root/doc/latex/classbdm_1_1migamma.tex @ 275

\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}