\hypertarget{classmigamma}{ \section{migamma Class Reference} \label{classmigamma}\index{migamma@{migamma}} } Inverse-Gamma random walk. {\tt \#include $<$libEF.h$>$} Inheritance diagram for migamma:\nopagebreak \begin{figure}[H] \begin{center} \leavevmode \includegraphics[width=62pt]{classmigamma__inherit__graph} \end{center} \end{figure} Collaboration diagram for migamma:\nopagebreak \begin{figure}[H] \begin{center} \leavevmode \includegraphics[height=400pt]{classmigamma__coll__graph} \end{center} \end{figure} \subsection*{Public Member Functions} \begin{CompactItemize} \item \hypertarget{classmigamma_81d6f9fe46acec656ccde245220b7090}{ \hyperlink{classmigamma_81d6f9fe46acec656ccde245220b7090}{migamma} (const \hyperlink{classRV}{RV} \&\hyperlink{classmpdf_f6687c07ff07d47812dd565368ca59eb}{rv}, const \hyperlink{classRV}{RV} \&\hyperlink{classmpdf_acb7dda792b3cd5576f39fa3129abbab}{rvc})} \label{classmigamma_81d6f9fe46acec656ccde245220b7090} \begin{CompactList}\small\item\em Constructor. \item\end{CompactList}\item \hypertarget{classmigamma_6cf801c0319ffcfc6317e9f2ecef4cf8}{ void \hyperlink{classmigamma_6cf801c0319ffcfc6317e9f2ecef4cf8}{set\_\-parameters} (double k0)} \label{classmigamma_6cf801c0319ffcfc6317e9f2ecef4cf8} \begin{CompactList}\small\item\em Set value of {\tt k}. \item\end{CompactList}\item \hypertarget{classmigamma_739c196dfcc586dec49043150da6ed0d}{ void \hyperlink{classmigamma_739c196dfcc586dec49043150da6ed0d}{condition} (const vec \&val)} \label{classmigamma_739c196dfcc586dec49043150da6ed0d} \begin{CompactList}\small\item\em Update {\tt ep} so that it represents this \hyperlink{classmpdf}{mpdf} conditioned on {\tt rvc} = cond. \item\end{CompactList}\item virtual vec \hyperlink{classmpdf_3f172b79ec4a5ebc87898a5381141f1b}{samplecond} (const vec \&cond, double \&ll) \begin{CompactList}\small\item\em Returns a sample from the density conditioned on {\tt cond}, $x \sim epdf(rv|cond)$. \item\end{CompactList}\item virtual mat \hyperlink{classmpdf_b1dae6171ee39a6a05976c7b1007a3c5}{samplecond\_\-m} (const vec \&cond, vec \&ll, int N) \begin{CompactList}\small\item\em Returns. \item\end{CompactList}\item \hypertarget{classmpdf_2ef8a6374029d990a678782f6decebbe}{ virtual double \hyperlink{classmpdf_2ef8a6374029d990a678782f6decebbe}{evallogcond} (const vec \&dt, const vec \&cond)} \label{classmpdf_2ef8a6374029d990a678782f6decebbe} \begin{CompactList}\small\item\em Shortcut for conditioning and evaluation of the internal \hyperlink{classepdf}{epdf}. In some cases, this operation can be implemented efficiently. \item\end{CompactList}\item \hypertarget{classmpdf_95fcff214848f66f1b489459370573fa}{ virtual vec \hyperlink{classmpdf_95fcff214848f66f1b489459370573fa}{evallogcond\_\-m} (const mat \&Dt, const vec \&cond)} \label{classmpdf_95fcff214848f66f1b489459370573fa} \begin{CompactList}\small\item\em Matrix version of evallogcond. \item\end{CompactList}\item \hypertarget{classmpdf_15ef062183b1ccdf794732d5fa0b77cd}{ \hyperlink{classRV}{RV} \hyperlink{classmpdf_15ef062183b1ccdf794732d5fa0b77cd}{\_\-rvc} () const } \label{classmpdf_15ef062183b1ccdf794732d5fa0b77cd} \begin{CompactList}\small\item\em access function \item\end{CompactList}\item \hypertarget{classmpdf_71256ffb5fbd08f41d650e606a5bd585}{ \hyperlink{classRV}{RV} \hyperlink{classmpdf_71256ffb5fbd08f41d650e606a5bd585}{\_\-rv} () const } \label{classmpdf_71256ffb5fbd08f41d650e606a5bd585} \begin{CompactList}\small\item\em access function \item\end{CompactList}\item \hypertarget{classmpdf_e17780ee5b2cfe05922a6c56af1462f8}{ \hyperlink{classepdf}{epdf} \& \hyperlink{classmpdf_e17780ee5b2cfe05922a6c56af1462f8}{\_\-epdf} ()} \label{classmpdf_e17780ee5b2cfe05922a6c56af1462f8} \begin{CompactList}\small\item\em access function \item\end{CompactList}\item \hypertarget{classmpdf_75ded3b0f657cd7da6590691a810963c}{ \hyperlink{classepdf}{epdf} $\ast$ \hyperlink{classmpdf_75ded3b0f657cd7da6590691a810963c}{\_\-e} ()} \label{classmpdf_75ded3b0f657cd7da6590691a810963c} \begin{CompactList}\small\item\em access function \item\end{CompactList}\end{CompactItemize} \subsection*{Protected Attributes} \begin{CompactItemize} \item \hypertarget{classmigamma_74712a98f587efdf35da540f7f5b5d0d}{ \hyperlink{classeigamma}{eigamma} \hyperlink{classmigamma_74712a98f587efdf35da540f7f5b5d0d}{epdf}} \label{classmigamma_74712a98f587efdf35da540f7f5b5d0d} \begin{CompactList}\small\item\em Internal \hyperlink{classepdf}{epdf} that arise by conditioning on {\tt rvc}. \item\end{CompactList}\item \hypertarget{classmigamma_8425bc642c6f7876b578e666c841fa9c}{ double \hyperlink{classmigamma_8425bc642c6f7876b578e666c841fa9c}{k}} \label{classmigamma_8425bc642c6f7876b578e666c841fa9c} \begin{CompactList}\small\item\em Constant $k$. \item\end{CompactList}\item \hypertarget{classmigamma_92c2e81705d8edb58181b61af75574e0}{ vec $\ast$ \hyperlink{classmigamma_92c2e81705d8edb58181b61af75574e0}{\_\-beta}} \label{classmigamma_92c2e81705d8edb58181b61af75574e0} \begin{CompactList}\small\item\em cache of epdf.beta \item\end{CompactList}\item \hypertarget{classmigamma_fb9bf89eb2c15fc267c97eef2218ebfa}{ vec $\ast$ \hyperlink{classmigamma_fb9bf89eb2c15fc267c97eef2218ebfa}{\_\-alpha}} \label{classmigamma_fb9bf89eb2c15fc267c97eef2218ebfa} \begin{CompactList}\small\item\em chaceh of epdf.alpha \item\end{CompactList}\item \hypertarget{classmpdf_f6687c07ff07d47812dd565368ca59eb}{ \hyperlink{classRV}{RV} \hyperlink{classmpdf_f6687c07ff07d47812dd565368ca59eb}{rv}} \label{classmpdf_f6687c07ff07d47812dd565368ca59eb} \begin{CompactList}\small\item\em modeled random variable \item\end{CompactList}\item \hypertarget{classmpdf_acb7dda792b3cd5576f39fa3129abbab}{ \hyperlink{classRV}{RV} \hyperlink{classmpdf_acb7dda792b3cd5576f39fa3129abbab}{rvc}} \label{classmpdf_acb7dda792b3cd5576f39fa3129abbab} \begin{CompactList}\small\item\em random variable in condition \item\end{CompactList}\item \hypertarget{classmpdf_7aa894208a32f3487827df6d5054424c}{ \hyperlink{classepdf}{epdf} $\ast$ \hyperlink{classmpdf_7aa894208a32f3487827df6d5054424c}{ep}} \label{classmpdf_7aa894208a32f3487827df6d5054424c} \begin{CompactList}\small\item\em pointer to internal \hyperlink{classepdf}{epdf} \item\end{CompactList}\end{CompactItemize} \subsection{Detailed Description} Inverse-Gamma random walk. Mean value, $\mu$, of this density is given by {\tt rvc} . Standard deviation of the random walk is proportional to one $k$-th the mean. This is achieved by setting $\alpha=\mu/k+2$ and $\beta=\mu(\alpha-1)$. The standard deviation of the walk is then: $\mu/\sqrt(k)$. \subsection{Member Function Documentation} \hypertarget{classmpdf_3f172b79ec4a5ebc87898a5381141f1b}{ \index{migamma@{migamma}!samplecond@{samplecond}} \index{samplecond@{samplecond}!migamma@{migamma}} \subsubsection[samplecond]{\setlength{\rightskip}{0pt plus 5cm}virtual vec mpdf::samplecond (const vec \& {\em cond}, \/ double \& {\em ll})\hspace{0.3cm}{\tt \mbox{[}inline, virtual, inherited\mbox{]}}}} \label{classmpdf_3f172b79ec4a5ebc87898a5381141f1b} Returns a sample from the density conditioned on {\tt cond}, $x \sim epdf(rv|cond)$. \begin{Desc} \item[Parameters:] \begin{description} \item[{\em cond}]is numeric value of {\tt rv} \item[{\em ll}]is a return value of log-likelihood of the sample. \end{description} \end{Desc} Reimplemented in \hyperlink{classmprod_a48887eb8738a9e5550bfc38eb8e9d68}{mprod}. References mpdf::condition(), mpdf::ep, epdf::evallog(), and epdf::sample(). Referenced by MPF$<$ BM\_\-T $>$::bayes(), and PF::bayes().\hypertarget{classmpdf_b1dae6171ee39a6a05976c7b1007a3c5}{ \index{migamma@{migamma}!samplecond\_\-m@{samplecond\_\-m}} \index{samplecond\_\-m@{samplecond\_\-m}!migamma@{migamma}} \subsubsection[samplecond\_\-m]{\setlength{\rightskip}{0pt plus 5cm}virtual mat mpdf::samplecond\_\-m (const vec \& {\em cond}, \/ vec \& {\em ll}, \/ int {\em N})\hspace{0.3cm}{\tt \mbox{[}inline, virtual, inherited\mbox{]}}}} \label{classmpdf_b1dae6171ee39a6a05976c7b1007a3c5} Returns. \begin{Desc} \item[Parameters:] \begin{description} \item[{\em N}]samples from the density conditioned on {\tt cond}, $x \sim epdf(rv|cond)$. \item[{\em cond}]is numeric value of {\tt rv} \item[{\em ll}]is a return value of log-likelihood of the sample. \end{description} \end{Desc} References mpdf::condition(), RV::count(), mpdf::ep, epdf::evallog(), mpdf::rv, and epdf::sample(). The documentation for this class was generated from the following file:\begin{CompactItemize} \item work/git/mixpp/bdm/stat/\hyperlink{libEF_8h}{libEF.h}\end{CompactItemize}