\hypertarget{classbdm_1_1migamma}{ \section{bdm::migamma Class Reference} \label{classbdm_1_1migamma}\index{bdm::migamma@{bdm::migamma}} } {\tt \#include $<$libEF.h$>$} Inheritance diagram for bdm::migamma::\begin{figure}[H] \begin{center} \leavevmode \includegraphics[height=5cm]{classbdm_1_1migamma} \end{center} \end{figure} \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+2 $ and $ \beta=\mu(\alpha-1)$. The standard deviation of the walk is then: $ \mu/\sqrt(k)$. \subsection*{Public Member Functions} \begin{CompactItemize} \item \hypertarget{classbdm_1_1migamma_8b10ab922e2a7bae2fb6bb3efc7b6151}{ void \hyperlink{classbdm_1_1migamma_8b10ab922e2a7bae2fb6bb3efc7b6151}{set\_\-parameters} (int len, double k0)} \label{classbdm_1_1migamma_8b10ab922e2a7bae2fb6bb3efc7b6151} \begin{CompactList}\small\item\em Set value of {\tt k}. \item\end{CompactList}\item \hypertarget{classbdm_1_1migamma_7a34b1e2e3aa2250d7c0ed7df1665b8c}{ void \hyperlink{classbdm_1_1migamma_7a34b1e2e3aa2250d7c0ed7df1665b8c}{condition} (const vec \&val)} \label{classbdm_1_1migamma_7a34b1e2e3aa2250d7c0ed7df1665b8c} \begin{CompactList}\small\item\em Update {\tt ep} so that it represents this \hyperlink{classbdm_1_1mpdf}{mpdf} conditioned on {\tt rvc} = cond. \item\end{CompactList}\end{CompactItemize} \begin{Indent}{\bf Constructors}\par \begin{CompactItemize} \item \hypertarget{classbdm_1_1migamma_b109fa502a9ab521dfb48412fd45fca7}{ \textbf{migamma} ()} \label{classbdm_1_1migamma_b109fa502a9ab521dfb48412fd45fca7} \item \hypertarget{classbdm_1_1migamma_a0126f741c6d2b6016df95a2410071e3}{ \textbf{migamma} (const \hyperlink{classbdm_1_1migamma}{migamma} \&m)} \label{classbdm_1_1migamma_a0126f741c6d2b6016df95a2410071e3} \end{CompactItemize} \end{Indent} \begin{Indent}{\bf Matematical operations}\par \begin{CompactItemize} \item virtual vec \hyperlink{classbdm_1_1mpdf_f0c1db6fcbb3aae2dd6123884457a367}{samplecond} (const vec \&cond) \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{classbdm_1_1mpdf_afe4185b26baeb03688202e254d3b005}{samplecond\_\-m} (const vec \&cond, int N) \begin{CompactList}\small\item\em Returns. \item\end{CompactList}\item \hypertarget{classbdm_1_1mpdf_6336a8a72462e2a56a3989a220f18b1b}{ virtual double \hyperlink{classbdm_1_1mpdf_6336a8a72462e2a56a3989a220f18b1b}{evallogcond} (const vec \&dt, const vec \&cond)} \label{classbdm_1_1mpdf_6336a8a72462e2a56a3989a220f18b1b} \begin{CompactList}\small\item\em Shortcut for conditioning and evaluation of the internal \hyperlink{classbdm_1_1epdf}{epdf}. In some cases, this operation can be implemented efficiently. \item\end{CompactList}\item \hypertarget{classbdm_1_1mpdf_0b0ed1ed663071bb7cf4a1349eb94fcb}{ virtual vec \hyperlink{classbdm_1_1mpdf_0b0ed1ed663071bb7cf4a1349eb94fcb}{evallogcond\_\-m} (const mat \&Dt, const vec \&cond)} \label{classbdm_1_1mpdf_0b0ed1ed663071bb7cf4a1349eb94fcb} \begin{CompactList}\small\item\em