation loop
        for (int i=0;i<100;i++){
                KF.bayes(randn(dx+du));
        }
        //print results
        cout << "Posterior estimate of x is: "  << endl;
        cout << "mean: "<< KF.posterior().mean()<< endl;
        cout << "variance: "<< KF.posterior().variance()<< endl;
}
\end{verbatim}
\end{DocInclude}
 \subsection*{Public Member Functions}
\begin{CompactItemize}
\item 
\hypertarget{classbdm_1_1KalmanCh_830486554e1a2c7652541dbc9dcd3fb3}{
\hyperlink{classbdm_1_1KalmanCh_830486554e1a2c7652541dbc9dcd3fb3}{KalmanCh} ()}
\label{classbdm_1_1KalmanCh_830486554e1a2c7652541dbc9dcd3fb3}

\begin{CompactList}\small\item\em Default constructor. \item\end{CompactList}\item 
\hypertarget{classbdm_1_1KalmanCh_20a4d4c664e8ac8a3f1bb7b0d11c6d87}{
void \hyperlink{classbdm_1_1KalmanCh_20a4d4c664e8ac8a3f1bb7b0d11c6d87}{set\_\-parameters} (const mat \&A0, const mat \&B0, const mat \&C0, const mat \&D0, const \hyperlink{classchmat}{chmat} \&Q0, const \hyperlink{classchmat}{chmat} \&R0)}
\label{classbdm_1_1KalmanCh_20a4d4c664e8ac8a3f1bb7b0d11c6d87}

\begin{CompactList}\small\item\em Set parameters with check of relevance. \item\end{CompactList}\item 
\hypertarget{classbdm_1_1KalmanCh_6e169272657ed101f3d128b49c59b890}{
void \textbf{set\_\-statistics} (const vec \&mu0, const \hyperlink{classchmat}{chmat} \&P0)}
\label{classbdm_1_1KalmanCh_6e169272657ed101f3d128b49c59b890}

\item 
void \hyperlink{classbdm_1_1KalmanCh_b41fe5540548100b08e1684c3be767b6}{bayes} (const vec \&dt)
\begin{CompactList}\small\item\em Here dt = \mbox{[}yt;ut\mbox{]} of appropriate dimensions. \item\end{CompactList}\item 
\hypertarget{classbdm_1_1Kalman_9264fc6b173ecb803d2684b883f32c68}{
void \hyperlink{classbdm_1_1Kalman_9264fc6b173ecb803d2684b883f32c68}{set\_\-est} (const vec \&mu0, const \hyperlink{classchmat}{chmat} \&P0)}
\label{classbdm_1_1Kalman_9264fc6b173ecb803d2684b883f32c68}

\begin{CompactList}\small\item\em Set estimate values, used e.g. in initialization. \item\end{CompactList}\item 
\hypertarget{classbdm_1_1Kalman_f75e487ff6c129d7012d702030f8c890}{
const \hyperlink{classbdm_1_1epdf}{epdf} \& \hyperlink{classbdm_1_1Kalman_f75e487ff6c129d7012d702030f8c890}{posterior} () const }
\label{classbdm_1_1Kalman_f75e487ff6c129d7012d702030f8c890}

\begin{CompactList}\small\item\em access function \item\end{CompactList}\item 
\hypertarget{classbdm_1_1Kalman_c34989b1e53c7d4ecdaea63a95ddbd77}{
const \hyperlink{classbdm_1_1enorm}{enorm}$<$ \hyperlink{classchmat}{chmat} $>$ $\ast$ \textbf{\_\-e} () const }
\label{classbdm_1_1Kalman_c34989b1e53c7d4ecdaea63a95ddbd77}

\item 
\hypertarget{classbdm_1_1Kalman_c788ec6e6c6f5f5861ae8a56d8ede277}{
mat \& \hyperlink{classbdm_1_1Kalman_c788ec6e6c6f5f5861ae8a56d8ede277}{\_\-\_\-K} ()}
\label{classbdm_1_1Kalman_c788ec6e6c6f5f5861ae8a56d8ede277}

\begin{CompactList}\small\item\em access function \item\end{CompactList}\item 
\hypertarget{classbdm_1_1Kalman_a250d1dbe7bba861dba2a324520cfa48}{
vec \hyperlink{classbdm_1_1Kalman_a250d1dbe7bba861dba2a324520cfa48}{\_\-dP} ()}
\label{classbdm_1_1Kalman_a250d1dbe7bba861dba2a324520cfa48}

