root/doc/latex/classeDirich.tex @ 181

Revision 181, 7.8 kB (checked in by smidl, 16 years ago)

Regenerated doc

RevLine 
[172]1\hypertarget{classeDirich}{
2\section{eDirich Class Reference}
3\label{classeDirich}\index{eDirich@{eDirich}}
4}
5Dirichlet posterior density. 
6
7
8{\tt \#include $<$libEF.h$>$}
9
10Inheritance diagram for eDirich:\nopagebreak
11\begin{figure}[H]
12\begin{center}
13\leavevmode
14\includegraphics[width=46pt]{classeDirich__inherit__graph}
15\end{center}
16\end{figure}
17Collaboration diagram for eDirich:\nopagebreak
18\begin{figure}[H]
19\begin{center}
20\leavevmode
21\includegraphics[width=46pt]{classeDirich__coll__graph}
22\end{center}
23\end{figure}
24\subsection*{Public Member Functions}
25\begin{CompactItemize}
26\item 
27\hypertarget{classeDirich_ac7e6116f3575c3860d07355e96cd4af}{
28\hyperlink{classeDirich_ac7e6116f3575c3860d07355e96cd4af}{eDirich} (const \hyperlink{classRV}{RV} \&\hyperlink{classepdf_74da992e3f5d598da8850b646b79b9d9}{rv}, const vec \&beta0)}
29\label{classeDirich_ac7e6116f3575c3860d07355e96cd4af}
30
31\begin{CompactList}\small\item\em Default constructor. \item\end{CompactList}\item 
32\hypertarget{classeDirich_55cccbc5eb44764dce722567acf5fd58}{
33\hyperlink{classeDirich_55cccbc5eb44764dce722567acf5fd58}{eDirich} (const \hyperlink{classeDirich}{eDirich} \&D0)}
34\label{classeDirich_55cccbc5eb44764dce722567acf5fd58}
35
36\begin{CompactList}\small\item\em Copy constructor. \item\end{CompactList}\item 
37\hypertarget{classeDirich_23dff79110822e9639343fe8e177fd80}{
38vec \hyperlink{classeDirich_23dff79110822e9639343fe8e177fd80}{sample} () const }
39\label{classeDirich_23dff79110822e9639343fe8e177fd80}
40
41\begin{CompactList}\small\item\em Returns a sample, $x$ from density $epdf(rv)$. \item\end{CompactList}\item 
42\hypertarget{classeDirich_4206e1da149d51ff3b663c9241096b73}{
43vec \hyperlink{classeDirich_4206e1da149d51ff3b663c9241096b73}{mean} () const }
44\label{classeDirich_4206e1da149d51ff3b663c9241096b73}
45
46\begin{CompactList}\small\item\em return expected value \item\end{CompactList}\item 
47\hypertarget{classeDirich_688a24f04be6d80d4769cf0e4ded7acc}{
48double \hyperlink{classeDirich_688a24f04be6d80d4769cf0e4ded7acc}{evalpdflog\_\-nn} (const vec \&val) const }
49\label{classeDirich_688a24f04be6d80d4769cf0e4ded7acc}
50
[180]51\begin{CompactList}\small\item\em In this instance, val is ... \item\end{CompactList}\item 
[172]52\hypertarget{classeDirich_7ce60be7119ffc639ede4e583c1f6e77}{
53double \hyperlink{classeDirich_7ce60be7119ffc639ede4e583c1f6e77}{lognc} () const }
54\label{classeDirich_7ce60be7119ffc639ede4e583c1f6e77}
55
56\begin{CompactList}\small\item\em logarithm of the normalizing constant, $\mathcal{I}$ \item\end{CompactList}\item 
57\hypertarget{classeDirich_6409d0362143a23976b43641ff19e53a}{
58vec \& \hyperlink{classeDirich_6409d0362143a23976b43641ff19e53a}{\_\-beta} ()}
59\label{classeDirich_6409d0362143a23976b43641ff19e53a}
60
61\begin{CompactList}\small\item\em access function \item\end{CompactList}\item 
[180]62\hypertarget{classeDirich_c842acb2e1cce5cc9000769ff06c086d}{
63void \hyperlink{classeDirich_c842acb2e1cce5cc9000769ff06c086d}{set\_\-parameters} (const vec \&beta0)}
64\label{classeDirich_c842acb2e1cce5cc9000769ff06c086d}
65
66\begin{CompactList}\small\item\em Set internal parameters. \item\end{CompactList}\item 
[172]67\hypertarget{classeEF_a89bef8996410609004fa019b5b48964}{
68virtual void \hyperlink{classeEF_a89bef8996410609004fa019b5b48964}{dupdate} (mat \&v)}
69\label{classeEF_a89bef8996410609004fa019b5b48964}
70
71\begin{CompactList}\small\item\em TODO decide if it is really needed. \item\end{CompactList}\item 
72\hypertarget{classeEF_6466e8d4aa9dd64698ed288cbb1afc03}{
73virtual double \hyperlink{classeEF_6466e8d4aa9dd64698ed288cbb1afc03}{evalpdflog} (const vec \&val) const }
74\label{classeEF_6466e8d4aa9dd64698ed288cbb1afc03}
75
76\begin{CompactList}\small\item\em Evaluate normalized log-probability. \item\end{CompactList}\item 
77\hypertarget{classeEF_c71faf4b2d153efda14bf1f87dca1507}{
78virtual vec \hyperlink{classeEF_c71faf4b2d153efda14bf1f87dca1507}{evalpdflog} (const mat \&Val) const }
79\label{classeEF_c71faf4b2d153efda14bf1f87dca1507}
80
81\begin{CompactList}\small\item\em Evaluate normalized log-probability for many samples. \item\end{CompactList}\item 
