root/doc/latex/classbdm_1_1MixEF.tex @ 261

Revision 261, 14.2 kB (checked in by smidl, 16 years ago)

doc

RevLine 
[261]1\hypertarget{classbdm_1_1MixEF}{
2\section{bdm::MixEF Class Reference}
3\label{classbdm_1_1MixEF}\index{bdm::MixEF@{bdm::MixEF}}
4}
5Mixture of Exponential Family Densities. 
6
7
8{\tt \#include $<$mixef.h$>$}
9
10Inheritance diagram for bdm::MixEF:\nopagebreak
11\begin{figure}[H]
12\begin{center}
13\leavevmode
14\includegraphics[width=64pt]{classbdm_1_1MixEF__inherit__graph}
15\end{center}
16\end{figure}
17Collaboration diagram for bdm::MixEF:\nopagebreak
18\begin{figure}[H]
19\begin{center}
20\leavevmode
21\includegraphics[height=400pt]{classbdm_1_1MixEF__coll__graph}
22\end{center}
23\end{figure}
24\subsection*{Public Member Functions}
25\begin{CompactItemize}
26\item 
27\hypertarget{classbdm_1_1MixEF_4efe67d414ff34a1e7534004fd061241}{
28\hyperlink{classbdm_1_1MixEF_4efe67d414ff34a1e7534004fd061241}{MixEF} (const Array$<$ \hyperlink{classbdm_1_1BMEF}{BMEF} $\ast$ $>$ \&Coms0, const vec \&alpha0)}
29\label{classbdm_1_1MixEF_4efe67d414ff34a1e7534004fd061241}
30
31\begin{CompactList}\small\item\em Full constructor. \item\end{CompactList}\item 
32\hypertarget{classbdm_1_1MixEF_0266854387338ba757e6192d62907984}{
33\hyperlink{classbdm_1_1MixEF_0266854387338ba757e6192d62907984}{MixEF} ()}
34\label{classbdm_1_1MixEF_0266854387338ba757e6192d62907984}
35
36\begin{CompactList}\small\item\em Constructor of empty mixture. \item\end{CompactList}\item 
37\hypertarget{classbdm_1_1MixEF_9577de85c3e3481f7c0e23cf8f87c482}{
38\hyperlink{classbdm_1_1MixEF_9577de85c3e3481f7c0e23cf8f87c482}{MixEF} (const \hyperlink{classbdm_1_1MixEF}{MixEF} \&M2)}
39\label{classbdm_1_1MixEF_9577de85c3e3481f7c0e23cf8f87c482}
40
41\begin{CompactList}\small\item\em Copy constructor. \item\end{CompactList}\item 
42void \hyperlink{classbdm_1_1MixEF_0c2a50789b30769964a909d217125ed2}{init} (\hyperlink{classbdm_1_1BMEF}{BMEF} $\ast$Com0, const mat \&Data, int c=5)
43\item 
44\hypertarget{classbdm_1_1MixEF_5bd7da667da183eed1577f11dff0c1f1}{
45void \hyperlink{classbdm_1_1MixEF_5bd7da667da183eed1577f11dff0c1f1}{bayes} (const vec \&dt)}
46\label{classbdm_1_1MixEF_5bd7da667da183eed1577f11dff0c1f1}
47
48\begin{CompactList}\small\item\em Recursive EM-like algorithm (QB-variant), see Karny et. al, 2006. \item\end{CompactList}\item 
49\hypertarget{classbdm_1_1MixEF_5c41d5a4403da6e629f6bdfc70c43d20}{
50void \hyperlink{classbdm_1_1MixEF_5c41d5a4403da6e629f6bdfc70c43d20}{bayes} (const mat \&dt)}
51\label{classbdm_1_1MixEF_5c41d5a4403da6e629f6bdfc70c43d20}
52
53\begin{CompactList}\small\item\em EM algorithm. \item\end{CompactList}\item 
54\hypertarget{classbdm_1_1MixEF_5de521c395e93478df00d881ab8dac81}{
55void \textbf{bayesB} (const mat \&dt, const vec \&wData)}
56\label{classbdm_1_1MixEF_5de521c395e93478df00d881ab8dac81}
57
58\item 
59double \hyperlink{classbdm_1_1MixEF_da724da464a75e07521941e430929efa}{logpred} (const vec \&dt) const
60\item 
61\hypertarget{classbdm_1_1MixEF_33d0b3da1d10bf149d41ee74f6284a19}{