\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_b38d92f17620813ad872d86e01a26e5e}{
void \textbf{set\_\-rv} (const \hyperlink{classbdm_1_1RV}{RV} \&rv)}
\label{classbdm_1_1BM_b38d92f17620813ad872d86e01a26e5e}

\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_1KalmanCh_48611c8582706cfa62e832be0972e75d}{
mat \hyperlink{classbdm_1_1KalmanCh_48611c8582706cfa62e832be0972e75d}{preA}}
\label{classbdm_1_1KalmanCh_48611c8582706cfa62e832be0972e75d}

\begin{CompactList}\small\item\em pre array (triangular matrix) \item\end{CompactList}\item 
\hypertarget{classbdm_1_1KalmanCh_bcbd68f51d4b57246e7784ca5900171f}{
mat \hyperlink{classbdm_1_1KalmanCh_bcbd68f51d4b57246e7784ca5900171f}{postA}}
\label{classbdm_1_1KalmanCh_bcbd68f51d4b57246e7784ca5900171f}

\begin{CompactList}\small\item\em post array (triangular matrix) \item\end{CompactList}\item 
\hypertarget{classbdm_1_1Kalman_3fe475a1e920b20b63bb342c0e1571f7}{
\hyperlink{classbdm_1_1RV}{RV} \hyperlink{classbdm_1_1Kalman_3fe475a1e920b20b63bb342c0e1571f7}{rvy}}
\label{classbdm_1_1Kalman_3fe475a1e920b20b63bb342c0e1571f7}

\begin{CompactList}\small\item\em Indetifier of output rv. \item\end{CompactList}\item 
\hypertarget{classbdm_1_1Kalman_149e27424fd1a7cc1c998ea088618a94}{
\hyperlink{classbdm_1_1RV}{RV} \hyperlink{classbdm_1_1Kalman_149e27424fd1a7cc1c998ea088618a94}{rvu}}
\label{classbdm_1_1Kalman_149e27424fd1a7cc1c998ea088618a94}

\begin{CompactList}\small\item\em Indetifier of exogeneous rv. \item\end{CompactList}\item 
\hypertarget{classbdm_1_1Kalman_ba7699cdb3b1382a54d3e28b9b7517fa}{
int \hyperlink{classbdm_1_1Kalman_ba7699cdb3b1382a54d3e28b9b7517fa}{dimx}}
\label{classbdm_1_1Kalman_ba7699cdb3b1382a54d3e28b9b7517fa}

\begin{CompactList}\small\item\em cache of rv.count() \item\end{CompactList}\item 
\hypertarget{classbdm_1_1Kalman_d2c36ba01760bf207b985bf321b7817f}{
int \hyperlink{classbdm_1_1Kalman_d2c36ba01760bf207b985bf321b7817f}{dimy}}
\label{classbdm_1_1Kalman_d2c36ba01760bf207b985bf321b7817f}

\begin{CompactList}\small\item\em cache of rvy.count() \item\end{CompactList}\item 
\hypertarget{classbdm_1_1Kalman_c5136ef617f6ac0e426bea222755d92b}{
int \hyperlink{classbdm_1_1Kalman_c5136ef617f6ac0e426bea222755d92b}{dimu}}
\label{classbdm_1_1Kalman_c5136ef617f6ac0e426bea222755d92b}

\begin{CompactList}\small\item\em cache of rvu.count() \item\end{CompactList}\item 
\hypertarget{classbdm_1_1Kalman_0a2072e2090c10fac74ad30a023a4ace}{
mat \hyperlink{classbdm_1_1Kalman_0a2072e2090c10fac74ad30a023a4ace}{A}}
\label{classbdm_1_1Kalman_0a2072e2090c10fac74ad30a023a4ace}

\begin{CompactList}\small\item\em Matrix A. \item\end{CompactList}\item 
\hypertarget{classbdm_1_1Kalman_5977b2c81857948a35105f0e7840203c}{
mat \hyperlink{classbdm_1_1Kalman_5977b2c81857948a35105f0e7840203c}{B}}
\label{classbdm_1_1Kalman_5977b2c81857948a35105f0e7840203c}

