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1\hypertarget{classbdm_1_1egiw}{
2\section{bdm::egiw Class Reference}
3\label{classbdm_1_1egiw}\index{bdm::egiw@{bdm::egiw}}
4}
5Gauss-inverse-Wishart density stored in LD form. 
6
7
8{\tt \#include $<$libEF.h$>$}
9
10Inheritance diagram for bdm::egiw:\nopagebreak
11\begin{figure}[H]
12\begin{center}
13\leavevmode
14\includegraphics[width=64pt]{classbdm_1_1egiw__inherit__graph}
15\end{center}
16\end{figure}
17Collaboration diagram for bdm::egiw:\nopagebreak
18\begin{figure}[H]
19\begin{center}
20\leavevmode
21\includegraphics[width=89pt]{classbdm_1_1egiw__coll__graph}
22\end{center}
23\end{figure}
24\subsection*{Public Member Functions}
25\begin{CompactItemize}
26\item 
27\hypertarget{classbdm_1_1egiw_a60e072c191acf65ab480deeb11c5b88}{
28\hyperlink{classbdm_1_1egiw_a60e072c191acf65ab480deeb11c5b88}{egiw} (\hyperlink{classbdm_1_1RV}{RV} \hyperlink{classbdm_1_1epdf_62c5b8ff71d9ebe6cd58d3c342eb1dc8}{rv}, mat V0, double nu0=-1.0)}
29\label{classbdm_1_1egiw_a60e072c191acf65ab480deeb11c5b88}
30
31\begin{CompactList}\small\item\em Default constructor, if nu0$<$0 a minimal nu0 will be computed. \item\end{CompactList}\item 
32\hypertarget{classbdm_1_1egiw_bc3db93cb60dd29187eb3c6cfd557f97}{
33\hyperlink{classbdm_1_1egiw_bc3db93cb60dd29187eb3c6cfd557f97}{egiw} (\hyperlink{classbdm_1_1RV}{RV} \hyperlink{classbdm_1_1epdf_62c5b8ff71d9ebe6cd58d3c342eb1dc8}{rv}, \hyperlink{classldmat}{ldmat} V0, double nu0=-1.0)}
34\label{classbdm_1_1egiw_bc3db93cb60dd29187eb3c6cfd557f97}
35
36\begin{CompactList}\small\item\em Full constructor for V in \hyperlink{classldmat}{ldmat} form. \item\end{CompactList}\item 
37\hypertarget{classbdm_1_1egiw_920f21548b7a3723923dd108fe514c61}{
38vec \hyperlink{classbdm_1_1egiw_920f21548b7a3723923dd108fe514c61}{sample} () const }
39\label{classbdm_1_1egiw_920f21548b7a3723923dd108fe514c61}
40
41\begin{CompactList}\small\item\em Returns a sample, $x$ from density $epdf(rv)$. \item\end{CompactList}\item 
42\hypertarget{classbdm_1_1egiw_df70c05f918c3a6f86d60f10c1fd6ba2}{
43vec \hyperlink{classbdm_1_1egiw_df70c05f918c3a6f86d60f10c1fd6ba2}{mean} () const }
44\label{classbdm_1_1egiw_df70c05f918c3a6f86d60f10c1fd6ba2}
45
46\begin{CompactList}\small\item\em return expected value \item\end{CompactList}\item 
47\hypertarget{classbdm_1_1egiw_c1ecc406613cc2341225dc10c3d3b46a}{
48vec \hyperlink{classbdm_1_1egiw_c1ecc406613cc2341225dc10c3d3b46a}{variance} () const }
49\label{classbdm_1_1egiw_c1ecc406613cc2341225dc10c3d3b46a}
50
51\begin{CompactList}\small\item\em return expected variance (not covariance!) \item\end{CompactList}\item 
52\hypertarget{classbdm_1_1egiw_d2075aa2306648b3e4fe40bb86628d5c}{
53void \textbf{mean\_\-mat} (mat \&M, mat \&R) const }
