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\section{mixpp Class List}
Here are the classes, structs, unions and interfaces with brief descriptions:\begin{CompactList}
\item\contentsline{section}{{\bf BM} (Bayesian Model of the world, i.e. all uncertainty is modeled by probabilities )}{\pageref{classBM}}{}
\item\contentsline{section}{{\bf eEF} (General conjugate exponential family posterior density )}{\pageref{classeEF}}{}
\item\contentsline{section}{{\bf enorm$<$ sq\_\-T $>$} (General exponential family density )}{\pageref{classenorm}}{}
\item\contentsline{section}{{\bf epdf} (Probability density function with numerical statistics, e.g. posterior density )}{\pageref{classepdf}}{}
\item\contentsline{section}{{\bf fnc} (Class representing function of variables )}{\pageref{classfnc}}{}
\item\contentsline{section}{{\bf fsqmat} (Fake \doxyref{sqmat}{p.}{classsqmat}. This class maps \doxyref{sqmat}{p.}{classsqmat} operations to operations on full matrix )}{\pageref{classfsqmat}}{}
\item\contentsline{section}{{\bf Kalman$<$ sq\_\-T $>$} (\doxyref{Kalman}{p.}{classKalman} filter with covaraince matrices in square root form )}{\pageref{classKalman}}{}
\item\contentsline{section}{{\bf KalmanFull} (Basic \doxyref{Kalman}{p.}{classKalman} filter with full matrices (education purpose only)! Will be deleted soon! )}{\pageref{classKalmanFull}}{}
\item\contentsline{section}{{\bf mpdf} (Conditional probability density, e.g. modeling some dependencies )}{\pageref{classmpdf}}{}
\item\contentsline{section}{{\bf PF} (A Particle Filter prototype )}{\pageref{classPF}}{}
\item\contentsline{section}{{\bf RV} (Class representing variables, most often random variables )}{\pageref{classRV}}{}
\item\contentsline{section}{{\bf sqmat} (Virtual class for representation of double symmetric matrices in square-root form )}{\pageref{classsqmat}}{}
\item\contentsline{section}{{\bf TrivialPF} (Trivial particle filter with proposal density that is not conditioned on the data )}{\pageref{classTrivialPF}}{}
\end{CompactList}