\begin{CompactList}\small\item\em Matrix B. \item\end{CompactList}\item 
\hypertarget{classbdm_1_1Kalman_818eba63a23972786a4579ad30294177}{
mat \hyperlink{classbdm_1_1Kalman_818eba63a23972786a4579ad30294177}{C}}
\label{classbdm_1_1Kalman_818eba63a23972786a4579ad30294177}

\begin{CompactList}\small\item\em Matrix C. \item\end{CompactList}\item 
\hypertarget{classbdm_1_1Kalman_7b56ac423d0654b5755e4f852a870456}{
mat \hyperlink{classbdm_1_1Kalman_7b56ac423d0654b5755e4f852a870456}{D}}
\label{classbdm_1_1Kalman_7b56ac423d0654b5755e4f852a870456}

\begin{CompactList}\small\item\em Matrix D. \item\end{CompactList}\item 
\hypertarget{classbdm_1_1Kalman_70f8bf19e81b532c60fd3a7a152425ee}{
\hyperlink{classchmat}{chmat} \hyperlink{classbdm_1_1Kalman_70f8bf19e81b532c60fd3a7a152425ee}{Q}}
\label{classbdm_1_1Kalman_70f8bf19e81b532c60fd3a7a152425ee}

\begin{CompactList}\small\item\em Matrix Q in square-root form. \item\end{CompactList}\item 
\hypertarget{classbdm_1_1Kalman_475b088287cdfbba4dc60a3d027728b7}{
\hyperlink{classchmat}{chmat} \hyperlink{classbdm_1_1Kalman_475b088287cdfbba4dc60a3d027728b7}{R}}
\label{classbdm_1_1Kalman_475b088287cdfbba4dc60a3d027728b7}

\begin{CompactList}\small\item\em Matrix R in square-root form. \item\end{CompactList}\item 
\hypertarget{classbdm_1_1Kalman_383f329ff18bbe219254c8b3b916f40d}{
\hyperlink{classbdm_1_1enorm}{enorm}$<$ \hyperlink{classchmat}{chmat} $>$ \hyperlink{classbdm_1_1Kalman_383f329ff18bbe219254c8b3b916f40d}{est}}
\label{classbdm_1_1Kalman_383f329ff18bbe219254c8b3b916f40d}

\begin{CompactList}\small\item\em posterior density on \$x\_\-t\$ \item\end{CompactList}\item 
\hypertarget{classbdm_1_1Kalman_ba555c394c429f6831c9bbabfa2c944c}{
\hyperlink{classbdm_1_1enorm}{enorm}$<$ \hyperlink{classchmat}{chmat} $>$ \hyperlink{classbdm_1_1Kalman_ba555c394c429f6831c9bbabfa2c944c}{fy}}
\label{classbdm_1_1Kalman_ba555c394c429f6831c9bbabfa2c944c}

\begin{CompactList}\small\item\em preditive density on \$y\_\-t\$ \item\end{CompactList}\item 
\hypertarget{classbdm_1_1Kalman_bd69dfb802465f22dd84d73a180d5c92}{
mat \hyperlink{classbdm_1_1Kalman_bd69dfb802465f22dd84d73a180d5c92}{\_\-K}}
\label{classbdm_1_1Kalman_bd69dfb802465f22dd84d73a180d5c92}

\begin{CompactList}\small\item\em placeholder for Kalman gain \item\end{CompactList}\item 
\hypertarget{classbdm_1_1Kalman_c249d45258c8578b13858ad3e7b729b1}{
vec \& \hyperlink{classbdm_1_1Kalman_c249d45258c8578b13858ad3e7b729b1}{\_\-yp}}
\label{classbdm_1_1Kalman_c249d45258c8578b13858ad3e7b729b1}

\begin{CompactList}\small\item\em cache of fy.mu \item\end{CompactList}\item 
\hypertarget{classbdm_1_1Kalman_2dd268f2d7fbe6382cb8825a1114192a}{
\hyperlink{classchmat}{chmat} \& \hyperlink{classbdm_1_1Kalman_2dd268f2d7fbe6382cb8825a1114192a}{\_\-Ry}}
\label{classbdm_1_1Kalman_2dd268f2d7fbe6382cb8825a1114192a}