54\label{classbdm_1_1egiw_d2075aa2306648b3e4fe40bb86628d5c}
55
56\item 
57\hypertarget{classbdm_1_1egiw_bfb8e7c619b34ad804a73bff71742b5e}{
58double \hyperlink{classbdm_1_1egiw_bfb8e7c619b34ad804a73bff71742b5e}{evallog\_\-nn} (const vec \&val) const }
59\label{classbdm_1_1egiw_bfb8e7c619b34ad804a73bff71742b5e}
60
61\begin{CompactList}\small\item\em In this instance, val= \mbox{[}theta, r\mbox{]}. For multivariate instances, it is stored columnwise val = \mbox{[}theta\_\-1 theta\_\-2 ... r\_\-1 r\_\-2 \mbox{]}. \item\end{CompactList}\item 
62\hypertarget{classbdm_1_1egiw_41d72ba7b2abc8a9a4209ffa98ed5633}{
63double \hyperlink{classbdm_1_1egiw_41d72ba7b2abc8a9a4209ffa98ed5633}{lognc} () const }
64\label{classbdm_1_1egiw_41d72ba7b2abc8a9a4209ffa98ed5633}
65
66\begin{CompactList}\small\item\em logarithm of the normalizing constant, $\mathcal{I}$ \item\end{CompactList}\item 
67\hypertarget{classbdm_1_1egiw_15792f3112e5cf67d572f491b09324c8}{
68\hyperlink{classldmat}{ldmat} \& \hyperlink{classbdm_1_1egiw_15792f3112e5cf67d572f491b09324c8}{\_\-V} ()}
69\label{classbdm_1_1egiw_15792f3112e5cf67d572f491b09324c8}
70
71\begin{CompactList}\small\item\em returns a pointer to the internal statistics. Use with Care! \item\end{CompactList}\item 
72\hypertarget{classbdm_1_1egiw_ad9c539a80a552e837245ddcebcbbba4}{
73const \hyperlink{classldmat}{ldmat} \& \hyperlink{classbdm_1_1egiw_ad9c539a80a552e837245ddcebcbbba4}{\_\-V} () const }
74\label{classbdm_1_1egiw_ad9c539a80a552e837245ddcebcbbba4}
75
76\begin{CompactList}\small\item\em returns a pointer to the internal statistics. Use with Care! \item\end{CompactList}\item 
77\hypertarget{classbdm_1_1egiw_a025ee710274ca142dd0ae978735ad4a}{
78double \& \hyperlink{classbdm_1_1egiw_a025ee710274ca142dd0ae978735ad4a}{\_\-nu} ()}
79\label{classbdm_1_1egiw_a025ee710274ca142dd0ae978735ad4a}
80
81\begin{CompactList}\small\item\em returns a pointer to the internal statistics. Use with Care! \item\end{CompactList}\item 
82\hypertarget{classbdm_1_1egiw_cf3b2bcb158c15c24788bba90e4154e4}{
83const double \& \textbf{\_\-nu} () const }
84\label{classbdm_1_1egiw_cf3b2bcb158c15c24788bba90e4154e4}
85
86\item 
87\hypertarget{classbdm_1_1egiw_8e610e95401a11baf34f65e16ecd87be}{
88void \hyperlink{classbdm_1_1egiw_8e610e95401a11baf34f65e16ecd87be}{pow} (double p)}
89\label{classbdm_1_1egiw_8e610e95401a11baf34f65e16ecd87be}
90
91\begin{CompactList}\small\item\em Power of the density, used e.g. to flatten the density. \item\end{CompactList}\item 
92\hypertarget{classbdm_1_1eEF_deef7d6273ba4d5a5cf0bbd91ec7277a}{
93virtual void \hyperlink{classbdm_1_1eEF_deef7d6273ba4d5a5cf0bbd91ec7277a}{dupdate} (mat \&v)}
94\label{classbdm_1_1eEF_deef7d6273ba4d5a5cf0bbd91ec7277a}
95
