| 1 | \section{egiw Class Reference} |
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| 2 | \label{classegiw}\index{egiw@{egiw}} |
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| 3 | Gauss-inverse-Wishart density stored in LD form. |
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| 4 | |
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| 5 | |
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| 6 | {\tt \#include $<$libEF.h$>$} |
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| 7 | |
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| 8 | Inheritance diagram for egiw:\nopagebreak |
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| 9 | \begin{figure}[H] |
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| 10 | \begin{center} |
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| 11 | \leavevmode |
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| 12 | \includegraphics[width=40pt]{classegiw__inherit__graph} |
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| 13 | \end{center} |
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| 14 | \end{figure} |
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| 15 | Collaboration diagram for egiw:\nopagebreak |
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| 16 | \begin{figure}[H] |
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| 17 | \begin{center} |
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| 18 | \leavevmode |
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| 19 | \includegraphics[width=69pt]{classegiw__coll__graph} |
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| 20 | \end{center} |
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| 21 | \end{figure} |
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| 22 | \subsection*{Public Member Functions} |
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| 23 | \begin{CompactItemize} |
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| 24 | \item |
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| 25 | {\bf egiw} ({\bf RV} {\bf rv}, mat V0, double nu0)\label{classegiw_c52a2173c6eb1490edce9c6c7c05d60b} |
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| 26 | |
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| 27 | \begin{CompactList}\small\item\em Default constructor. \item\end{CompactList}\item |
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| 28 | vec {\bf sample} () const |
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| 29 | \begin{CompactList}\small\item\em Returns the required moment of the \doxyref{epdf}{p.}{classepdf}. \item\end{CompactList}\item |
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| 30 | vec {\bf mean} () const \label{classegiw_6deb0ff2859f41ef7cbdf6a842cabb29} |
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| 31 | |
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| 32 | \begin{CompactList}\small\item\em return expected value \item\end{CompactList}\item |
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| 33 | double {\bf evalpdflog} (const vec \&val) const \label{classegiw_425cbc53b377274e28c6add942bab62d} |
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| 34 | |
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| 35 | \begin{CompactList}\small\item\em Compute log-probability of argument {\tt val}. \item\end{CompactList}\item |
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| 36 | double {\bf lognc} () const \label{classegiw_70eb1a0b88459b227f919b425b0d3359} |
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| 37 | |
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| 38 | \begin{CompactList}\small\item\em logarithm of the normalizing constant, $\mathcal{I}$ \item\end{CompactList}\item |
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| 39 | {\bf ldmat} \& {\bf \_\-V} ()\label{classegiw_533e792e1175bfa06d5d595dc5d080d5} |
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| 40 | |
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| 41 | \begin{CompactList}\small\item\em returns a pointer to the internal statistics. Use with Care! \item\end{CompactList}\item |
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| 42 | double \& {\bf \_\-nu} ()\label{classegiw_08029c481ff95d24f093df0573879afe} |
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| 43 | |
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| 44 | \begin{CompactList}\small\item\em returns a pointer to the internal statistics. Use with Care! \item\end{CompactList}\item |
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| 45 | virtual void {\bf tupdate} (double phi, mat \&vbar, double nubar)\label{classeEF_fd88bc35550ec8fe9281d358216d0fcf} |
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| 46 | |
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| 47 | \begin{CompactList}\small\item\em TODO decide if it is really needed. \item\end{CompactList}\item |
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| 48 | virtual void {\bf dupdate} (mat \&v, double {\bf nu}=1.0)\label{classeEF_5863718c3b2fb1496dece10c5b745d5c} |
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| 49 | |
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| 50 | \begin{CompactList}\small\item\em TODO decide if it is really needed. \item\end{CompactList}\item |
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| 51 | virtual mat {\bf sampleN} (int N) const \label{classepdf_54d7dd53a641b618771cd9bee135181f} |
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| 52 | |
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| 53 | \begin{CompactList}\small\item\em Returns N samples from density $epdf(rv)$. \item\end{CompactList}\item |
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| 54 | virtual double {\bf eval} (const vec \&val) const \label{classepdf_3ea597362e11a0040fe7c990269d072c} |
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| 55 | |
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| 56 | \begin{CompactList}\small\item\em Compute probability of argument {\tt val}. \item\end{CompactList}\item |
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| 57 | {\bf RV} \& {\bf \_\-rv} ()\label{classepdf_4778ea61ef400813e47750e024e9fc2f} |
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| 58 | |
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| 59 | \begin{CompactList}\small\item\em access function, possibly dangerous! \item\end{CompactList}\end{CompactItemize} |
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| 60 | \subsection*{Protected Attributes} |
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| 61 | \begin{CompactItemize} |
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| 62 | \item |
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| 63 | {\bf ldmat} {\bf V}\label{classegiw_f343d03ede89db820edf44a6297fa442} |
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| 64 | |
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| 65 | \begin{CompactList}\small\item\em Extended information matrix of sufficient statistics. \item\end{CompactList}\item |
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| 66 | double {\bf nu}\label{classegiw_4a2f130b91afe84f6d62fed289d5d453} |
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| 67 | |
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| 68 | \begin{CompactList}\small\item\em Number of data records (degrees of freedom) of sufficient statistics. \item\end{CompactList}\item |
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| 69 | {\bf RV} {\bf rv}\label{classepdf_74da992e3f5d598da8850b646b79b9d9} |
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| 70 | |
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| 71 | \begin{CompactList}\small\item\em Identified of the random variable. \item\end{CompactList}\end{CompactItemize} |
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| 72 | |
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| 73 | |
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| 74 | \subsection{Detailed Description} |
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| 75 | Gauss-inverse-Wishart density stored in LD form. |
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| 76 | |
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| 77 | More?... |
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| 78 | |
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| 79 | \subsection{Member Function Documentation} |
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| 80 | \index{egiw@{egiw}!sample@{sample}} |
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| 81 | \index{sample@{sample}!egiw@{egiw}} |
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| 82 | \subsubsection[sample]{\setlength{\rightskip}{0pt plus 5cm}vec egiw::sample () const\hspace{0.3cm}{\tt [virtual]}}\label{classegiw_3d2c1f2ba0f9966781f1e0ae695e8a6f} |
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| 83 | |
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| 84 | |
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| 85 | Returns the required moment of the \doxyref{epdf}{p.}{classepdf}. |
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| 86 | |
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| 87 | Returns a sample, $x$ from density $epdf(rv)$ |
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| 88 | |
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| 89 | Implements {\bf epdf} \doxyref{}{p.}{classepdf_8019654e494bf5e458f6fb947e11b262}. |
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| 90 | |
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| 91 | The documentation for this class was generated from the following files:\begin{CompactItemize} |
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| 92 | \item |
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| 93 | work/git/mixpp/bdm/stat/{\bf libEF.h}\item |
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| 94 | work/git/mixpp/bdm/stat/libEF.cpp\end{CompactItemize} |
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