\begin{CompactList}\small\item\em cache of fy.R \item\end{CompactList}\item 
\hypertarget{classbdm_1_1Kalman_fa172078091e45561343fa513dd573b0}{
vec \& \hyperlink{classbdm_1_1Kalman_fa172078091e45561343fa513dd573b0}{\_\-mu}}
\label{classbdm_1_1Kalman_fa172078091e45561343fa513dd573b0}

\begin{CompactList}\small\item\em cache of est.mu \item\end{CompactList}\item 
\hypertarget{classbdm_1_1Kalman_00c27b0bf324f0018497921ca23c71ed}{
\hyperlink{classchmat}{chmat} \& \hyperlink{classbdm_1_1Kalman_00c27b0bf324f0018497921ca23c71ed}{\_\-P}}
\label{classbdm_1_1Kalman_00c27b0bf324f0018497921ca23c71ed}

\begin{CompactList}\small\item\em cache of est.R \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_1KalmanCh_b41fe5540548100b08e1684c3be767b6}{
\index{bdm::KalmanCh@{bdm::KalmanCh}!bayes@{bayes}}
\index{bayes@{bayes}!bdm::KalmanCh@{bdm::KalmanCh}}
\subsubsection[bayes]{\setlength{\rightskip}{0pt plus 5cm}void bdm::KalmanCh::bayes (const vec \& {\em dt})\hspace{0.3cm}{\tt  \mbox{[}virtual\mbox{]}}}}
\label{classbdm_1_1KalmanCh_b41fe5540548100b08e1684c3be767b6}


Here dt = \mbox{[}yt;ut\mbox{]} of appropriate dimensions. 

The following equality hold::\[ \left[\begin{array}{cc} R^{0.5}\\ P_{t|t-1}^{0.5}C' & P_{t|t-1}^{0.5}CA'\\ & Q^{0.5}\end{array}\right]<\mathrm{orth.oper.}>=\left[\begin{array}{cc} R_{y}^{0.5} & KA'\\ & P_{t+1|t}^{0.5}\\ \\\end{array}\right]\]

Thus this object evaluates only predictors! Not filtering densities. 

Reimplemented from \hyperlink{classbdm_1_1Kalman_4a39330c14eff8d13179e868a1d1aa8c}{bdm::Kalman$<$ chmat $>$}.

Reimplemented in \hyperlink{classbdm_1_1EKFCh_4c8609c37290b158f88a31dae4047225}{bdm::EKFCh}.

References chmat::\_\-Ch(), bdm::Kalman$<$ chmat $>$::\_\-K, bdm::Kalman$<$ chmat $>$::\_\-mu, bdm::Kalman$<$ chmat $>$::\_\-P, bdm::Kalman$<$ chmat $>$::\_\-Ry, bdm::Kalman$<$ chmat $>$::\_\-yp, bdm::Kalman$<$ chmat $>$::A, bdm::Kalman$<$ chmat $>$::B, bdm::Kalman$<$ chmat $>$::C, bdm::Kalman$<$ chmat $>$::D, bdm::Kalman$<$ chmat $>$::dimu, bdm::Kalman$<$ chmat $>$::dimx, bdm::Kalman$<$ chmat $>$::dimy, bdm::BM::evalll, bdm::eEF::evallog(), bdm::Kalman$<$ chmat $>$::fy, bdm::BM::ll, postA, and preA.\hypertarget{classbdm_1_1BM_c0f027ff91d8459937c6f60ff8e553ff}{
\index{bdm::KalmanCh@{bdm::KalmanCh}!\_\-copy\_\-@{\_\-copy\_\-}}
\index{\_\-copy\_\-@{\_\-copy\_\-}!bdm::KalmanCh@{bdm::KalmanCh}}
\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::KalmanCh@{bdm::KalmanCh}!logpred@{logpred}}
\index{logpred@{logpred}!bdm::KalmanCh@{bdm::KalmanCh}}
\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 files:\begin{CompactItemize}
\item 
\hyperlink{libKF_8h}{libKF.h}\item 
libKF.cpp\end{CompactItemize}