62const \hyperlink{classbdm_1_1epdf}{epdf} \& \hyperlink{classbdm_1_1MixEF_33d0b3da1d10bf149d41ee74f6284a19}{\_\-epdf} () const }
63\label{classbdm_1_1MixEF_33d0b3da1d10bf149d41ee74f6284a19}
64
65\begin{CompactList}\small\item\em Returns a reference to the \hyperlink{classbdm_1_1epdf}{epdf} representing posterior density on parameters. \item\end{CompactList}\item 
66\hypertarget{classbdm_1_1MixEF_ea8be6f0703d87b7c4c3e77fd07e28c8}{
67const \hyperlink{classbdm_1_1eprod}{eprod} $\ast$ \hyperlink{classbdm_1_1MixEF_ea8be6f0703d87b7c4c3e77fd07e28c8}{\_\-e} () const }
68\label{classbdm_1_1MixEF_ea8be6f0703d87b7c4c3e77fd07e28c8}
69
70\begin{CompactList}\small\item\em Returns a pointer to the \hyperlink{classbdm_1_1epdf}{epdf} representing posterior density on parameters. Use with care! \item\end{CompactList}\item 
71\hypertarget{classbdm_1_1MixEF_5105973c0f790f08d1dfb79c2a3f6e1c}{
72\hyperlink{classbdm_1_1emix}{emix} $\ast$ \hyperlink{classbdm_1_1MixEF_5105973c0f790f08d1dfb79c2a3f6e1c}{predictor} (const \hyperlink{classbdm_1_1RV}{RV} \&\hyperlink{classbdm_1_1BM_18d6db4af8ee42077741d9e3618153ca}{rv}) const }
73\label{classbdm_1_1MixEF_5105973c0f790f08d1dfb79c2a3f6e1c}
74
75\begin{CompactList}\small\item\em Constructs a predictive density (marginal density on data). \item\end{CompactList}\item 
76\hypertarget{classbdm_1_1MixEF_f0dfb4375fef4e61c4cb062e5bac7c8c}{
77void \hyperlink{classbdm_1_1MixEF_f0dfb4375fef4e61c4cb062e5bac7c8c}{flatten} (const \hyperlink{classbdm_1_1BMEF}{BMEF} $\ast$M2)}
78\label{classbdm_1_1MixEF_f0dfb4375fef4e61c4cb062e5bac7c8c}
79
80\begin{CompactList}\small\item\em Flatten the density as if it was not estimated from the data. \item\end{CompactList}\item 
81\hypertarget{classbdm_1_1MixEF_251ef6fc51757712693da5faae5317c9}{
82\hyperlink{classbdm_1_1BMEF}{BMEF} $\ast$ \hyperlink{classbdm_1_1MixEF_251ef6fc51757712693da5faae5317c9}{\_\-Coms} (int i)}
83\label{classbdm_1_1MixEF_251ef6fc51757712693da5faae5317c9}
84
85\begin{CompactList}\small\item\em Access function. \item\end{CompactList}\item 
86\hypertarget{classbdm_1_1MixEF_664529d52cc667383b39eeb440ccd577}{
87void \hyperlink{classbdm_1_1MixEF_664529d52cc667383b39eeb440ccd577}{set\_\-method} (MixEF\_\-METHOD M)}
88\label{classbdm_1_1MixEF_664529d52cc667383b39eeb440ccd577}
89
90\begin{CompactList}\small\item\em Set which method is to be used. \item\end{CompactList}\item 
91\hypertarget{classbdm_1_1BMEF_d2b528b7a41ca67163152142f5404051}{
92virtual void \hyperlink{classbdm_1_1BMEF_d2b528b7a41ca67163152142f5404051}{set\_\-statistics} (const \hyperlink{classbdm_1_1BMEF}{BMEF} $\ast$BM0)}
93\label{classbdm_1_1BMEF_d2b528b7a41ca67163152142f5404051}
94
95\begin{CompactList}\small\item\em get statistics from another model \item\end{CompactList}\item 
96\hypertarget{classbdm_1_1BMEF_bf58deb99af2a6cc674f13ff90300de6}{
97virtual void \hyperlink{classbdm_1_1BMEF_bf58deb99af2a6cc674f13ff90300de6}{bayes} (const vec \&data, const double w)}
98\label{classbdm_1_1BMEF_bf58deb99af2a6cc674f13ff90300de6}
99
100\begin{CompactList}\small\item\em Weighted update of sufficient statistics (Bayes rule). \item\end{CompactList}\item 
