\hypertarget{classegamma}{ \section{egamma Class Reference} \label{classegamma}\index{egamma@{egamma}} } Gamma posterior density. {\tt \#include $<$libEF.h$>$} Inheritance diagram for egamma:\nopagebreak \begin{figure}[H] \begin{center} \leavevmode \includegraphics[width=49pt]{classegamma__inherit__graph} \end{center} \end{figure} Collaboration diagram for egamma:\nopagebreak \begin{figure}[H] \begin{center} \leavevmode \includegraphics[width=49pt]{classegamma__coll__graph} \end{center} \end{figure} \subsection*{Public Member Functions} \begin{CompactItemize} \item \hypertarget{classegamma_4b1d34f3b244ea51a58ec10c468788c1}{ \hyperlink{classegamma_4b1d34f3b244ea51a58ec10c468788c1}{egamma} (const \hyperlink{classRV}{RV} \&\hyperlink{classepdf_74da992e3f5d598da8850b646b79b9d9}{rv})} \label{classegamma_4b1d34f3b244ea51a58ec10c468788c1} \begin{CompactList}\small\item\em Default constructor. \item\end{CompactList}\item \hypertarget{classegamma_8e348b89be82b70471fe8c5630f61339}{ void \hyperlink{classegamma_8e348b89be82b70471fe8c5630f61339}{set\_\-parameters} (const vec \&a, const vec \&b)} \label{classegamma_8e348b89be82b70471fe8c5630f61339} \begin{CompactList}\small\item\em Sets parameters. \item\end{CompactList}\item \hypertarget{classegamma_8e10c0021b5dfdd9cb62c6959b5ef425}{ vec \hyperlink{classegamma_8e10c0021b5dfdd9cb62c6959b5ef425}{sample} () const } \label{classegamma_8e10c0021b5dfdd9cb62c6959b5ef425} \begin{CompactList}\small\item\em Returns a sample, $x$ from density $epdf(rv)$. \item\end{CompactList}\item \hypertarget{classegamma_74a49a4c696f44e54bb6b0515e155a9b}{ double \hyperlink{classegamma_74a49a4c696f44e54bb6b0515e155a9b}{evallog} (const vec \&val) const } \label{classegamma_74a49a4c696f44e54bb6b0515e155a9b} \begin{CompactList}\small\item\em TODO: is it used anywhere? \item\end{CompactList}\item \hypertarget{classegamma_d6dbbdb72360f9e54d64501f80318bb6}{ double \hyperlink{classegamma_d6dbbdb72360f9e54d64501f80318bb6}{lognc} () const } \label{classegamma_d6dbbdb72360f9e54d64501f80318bb6} \begin{CompactList}\small\item\em logarithm of the normalizing constant, $\mathcal{I}$ \item\end{CompactList}\item \hypertarget{classegamma_44445c56e60b91b377f207f8d5089790}{ void \hyperlink{classegamma_44445c56e60b91b377f207f8d5089790}{\_\-param} (vec $\ast$\&a, vec $\ast$\&b)} \label{classegamma_44445c56e60b91b377f207f8d5089790} \begin{CompactList}\small\item\em Returns poiter to alpha and beta. Potentially dengerous: use with care! \item\end{CompactList}\item \hypertarget{classegamma_6ab5ba56f7cdb2e5921c3e77524fa50a}{ vec \hyperlink{classegamma_6ab5ba56f7cdb2e5921c3e77524fa50a}{mean} () const } \label{classegamma_6ab5ba56f7cdb2e5921c3e77524fa50a} \begin{CompactList}\small\item\em return expected value \item\end{CompactList}\item \hypertarget{classegamma_1dee6186a084565de4f9ceb3410148e4}{ vec \hyperlink{classegamma_1dee6186a084565de4f9ceb3410148e4}{variance} () const } \label{classegamma_1dee6186a084565de4f9ceb3410148e4} \begin{CompactList}\small\item\em return expected variance (not covariance!) \item\end{CompactList}\item \hypertarget{classeEF_a89bef8996410609004fa019b5b48964}{ virtual void \hyperlink{classeEF_a89bef8996410609004fa019b5b48964}{dupdate} (mat \&v)} \label{classeEF_a89bef8996410609004fa019b5b48964} \begin{CompactList}\small\item\em TODO decide if it is really needed. \item\end{CompactList}\item \hypertarget{classeEF_41c70565b4d3fb424599817d008f0c71}{ virtual double \hyperlink{classeEF_41c70565b4d3fb424599817d008f0c71}{evallog\_\-nn} (const vec \&val) const } \label{classeEF_41c70565b4d3fb424599817d008f0c71} \begin{CompactList}\small\item\em Evaluate normalized log-probability. \item\end{CompactList}\item \hypertarget{classeEF_cff03a658aec11b806c3e3d48f37b81f}{ virtual vec \hyperlink{classeEF_cff03a658aec11b806c3e3d48f37b81f}{evallog} (const mat \&Val) const } \label{classeEF_cff03a658aec11b806c3e3d48f37b81f} \begin{CompactList}\small\item\em Evaluate normalized