root/doc/latex/classbdm_1_1mlstudent.tex @ 271

\hypertarget{classbdm_1_1mlstudent}{
\section{bdm::mlstudent Class Reference}
\label{classbdm_1_1mlstudent}\index{bdm::mlstudent@{bdm::mlstudent}}
}
{\tt \#include $<$libEF.h$>$}

Inheritance diagram for bdm::mlstudent::\begin{figure}[H]
\begin{center}
\leavevmode
\includegraphics[height=5cm]{classbdm_1_1mlstudent}
\end{center}
\end{figure}


\subsection{Detailed Description}
(Approximate) Student t density with linear function of mean value

The internal \hyperlink{classbdm_1_1epdf}{epdf} of this class is of the type of a Gaussian (\hyperlink{classbdm_1_1enorm}{enorm}). However, each conditioning is trying to assure the best possible approximation by taking into account the zeta function. See \mbox{[}\mbox{]} for reference.

Perhaps a moment-matching technique? \subsection*{Public Member Functions}
\begin{CompactItemize}
\item 
\hypertarget{classbdm_1_1mlstudent_4cdf79aac1b2165c0290e73810a0e4a3}{
void \textbf{set\_\-parameters} (const mat \&A0, const vec \&mu0, const \hyperlink{classldmat}{ldmat} \&R0, const \hyperlink{classldmat}{ldmat} \&Lambda0)}
\label{classbdm_1_1mlstudent_4cdf79aac1b2165c0290e73810a0e4a3}

\item 
void \hyperlink{classbdm_1_1mlstudent_efd37560585c8613897f30d3c2f58d0d}{condition} (const vec \&cond)
\item 
\hypertarget{classbdm_1_1mlnorm_56e587952f94fcac6cfc999eae6dbced}{
vec \& \hyperlink{classbdm_1_1mlnorm_56e587952f94fcac6cfc999eae6dbced}{\_\-mu\_\-const} ()}
\label{classbdm_1_1mlnorm_56e587952f94fcac6cfc999eae6dbced}

\begin{CompactList}\small\item\em access function \item\end{CompactList}\item 
\hypertarget{classbdm_1_1mlnorm_262a2a486bff585f34bb6a5005b02614}{
mat \& \hyperlink{classbdm_1_1mlnorm_262a2a486bff585f34bb6a5005b02614}{\_\-A} ()}
\label{classbdm_1_1mlnorm_262a2a486bff585f34bb6a5005b02614}

\begin{CompactList}\small\item\em access function \item\end{CompactList}\item 
\hypertarget{classbdm_1_1mlnorm_78120ecd1c2b1d7e80124b4603504604}{
mat \hyperlink{classbdm_1_1mlnorm_78120ecd1c2b1d7e80124b4603504604}{\_\-R} ()}
\label{classbdm_1_1mlnorm_78120ecd1c2b1d7e80124b4603504604}

\begin{CompactList}\small\item\em access function \item\end{CompactList}\end{CompactItemize}
\begin{Indent}{\bf Constructors}\par
\begin{CompactItemize}
\item 
\hypertarget{classbdm_1_1mlnorm_5d18dec3167584338a4775c1d165d96f}{
void \hyperlink{classbdm_1_1mlnorm_5d18dec3167584338a4775c1d165d96f}{set\_\-parameters} (const mat \&A, const vec \&mu0, const \hyperlink{classldmat}{ldmat} \&R)}
\label{classbdm_1_1mlnorm_5d18dec3167584338a4775c1d165d96f}

\begin{CompactList}\small\item\em Set {\tt A} and {\tt R}. \item\end{CompactList}\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_1mlstudent_41595144a79594acbe288c6b59412657}{
\hyperlink{classldmat}{ldmat} \textbf{Lambda}}
\label{classbdm_1_1mlstudent_41595144a79594acbe288c6b59412657}

\item 
\hypertarget{classbdm_1_1mlstudent_72e9bda4d6684e07faafc4b2192daf39}{
\hyperlink{classldmat}{ldmat} \& \textbf{\_\-R}}
\label{classbdm_1_1mlstudent_72e9bda4d6684e07faafc4b2192daf39}