101\hypertarget{classbdm_1_1BMEF_5912dbcf28ae711e30b08c2fa766a3e6}{
102\hyperlink{classbdm_1_1BMEF}{BMEF} $\ast$ \hyperlink{classbdm_1_1BMEF_5912dbcf28ae711e30b08c2fa766a3e6}{\_\-copy\_\-} (bool changerv=false)}
103\label{classbdm_1_1BMEF_5912dbcf28ae711e30b08c2fa766a3e6}
104
105\begin{CompactList}\small\item\em Flatten the posterior as if to keep nu0 data. \item\end{CompactList}\item 
106\hypertarget{classbdm_1_1BM_1dee3fddaf021e62d925289660a707dc}{
107virtual void \hyperlink{classbdm_1_1BM_1dee3fddaf021e62d925289660a707dc}{bayesB} (const mat \&Dt)}
108\label{classbdm_1_1BM_1dee3fddaf021e62d925289660a707dc}
109
110\begin{CompactList}\small\item\em Batch Bayes rule (columns of Dt are observations). \item\end{CompactList}\item 
111\hypertarget{classbdm_1_1BM_0e8ebe61fb14990abe1254bd3dda5fae}{
112vec \hyperlink{classbdm_1_1BM_0e8ebe61fb14990abe1254bd3dda5fae}{logpred\_\-m} (const mat \&dt) const }
113\label{classbdm_1_1BM_0e8ebe61fb14990abe1254bd3dda5fae}
114
115\begin{CompactList}\small\item\em Matrix version of logpred. \item\end{CompactList}\item 
116\hypertarget{classbdm_1_1BM_40a3c891996391e3135518053a917793}{
117const \hyperlink{classbdm_1_1RV}{RV} \& \hyperlink{classbdm_1_1BM_40a3c891996391e3135518053a917793}{\_\-rv} () const }
118\label{classbdm_1_1BM_40a3c891996391e3135518053a917793}
119
120\begin{CompactList}\small\item\em access function \item\end{CompactList}\item 
121\hypertarget{classbdm_1_1BM_5be65d37dedfe33a3671e7065f523a70}{
122double \hyperlink{classbdm_1_1BM_5be65d37dedfe33a3671e7065f523a70}{\_\-ll} () const }
123\label{classbdm_1_1BM_5be65d37dedfe33a3671e7065f523a70}
124
125\begin{CompactList}\small\item\em access function \item\end{CompactList}\item 
126\hypertarget{classbdm_1_1BM_236b3abbcc93594fc97cd86d82c1a83f}{
127void \hyperlink{classbdm_1_1BM_236b3abbcc93594fc97cd86d82c1a83f}{set\_\-evalll} (bool evl0)}
128\label{classbdm_1_1BM_236b3abbcc93594fc97cd86d82c1a83f}
129
130\begin{CompactList}\small\item\em access function \item\end{CompactList}\end{CompactItemize}
131\subsection*{Protected Member Functions}
132\begin{CompactItemize}
133\item 
134\hypertarget{classbdm_1_1MixEF_d74a8d1370c63c93ec554908ae3e6006}{
135void \hyperlink{classbdm_1_1MixEF_d74a8d1370c63c93ec554908ae3e6006}{build\_\-est} ()}
136\label{classbdm_1_1MixEF_d74a8d1370c63c93ec554908ae3e6006}
137
138\begin{CompactList}\small\item\em Auxiliary function for use in constructors. \item\end{CompactList}\end{CompactItemize}
139\subsection*{Protected Attributes}
140\begin{CompactItemize}
141\item 
142\hypertarget{classbdm_1_1MixEF_38ca1d86e977d1c38810a3c95bf074a5}{
143int \hyperlink{classbdm_1_1MixEF_38ca1d86e977d1c38810a3c95bf074a5}{n}}
144\label{classbdm_1_1MixEF_38ca1d86e977d1c38810a3c95bf074a5}
145
146\begin{CompactList}\small\item\em Number of components. \item\end{CompactList}\item 
147\hypertarget{classbdm_1_1MixEF_90c21ab5a2af56d4b49e2eaef6eccc08}{
148Array$<$ \hyperlink{classbdm_1_1BMEF}{BMEF} $\ast$ $>$ \hyperlink{classbdm_1_1MixEF_90c21ab5a2af56d4b49e2eaef6eccc08}{Coms}}