82\hypertarget{classeEF_4f8385dd1cc9740522dc373b1dc3cbf5}{
83virtual void \hyperlink{classeEF_4f8385dd1cc9740522dc373b1dc3cbf5}{pow} (double p)}
84\label{classeEF_4f8385dd1cc9740522dc373b1dc3cbf5}
85
86\begin{CompactList}\small\item\em Power of the density, used e.g. to flatten the density. \item\end{CompactList}\item 
87\hypertarget{classepdf_54d7dd53a641b618771cd9bee135181f}{
88virtual mat \hyperlink{classepdf_54d7dd53a641b618771cd9bee135181f}{sampleN} (int N) const }
89\label{classepdf_54d7dd53a641b618771cd9bee135181f}
90
91\begin{CompactList}\small\item\em Returns N samples from density $epdf(rv)$. \item\end{CompactList}\item 
92\hypertarget{classepdf_3ea597362e11a0040fe7c990269d072c}{
93virtual double \hyperlink{classepdf_3ea597362e11a0040fe7c990269d072c}{eval} (const vec \&val) const }
94\label{classepdf_3ea597362e11a0040fe7c990269d072c}
95
96\begin{CompactList}\small\item\em Compute probability of argument {\tt val}. \item\end{CompactList}\item 
[180]97\hypertarget{classepdf_cebbdd7a85e6328f7358fc0ba8eee06c}{
98virtual vec \hyperlink{classepdf_cebbdd7a85e6328f7358fc0ba8eee06c}{evalpdflog\_\-m} (const mat \&Val) const }
99\label{classepdf_cebbdd7a85e6328f7358fc0ba8eee06c}
100
101\begin{CompactList}\small\item\em Compute log-probability of multiple values argument {\tt val}. \item\end{CompactList}\item 
[181]102\hypertarget{classepdf_3ba08c0e788deff22134c049b9269666}{
103\hyperlink{classmpdf}{mpdf} $\ast$ \hyperlink{classepdf_3ba08c0e788deff22134c049b9269666}{condition} (const \hyperlink{classRV}{RV} \&\hyperlink{classepdf_74da992e3f5d598da8850b646b79b9d9}{rv})}
104\label{classepdf_3ba08c0e788deff22134c049b9269666}
105
106\begin{CompactList}\small\item\em Return conditional density on the given \hyperlink{classRV}{RV}, the remaining rvs will be in conditioning. \item\end{CompactList}\item 
107\hypertarget{classepdf_bc0c171b6dafacd78d26263913b1d0c0}{
108\hyperlink{classepdf}{epdf} $\ast$ \hyperlink{classepdf_bc0c171b6dafacd78d26263913b1d0c0}{marginal} (const \hyperlink{classRV}{RV} \&\hyperlink{classepdf_74da992e3f5d598da8850b646b79b9d9}{rv})}
109\label{classepdf_bc0c171b6dafacd78d26263913b1d0c0}
110
111\begin{CompactList}\small\item\em Return marginal density on the given \hyperlink{classRV}{RV}, the remainig rvs are intergrated out. \item\end{CompactList}\item 
[172]112\hypertarget{classepdf_ca0d32aabb4cbba347e0c37fe8607562}{
113const \hyperlink{classRV}{RV} \& \hyperlink{classepdf_ca0d32aabb4cbba347e0c37fe8607562}{\_\-rv} () const }
114\label{classepdf_ca0d32aabb4cbba347e0c37fe8607562}
115
116\begin{CompactList}\small\item\em access function, possibly dangerous! \item\end{CompactList}\item 
117\hypertarget{classepdf_7fb94ce90d1ac7077d29f7d6a6c3e0a5}{
118void \hyperlink{classepdf_7fb94ce90d1ac7077d29f7d6a6c3e0a5}{\_\-renewrv} (const \hyperlink{classRV}{RV} \&in\_\-rv)}
119\label{classepdf_7fb94ce90d1ac7077d29f7d6a6c3e0a5}
120
121\begin{CompactList}\small\item\em modifier function - useful when copying epdfs \item\end{CompactList}\end{CompactItemize}
122\subsection*{Protected Attributes}
123\begin{CompactItemize}
124\item 
125\hypertarget{classeDirich_15e6b65e9595eedc8a1286c6cecd36d7}{
126vec \hyperlink{classeDirich_15e6b65e9595eedc8a1286c6cecd36d7}{beta}}
127\label{classeDirich_15e6b65e9595eedc8a1286c6cecd36d7}
128
129\begin{CompactList}\small\item\em sufficient statistics \item\end{CompactList}\item 
130\hypertarget{classepdf_74da992e3f5d598da8850b646b79b9d9}{
131\hyperlink{classRV}{RV} \hyperlink{classepdf_74da992e3f5d598da8850b646b79b9d9}{rv}}
132\label{classepdf_74da992e3f5d598da8850b646b79b9d9}
133
134\begin{CompactList}\small\item\em Identified of the random variable. \item\end{CompactList}\end{CompactItemize}
135
136
137\subsection{Detailed Description}
138Dirichlet posterior density.
139
140Continuous Dirichlet density of $n$-dimensional variable $x$ \[ f(x|\beta) = \frac{\Gamma[\gamma]}{\prod_{i=1}^{n}\Gamma(\beta_i)} \prod_{i=1}^{n}x_i^{\beta_i-1} \] where $\gamma=\sum_i \beta_i$.
141
142The documentation for this class was generated from the following file:\begin{CompactItemize}
143\item 
144work/git/mixpp/bdm/stat/\hyperlink{libEF_8h}{libEF.h}\end{CompactItemize}
Note: See TracBrowser for help on using the browser.