\item 
\hypertarget{classbdm_1_1mlstudent_1c063ad6cb6e079ee11bc4128c2c9fe8}{
\hyperlink{classldmat}{ldmat} \textbf{Re}}
\label{classbdm_1_1mlstudent_1c063ad6cb6e079ee11bc4128c2c9fe8}

\item 
\hypertarget{classbdm_1_1mlnorm_150ad6acb223b0a0abeaf92346686dcd}{
\hyperlink{classbdm_1_1enorm}{enorm}$<$ \hyperlink{classldmat}{ldmat} $>$ \hyperlink{classbdm_1_1mlnorm_150ad6acb223b0a0abeaf92346686dcd}{epdf}}
\label{classbdm_1_1mlnorm_150ad6acb223b0a0abeaf92346686dcd}

\begin{CompactList}\small\item\em Internal epdf that arise by conditioning on {\tt rvc}. \item\end{CompactList}\item 
\hypertarget{classbdm_1_1mlnorm_8207ae86d1722102897e139a23e29af8}{
mat \textbf{A}}
\label{classbdm_1_1mlnorm_8207ae86d1722102897e139a23e29af8}

\item 
\hypertarget{classbdm_1_1mlnorm_3a019144d414d1737aea331ffe1c3845}{
vec \textbf{mu\_\-const}}
\label{classbdm_1_1mlnorm_3a019144d414d1737aea331ffe1c3845}

\item 
\hypertarget{classbdm_1_1mlnorm_dea5ea658d5020c11da91275f592244b}{
vec \& \textbf{\_\-mu}}
\label{classbdm_1_1mlnorm_dea5ea658d5020c11da91275f592244b}

\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*{Friends}
\begin{CompactItemize}
\item 
\hypertarget{classbdm_1_1mlnorm_1917009347bb410f73bf827df8767b09}{
std::ostream \& \textbf{operator$<$$<$} (std::ostream \&os, \hyperlink{classbdm_1_1mlnorm}{mlnorm}$<$ sq\_\-M $>$ \&ml)}
\label{classbdm_1_1mlnorm_1917009347bb410f73bf827df8767b09}

\end{CompactItemize}


\subsection{Member Function Documentation}
\hypertarget{classbdm_1_1mlstudent_efd37560585c8613897f30d3c2f58d0d}{
\index{bdm::mlstudent@{bdm::mlstudent}!condition@{condition}}
\index{condition@{condition}!bdm::mlstudent@{bdm::mlstudent}}
\subsubsection[condition]{\setlength{\rightskip}{0pt plus 5cm}void bdm::mlstudent::condition (const vec \& {\em cond})\hspace{0.3cm}{\tt  \mbox{[}inline, virtual\mbox{]}}}}
\label{classbdm_1_1mlstudent_efd37560585c8613897f30d3c2f58d0d}


Set value of {\tt rvc} . Result of this operation is stored in {\tt \hyperlink{classbdm_1_1epdf}{epdf}} use function {\tt \_\-ep} to access it. 

Reimplemented from \hyperlink{classbdm_1_1mlnorm_0dafc0196e7e07fd06dc6716e0e18bc2}{bdm::mlnorm$<$ ldmat $>$}.

References bdm::mlnorm$<$ ldmat $>$::\_\-R(), ldmat::invqform(), and ldmat::rows().\hypertarget{classbdm_1_1mpdf_f0c1db6fcbb3aae2dd6123884457a367}{
\index{bdm::mlstudent@{bdm::mlstudent}!samplecond@{samplecond}}
\index{samplecond@{samplecond}!bdm::mlstudent@{bdm::mlstudent}}
\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::mlstudent@{bdm::mlstudent}!samplecond\_\-m@{samplecond\_\-m}}
\index{samplecond\_\-m@{samplecond\_\-m}!bdm::mlstudent@{bdm::mlstudent}}
\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}