149\label{classbdm_1_1MixEF_90c21ab5a2af56d4b49e2eaef6eccc08}
150
151\begin{CompactList}\small\item\em Models for Components of $\theta_i$. \item\end{CompactList}\item 
152\hypertarget{classbdm_1_1MixEF_e39faa70cebadc3296bd249040105e86}{
153\hyperlink{classbdm_1_1multiBM}{multiBM} \hyperlink{classbdm_1_1MixEF_e39faa70cebadc3296bd249040105e86}{weights}}
154\label{classbdm_1_1MixEF_e39faa70cebadc3296bd249040105e86}
155
156\begin{CompactList}\small\item\em Statistics for weights. \item\end{CompactList}\item 
157\hypertarget{classbdm_1_1MixEF_9413fb7f1836237aac807fb9f245e4f6}{
158\hyperlink{classbdm_1_1eprod}{eprod} $\ast$ \hyperlink{classbdm_1_1MixEF_9413fb7f1836237aac807fb9f245e4f6}{est}}
159\label{classbdm_1_1MixEF_9413fb7f1836237aac807fb9f245e4f6}
160
161\begin{CompactList}\small\item\em Posterior on component parameters. \item\end{CompactList}\item 
162\hypertarget{classbdm_1_1MixEF_a2376ddadb7573532404452d0c2dd28a}{
163MixEF\_\-METHOD \hyperlink{classbdm_1_1MixEF_a2376ddadb7573532404452d0c2dd28a}{method}}
164\label{classbdm_1_1MixEF_a2376ddadb7573532404452d0c2dd28a}
165
166\begin{CompactList}\small\item\em Flag for a method that is used in the inference. \item\end{CompactList}\item 
167\hypertarget{classbdm_1_1BMEF_1331865e10fb1ccef65bb4c47fa3be64}{
168double \hyperlink{classbdm_1_1BMEF_1331865e10fb1ccef65bb4c47fa3be64}{frg}}
169\label{classbdm_1_1BMEF_1331865e10fb1ccef65bb4c47fa3be64}
170
171\begin{CompactList}\small\item\em forgetting factor \item\end{CompactList}\item 
172\hypertarget{classbdm_1_1BMEF_06e7b3ac03e10017d4288c76888e2865}{
173double \hyperlink{classbdm_1_1BMEF_06e7b3ac03e10017d4288c76888e2865}{last\_\-lognc}}
174\label{classbdm_1_1BMEF_06e7b3ac03e10017d4288c76888e2865}
175
176\begin{CompactList}\small\item\em cached value of lognc() in the previous step (used in evaluation of {\tt ll} ) \item\end{CompactList}\item 
177\hypertarget{classbdm_1_1BM_18d6db4af8ee42077741d9e3618153ca}{
178\hyperlink{classbdm_1_1RV}{RV} \hyperlink{classbdm_1_1BM_18d6db4af8ee42077741d9e3618153ca}{rv}}
179\label{classbdm_1_1BM_18d6db4af8ee42077741d9e3618153ca}
180
181\begin{CompactList}\small\item\em Random variable of the posterior. \item\end{CompactList}\item 
182\hypertarget{classbdm_1_1BM_4064b6559d962633e4372b12f4cd204a}{
183double \hyperlink{classbdm_1_1BM_4064b6559d962633e4372b12f4cd204a}{ll}}
184\label{classbdm_1_1BM_4064b6559d962633e4372b12f4cd204a}
185
186\begin{CompactList}\small\item\em Logarithm of marginalized data likelihood. \item\end{CompactList}\item 
187\hypertarget{classbdm_1_1BM_faff0ad12556fe7dc0e2807d4fd938ee}{
188bool \hyperlink{classbdm_1_1BM_faff0ad12556fe7dc0e2807d4fd938ee}{evalll}}
189\label{classbdm_1_1BM_faff0ad12556fe7dc0e2807d4fd938ee}
190
191\begin{CompactList}\small\item\em If true, the filter will compute likelihood of the data record and store it in {\tt ll} . Set to false if you want to save computational time. \item\end{CompactList}\end{CompactItemize}
192
193
194\subsection{Detailed Description}
195Mixture of Exponential Family Densities.