96\begin{CompactList}\small\item\em TODO decide if it is really needed. \item\end{CompactList}\item 
97\hypertarget{classbdm_1_1eEF_a36d06ecdd6f4c79dc122510eaccc692}{
98virtual double \hyperlink{classbdm_1_1eEF_a36d06ecdd6f4c79dc122510eaccc692}{evallog} (const vec \&val) const }
99\label{classbdm_1_1eEF_a36d06ecdd6f4c79dc122510eaccc692}
100
101\begin{CompactList}\small\item\em Evaluate normalized log-probability. \item\end{CompactList}\item 
102\hypertarget{classbdm_1_1eEF_79a7c8ea8c02e45d410bd1d7ffd72b41}{
103virtual vec \hyperlink{classbdm_1_1eEF_79a7c8ea8c02e45d410bd1d7ffd72b41}{evallog} (const mat \&Val) const }
104\label{classbdm_1_1eEF_79a7c8ea8c02e45d410bd1d7ffd72b41}
105
106\begin{CompactList}\small\item\em Evaluate normalized log-probability for many samples. \item\end{CompactList}\item 
107\hypertarget{classbdm_1_1epdf_b4cf45fd83cc7573ede9fe1215256058}{
108virtual mat \hyperlink{classbdm_1_1epdf_b4cf45fd83cc7573ede9fe1215256058}{sample\_\-m} (int N) const }
109\label{classbdm_1_1epdf_b4cf45fd83cc7573ede9fe1215256058}
110
111\begin{CompactList}\small\item\em Returns N samples from density $epdf(rv)$. \item\end{CompactList}\item 
112\hypertarget{classbdm_1_1epdf_34956d4dd3176eeb5937cf48a1546b62}{
113virtual vec \hyperlink{classbdm_1_1epdf_34956d4dd3176eeb5937cf48a1546b62}{evallog\_\-m} (const mat \&Val) const }
114\label{classbdm_1_1epdf_34956d4dd3176eeb5937cf48a1546b62}
115
116\begin{CompactList}\small\item\em Compute log-probability of multiple values argument {\tt val}. \item\end{CompactList}\item 
117\hypertarget{classbdm_1_1epdf_e584eac5579c1b6384947ecf66166c77}{
118virtual \hyperlink{classbdm_1_1mpdf}{mpdf} $\ast$ \hyperlink{classbdm_1_1epdf_e584eac5579c1b6384947ecf66166c77}{condition} (const \hyperlink{classbdm_1_1RV}{RV} \&\hyperlink{classbdm_1_1epdf_62c5b8ff71d9ebe6cd58d3c342eb1dc8}{rv}) const }
119\label{classbdm_1_1epdf_e584eac5579c1b6384947ecf66166c77}
120
121\begin{CompactList}\small\item\em Return conditional density on the given \hyperlink{classbdm_1_1RV}{RV}, the remaining rvs will be in conditioning. \item\end{CompactList}\item 
122\hypertarget{classbdm_1_1epdf_3fb2ece54f720b62ad325e61214fa0a1}{
123virtual \hyperlink{classbdm_1_1epdf}{epdf} $\ast$ \hyperlink{classbdm_1_1epdf_3fb2ece54f720b62ad325e61214fa0a1}{marginal} (const \hyperlink{classbdm_1_1RV}{RV} \&\hyperlink{classbdm_1_1epdf_62c5b8ff71d9ebe6cd58d3c342eb1dc8}{rv}) const }
124\label{classbdm_1_1epdf_3fb2ece54f720b62ad325e61214fa0a1}
125
126\begin{CompactList}\small\item\em Return marginal density on the given \hyperlink{classbdm_1_1RV}{RV}, the remainig rvs are intergrated out. \item\end{CompactList}\item 
127\hypertarget{classbdm_1_1epdf_a4ab378d5e004c3ff3e2d4e64f7bba21}{
128const \hyperlink{classbdm_1_1RV}{RV} \& \hyperlink{classbdm_1_1epdf_a4ab378d5e004c3ff3e2d4e64f7bba21}{\_\-rv} () const }
