\section{mgamma Class Reference} \label{classmgamma}\index{mgamma@{mgamma}} Gamma random walk. {\tt \#include $<$libEF.h$>$} Collaboration diagram for mgamma:\nopagebreak \begin{figure}[H] \begin{center} \leavevmode \includegraphics[width=54pt]{classmgamma__coll__graph} \end{center} \end{figure} \subsection*{Public Member Functions} \begin{CompactItemize} \item {\bf mgamma} (const {\bf RV} \&rv, const {\bf RV} \&rvc)\label{classmgamma_af43e61b86900c0398d5c0ffc83b94e6} \begin{CompactList}\small\item\em Constructor. \item\end{CompactList}\item void \textbf{set\_\-parameters} (double k)\label{classmgamma_a9d646cf758a70126dde7c48790b6e94} \item vec {\bf samplecond} (vec \&cond, double \&lik)\label{classmgamma_9f40dc43885085fad8e3d6652b79e139} \begin{CompactList}\small\item\em Generate one sample of the posterior. \item\end{CompactList}\item mat {\bf samplecond} (vec \&cond, vec \&lik, int n)\label{classmgamma_e9d52749793f40aad85b70c6db4435ae} \begin{CompactList}\small\item\em Generate matrix of samples of the posterior. \item\end{CompactList}\item void \textbf{condition} (const vec \&val)\label{classmgamma_a61094c9f7a2d64ea77b130cbc031f97} \end{CompactItemize} \subsection{Detailed Description} Gamma random walk. Mean value, \$\$, 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 \$=k\$ and \$=k/\$. The standard deviation of the walk is then: \$/(k)\$. The documentation for this class was generated from the following files:\begin{CompactItemize} \item work/mixpp/bdm/stat/{\bf libEF.h}\item work/mixpp/bdm/stat/libEF.cpp\end{CompactItemize}