196
197An approximate estimation method for models with latent discrete variable, such as mixture models of the following kind: \[ f(y_t|\psi_t, \Theta) = \sum_{i=1}^{n} w_i f(y_t|\psi_t, \theta_i) \] where $\psi$ is a known function of past outputs, $w=[w_1,\ldots,w_n]$ are component weights, and component parameters $\theta_i$ are assumed to be mutually independent. $\Theta$ is an aggregation af all component parameters and weights, i.e. $\Theta = [\theta_1,\ldots,\theta_n,w]$.
198
199The characteristic feature of this model is that if the exact values of the latent variable were known, estimation of the parameters can be handled by a single model. For example, for the case of mixture models, posterior density for each component parameters would be a BayesianModel from Exponential Family.
200
201This class uses EM-style type algorithms for estimation of its parameters. Under this simplification, the posterior density is a product of exponential family members, hence under EM-style approximate estimation this class itself belongs to the exponential family.
202
203TODO: Extend \hyperlink{classbdm_1_1BM}{BM} to use rvc.
204
205\subsection{Member Function Documentation}
206\hypertarget{classbdm_1_1MixEF_0c2a50789b30769964a909d217125ed2}{
207\index{bdm::MixEF@{bdm::MixEF}!init@{init}}
208\index{init@{init}!bdm::MixEF@{bdm::MixEF}}
209\subsubsection[init]{\setlength{\rightskip}{0pt plus 5cm}void bdm::MixEF::init ({\bf BMEF} $\ast$ {\em Com0}, \/  const mat \& {\em Data}, \/  int {\em c} = {\tt 5})}}
210\label{classbdm_1_1MixEF_0c2a50789b30769964a909d217125ed2}
211
212
213Initializing the mixture by a random pick of centroids from data \begin{Desc}
214\item[Parameters:]
215\begin{description}
216\item[{\em Com0}]Initial component - necessary to determine its type. \item[{\em Data}]Data on which the initialization will be done \item[{\em c}]Initial number of components, default=5 \end{description}
217\end{Desc}
218
219
220References bdm::BMEF::\_\-copy\_\-(), build\_\-est(), Coms, est, n, bdm::multiBM::set\_\-parameters(), bdm::UniRNG, and weights.
221
222Referenced by bdm::merger::merge().\hypertarget{classbdm_1_1MixEF_da724da464a75e07521941e430929efa}{
223\index{bdm::MixEF@{bdm::MixEF}!logpred@{logpred}}
224\index{logpred@{logpred}!bdm::MixEF@{bdm::MixEF}}
225\subsubsection[logpred]{\setlength{\rightskip}{0pt plus 5cm}double bdm::MixEF::logpred (const vec \& {\em dt}) const\hspace{0.3cm}{\tt  \mbox{[}virtual\mbox{]}}}}
226\label{classbdm_1_1MixEF_da724da464a75e07521941e430929efa}
227
228
229Evaluates predictive log-likelihood of the given data record I.e. marginal likelihood of the data with the posterior integrated out.
230
231Reimplemented from \hyperlink{classbdm_1_1BM_50257e0c1e5b5c73153ea6e716ad8ae0}{bdm::BM}.
232
233References bdm::multiBM::\_\-epdf(), Coms, bdm::epdf::mean(), and weights.
234
235Referenced by bdm::merger::evallog(), and bdm::merger::merge().
236
237The documentation for this class was generated from the following files:\begin{CompactItemize}
238\item 
239\hyperlink{mixef_8h}{mixef.h}\item 
240mixef.cpp\end{CompactItemize}
Note: See TracBrowser for help on using the browser.