129\label{classbdm_1_1epdf_a4ab378d5e004c3ff3e2d4e64f7bba21}
130
131\begin{CompactList}\small\item\em access function, possibly dangerous! \item\end{CompactList}\item 
132\hypertarget{classbdm_1_1epdf_62e88cbce0ce77a8692f5e15d76e805f}{
133void \hyperlink{classbdm_1_1epdf_62e88cbce0ce77a8692f5e15d76e805f}{\_\-renewrv} (const \hyperlink{classbdm_1_1RV}{RV} \&in\_\-rv)}
134\label{classbdm_1_1epdf_62e88cbce0ce77a8692f5e15d76e805f}
135
136\begin{CompactList}\small\item\em modifier function - useful when copying epdfs \item\end{CompactList}\end{CompactItemize}
137\subsection*{Protected Attributes}
138\begin{CompactItemize}
139\item 
140\hypertarget{classbdm_1_1egiw_ae56852845c6af176fd9017dbebbbd52}{
141\hyperlink{classldmat}{ldmat} \hyperlink{classbdm_1_1egiw_ae56852845c6af176fd9017dbebbbd52}{V}}
142\label{classbdm_1_1egiw_ae56852845c6af176fd9017dbebbbd52}
143
144\begin{CompactList}\small\item\em Extended information matrix of sufficient statistics. \item\end{CompactList}\item 
145\hypertarget{classbdm_1_1egiw_447eacf19d4f4083872686f044814dc4}{
146double \hyperlink{classbdm_1_1egiw_447eacf19d4f4083872686f044814dc4}{nu}}
147\label{classbdm_1_1egiw_447eacf19d4f4083872686f044814dc4}
148
149\begin{CompactList}\small\item\em Number of data records (degrees of freedom) of sufficient statistics. \item\end{CompactList}\item 
150\hypertarget{classbdm_1_1egiw_40b68a9c3b2120fba94cc4d2fcd291e1}{
151int \hyperlink{classbdm_1_1egiw_40b68a9c3b2120fba94cc4d2fcd291e1}{xdim}}
152\label{classbdm_1_1egiw_40b68a9c3b2120fba94cc4d2fcd291e1}
153
154\begin{CompactList}\small\item\em Dimension of the output. \item\end{CompactList}\item 
155\hypertarget{classbdm_1_1egiw_322414c32d9a21a006a5aab0311f64fd}{
156int \hyperlink{classbdm_1_1egiw_322414c32d9a21a006a5aab0311f64fd}{nPsi}}
157\label{classbdm_1_1egiw_322414c32d9a21a006a5aab0311f64fd}
158
159\begin{CompactList}\small\item\em Dimension of the regressor. \item\end{CompactList}\item 
160\hypertarget{classbdm_1_1epdf_62c5b8ff71d9ebe6cd58d3c342eb1dc8}{
161\hyperlink{classbdm_1_1RV}{RV} \hyperlink{classbdm_1_1epdf_62c5b8ff71d9ebe6cd58d3c342eb1dc8}{rv}}
162\label{classbdm_1_1epdf_62c5b8ff71d9ebe6cd58d3c342eb1dc8}
163
164\begin{CompactList}\small\item\em Identified of the random variable. \item\end{CompactList}\end{CompactItemize}
165
166
167\subsection{Detailed Description}
168Gauss-inverse-Wishart density stored in LD form.
169
170For $p$-variate densities, given rv.count() should be $p\times$ V.rows().
171
172The documentation for this class was generated from the following files:\begin{CompactItemize}
173\item 
174\hyperlink{libEF_8h}{libEF.h}\item 
175libEF.cpp\end{CompactItemize}
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