Matrix version of evallogcond. \item\end{CompactList}\end{CompactItemize} \end{Indent} \begin{Indent}{\bf Access to attributes}\par \begin{CompactItemize} \item \hypertarget{classbdm_1_1mpdf_5571482d150fbcb72cc36f6694ce1a10}{ \hyperlink{classbdm_1_1RV}{RV} \textbf{\_\-rv} ()} \label{classbdm_1_1mpdf_5571482d150fbcb72cc36f6694ce1a10} \item \hypertarget{classbdm_1_1mpdf_26001264236846897bd11e4baad47245}{ \hyperlink{classbdm_1_1RV}{RV} \textbf{\_\-rvc} ()} \label{classbdm_1_1mpdf_26001264236846897bd11e4baad47245} \item \hypertarget{classbdm_1_1mpdf_1c2bae3e1e90874e72941863974ec0ed}{ int \textbf{dimension} ()} \label{classbdm_1_1mpdf_1c2bae3e1e90874e72941863974ec0ed} \item \hypertarget{classbdm_1_1mpdf_35e135910aed187b7290742f50e61bc8}{ int \textbf{dimensionc} ()} \label{classbdm_1_1mpdf_35e135910aed187b7290742f50e61bc8} \item \hypertarget{classbdm_1_1mpdf_1892fe3933488942253679f068e9e7f6}{ \hyperlink{classbdm_1_1epdf}{epdf} \& \textbf{\_\-epdf} ()} \label{classbdm_1_1mpdf_1892fe3933488942253679f068e9e7f6} \item \hypertarget{classbdm_1_1mpdf_05e843fd11c410a99dad2b88c55aca80}{ \hyperlink{classbdm_1_1epdf}{epdf} $\ast$ \textbf{\_\-e} ()} \label{classbdm_1_1mpdf_05e843fd11c410a99dad2b88c55aca80} \end{CompactItemize} \end{Indent} \begin{Indent}{\bf Connection to other objects}\par \begin{CompactItemize} \item \hypertarget{classbdm_1_1mpdf_7631a5570e4ade1420065e8df78f4401}{ void \textbf{set\_\-rvc} (const \hyperlink{classbdm_1_1RV}{RV} \&rvc0)} \label{classbdm_1_1mpdf_7631a5570e4ade1420065e8df78f4401} \item \hypertarget{classbdm_1_1mpdf_18ac26bc2f96ae01ef4eb06178abbd75}{ void \textbf{set\_\-rv} (const \hyperlink{classbdm_1_1RV}{RV} \&rv0)} \label{classbdm_1_1mpdf_18ac26bc2f96ae01ef4eb06178abbd75} \item \hypertarget{classbdm_1_1mpdf_f8e3798150b42fd1f3e16ddbbe0e7045}{ bool \textbf{isnamed} ()} \label{classbdm_1_1mpdf_f8e3798150b42fd1f3e16ddbbe0e7045} \end{CompactItemize} \end{Indent} \subsection*{Protected Attributes} \begin{CompactItemize} \item \hypertarget{classbdm_1_1migamma_a31b39d4179551b593c9e0d7d756783a}{ \hyperlink{classbdm_1_1eigamma}{eigamma} \hyperlink{classbdm_1_1migamma_a31b39d4179551b593c9e0d7d756783a}{epdf}} \label{classbdm_1_1migamma_a31b39d4179551b593c9e0d7d756783a} \begin{CompactList}\small\item\em Internal \hyperlink{classbdm_1_1epdf}{epdf} that arise by conditioning on {\tt rvc}. \item\end{CompactList}\item \hypertarget{classbdm_1_1migamma_dc56bc9da542e0103ec16b9be8e5e38c}{ double \hyperlink{classbdm_1_1migamma_dc56bc9da542e0103ec16b9be8e5e38c}{k}} \label{classbdm_1_1migamma_dc56bc9da542e0103ec16b9be8e5e38c} \begin{CompactList}\small\item\em Constant $k$. \item\end{CompactList}\item \hypertarget{classbdm_1_1migamma_c9847093da59a9ba0ebb68d2c592f5dc}{ vec \& \hyperlink{classbdm_1_1migamma_c9847093da59a9ba0ebb68d2c592f5dc}{\_\-alpha}} \label{classbdm_1_1migamma_c9847093da59a9ba0ebb68d2c592f5dc} \begin{CompactList}\small\item\em