log-probability for many samples. \item\end{CompactList}\item \hypertarget{classeEF_4f8385dd1cc9740522dc373b1dc3cbf5}{ virtual void \hyperlink{classeEF_4f8385dd1cc9740522dc373b1dc3cbf5}{pow} (double p)} \label{classeEF_4f8385dd1cc9740522dc373b1dc3cbf5} \begin{CompactList}\small\item\em Power of the density, used e.g. to flatten the density. \item\end{CompactList}\item \hypertarget{classepdf_76608914c3b19e150292d5c56e93e508}{ virtual mat \hyperlink{classepdf_76608914c3b19e150292d5c56e93e508}{sample\_\-m} (int N) const } \label{classepdf_76608914c3b19e150292d5c56e93e508} \begin{CompactList}\small\item\em Returns N samples from density $epdf(rv)$. \item\end{CompactList}\item \hypertarget{classepdf_2495a04bbacb9b55fe5a3a59b78affca}{ virtual vec \hyperlink{classepdf_2495a04bbacb9b55fe5a3a59b78affca}{evallog\_\-m} (const mat \&Val) const } \label{classepdf_2495a04bbacb9b55fe5a3a59b78affca} \begin{CompactList}\small\item\em Compute log-probability of multiple values argument {\tt val}. \item\end{CompactList}\item \hypertarget{classepdf_e87dc8260a5c37bc1b03eb66174741a0}{ virtual \hyperlink{classmpdf}{mpdf} $\ast$ \hyperlink{classepdf_e87dc8260a5c37bc1b03eb66174741a0}{condition} (const \hyperlink{classRV}{RV} \&\hyperlink{classepdf_74da992e3f5d598da8850b646b79b9d9}{rv}) const } \label{classepdf_e87dc8260a5c37bc1b03eb66174741a0} \begin{CompactList}\small\item\em Return conditional density on the given \hyperlink{classRV}{RV}, the remaining rvs will be in conditioning. \item\end{CompactList}\item \hypertarget{classepdf_38de9f59b65ee06028554f3f74b66025}{ virtual \hyperlink{classepdf}{epdf} $\ast$ \hyperlink{classepdf_38de9f59b65ee06028554f3f74b66025}{marginal} (const \hyperlink{classRV}{RV} \&\hyperlink{classepdf_74da992e3f5d598da8850b646b79b9d9}{rv}) const } \label{classepdf_38de9f59b65ee06028554f3f74b66025} \begin{CompactList}\small\item\em Return marginal density on the given \hyperlink{classRV}{RV}, the remainig rvs are intergrated out. \item\end{CompactList}\item \hypertarget{classepdf_ca0d32aabb4cbba347e0c37fe8607562}{ const \hyperlink{classRV}{RV} \& \hyperlink{classepdf_ca0d32aabb4cbba347e0c37fe8607562}{\_\-rv} () const } \label{classepdf_ca0d32aabb4cbba347e0c37fe8607562} \begin{CompactList}\small\item\em access function, possibly dangerous! \item\end{CompactList}\item \hypertarget{classepdf_7fb94ce90d1ac7077d29f7d6a6c3e0a5}{ void \hyperlink{classepdf_7fb94ce90d1ac7077d29f7d6a6c3e0a5}{\_\-renewrv} (const \hyperlink{classRV}{RV} \&in\_\-rv)} \label{classepdf_7fb94ce90d1ac7077d29f7d6a6c3e0a5} \begin{CompactList}\small\item\em modifier function - useful when copying epdfs \item\end{CompactList}\end{CompactItemize} \subsection*{Protected Attributes} \begin{CompactItemize} \item \hypertarget{classegamma_376cebd8932546c440f21b182910b01b}{ vec \hyperlink{classegamma_376cebd8932546c440f21b182910b01b}{alpha}} \label{classegamma_376cebd8932546c440f21b182910b01b} \begin{CompactList}\small\item\em Vector $\alpha$. \item\end{CompactList}\item \hypertarget{classegamma_cfc5f136467488a421ab22f886323790}{ vec \hyperlink{classegamma_cfc5f136467488a421ab22f886323790}{beta}} \label{classegamma_cfc5f136467488a421ab22f886323790} \begin{CompactList}\small\item\em Vector $\beta$. \item\end{CompactList}\item \hypertarget{classepdf_74da992e3f5d598da8850b646b79b9d9}{ \hyperlink{classRV}{RV} \hyperlink{classepdf_74da992e3f5d598da8850b646b79b9d9}{rv}} \label{classepdf_74da992e3f5d598da8850b646b79b9d9} \begin{CompactList}\small\item\em Identified of the random variable. \item\end{CompactList}\end{CompactItemize} \subsection{Detailed Description} Gamma posterior density. Multivariate Gamma density as product of independent univariate densities. \[ f(x|\alpha,\beta) = \prod f(x_i|\alpha_i,\beta_i) \] The documentation for this class was generated from the following files:\begin{CompactItemize} \item work/git/mixpp/bdm/stat/\hyperlink{libEF_8h}{libEF.h}\item work/git/mixpp/bdm/stat/libEF.cpp\end{CompactItemize}