cache of epdf.alpha \item\end{CompactList}\item \hypertarget{classbdm_1_1migamma_0d854c047001b5465cf1ba21f52904b5}{ vec \& \hyperlink{classbdm_1_1migamma_0d854c047001b5465cf1ba21f52904b5}{\_\-beta}} \label{classbdm_1_1migamma_0d854c047001b5465cf1ba21f52904b5} \begin{CompactList}\small\item\em cache of epdf.beta \item\end{CompactList}\item \hypertarget{classbdm_1_1mpdf_7c1900976ff13dbc09c9729b3bbff9e6}{ int \hyperlink{classbdm_1_1mpdf_7c1900976ff13dbc09c9729b3bbff9e6}{dimc}} \label{classbdm_1_1mpdf_7c1900976ff13dbc09c9729b3bbff9e6} \begin{CompactList}\small\item\em dimension of the condition \item\end{CompactList}\item \hypertarget{classbdm_1_1mpdf_5a5f08950daa08b85b01ddf4e1c36288}{ \hyperlink{classbdm_1_1RV}{RV} \hyperlink{classbdm_1_1mpdf_5a5f08950daa08b85b01ddf4e1c36288}{rvc}} \label{classbdm_1_1mpdf_5a5f08950daa08b85b01ddf4e1c36288} \begin{CompactList}\small\item\em random variable in condition \item\end{CompactList}\item \hypertarget{classbdm_1_1mpdf_5eea43c56d38e4441bfb30270db949c0}{ \hyperlink{classbdm_1_1epdf}{epdf} $\ast$ \hyperlink{classbdm_1_1mpdf_5eea43c56d38e4441bfb30270db949c0}{ep}} \label{classbdm_1_1mpdf_5eea43c56d38e4441bfb30270db949c0} \begin{CompactList}\small\item\em pointer to internal \hyperlink{classbdm_1_1epdf}{epdf} \item\end{CompactList}\end{CompactItemize} \subsection{Member Function Documentation} \hypertarget{classbdm_1_1mpdf_f0c1db6fcbb3aae2dd6123884457a367}{ \index{bdm::migamma@{bdm::migamma}!samplecond@{samplecond}} \index{samplecond@{samplecond}!bdm::migamma@{bdm::migamma}} \subsubsection[samplecond]{\setlength{\rightskip}{0pt plus 5cm}virtual vec bdm::mpdf::samplecond (const vec \& {\em cond})\hspace{0.3cm}{\tt \mbox{[}inline, virtual, inherited\mbox{]}}}} \label{classbdm_1_1mpdf_f0c1db6fcbb3aae2dd6123884457a367} 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} \end{description} \end{Desc} Reimplemented in \hyperlink{classbdm_1_1mprod_ee715a8013acf9892f6cb489db595555}{bdm::mprod}. References bdm::mpdf::condition(), bdm::mpdf::ep, and bdm::epdf::sample(). Referenced by bdm::MPF$<$ BM\_\-T $>$::bayes(), bdm::PF::bayes(), and bdm::ArxDS::step().\hypertarget{classbdm_1_1mpdf_afe4185b26baeb03688202e254d3b005}{ \index{bdm::migamma@{bdm::migamma}!samplecond\_\-m@{samplecond\_\-m}} \index{samplecond\_\-m@{samplecond\_\-m}!bdm::migamma@{bdm::migamma}} \subsubsection[samplecond\_\-m]{\setlength{\rightskip}{0pt plus 5cm}virtual mat bdm::mpdf::samplecond\_\-m (const vec \& {\em cond}, \/ int {\em N})\hspace{0.3cm}{\tt \mbox{[}inline, virtual, inherited\mbox{]}}}} \label{classbdm_1_1mpdf_afe4185b26baeb03688202e254d3b005} 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 bdm::mpdf::condition(), bdm::epdf::dimension(), bdm::mpdf::ep, and bdm::epdf::sample(). The documentation for this class was generated from the following file:\begin{CompactItemize} \item \hyperlink{libEF_8h}{libEF.h}\end{CompactItemize}