root/doc/latex/classbdm_1_1EKF.tex @ 270

Revision 270, 14.7 kB (checked in by smidl, 16 years ago)

Changes in the very root classes!
* rv and rvc are no longer compulsory,
* samplecond does not return ll
* BM has drv

Line 
1\hypertarget{classbdm_1_1EKF}{
2\section{bdm::EKF$<$ sq\_\-T $>$ Class Template Reference}
3\label{classbdm_1_1EKF}\index{bdm::EKF@{bdm::EKF}}
4}
5{\tt \#include $<$libKF.h$>$}
6
7Inheritance diagram for bdm::EKF$<$ sq\_\-T $>$:\nopagebreak
8\begin{figure}[H]
9\begin{center}
10\leavevmode
11\includegraphics[width=117pt]{classbdm_1_1EKF__inherit__graph}
12\end{center}
13\end{figure}
14
15
16\subsection{Detailed Description}
17\subsubsection*{template$<$class sq\_\-T$>$ class bdm::EKF$<$ sq\_\-T $>$}
18
19Extended \hyperlink{classbdm_1_1Kalman}{Kalman} Filter.
20
21An approximation of the exact Bayesian filter with Gaussian noices and non-linear evolutions of their mean. \subsection*{Public Member Functions}
22\begin{CompactItemize}
23\item 
24\hypertarget{classbdm_1_1EKF_d087a8bb408d26ac4f5c542746b81059}{
25\hyperlink{classbdm_1_1EKF_d087a8bb408d26ac4f5c542746b81059}{EKF} (\hyperlink{classbdm_1_1RV}{RV} rvx, \hyperlink{classbdm_1_1RV}{RV} \hyperlink{classbdm_1_1Kalman_3fe475a1e920b20b63bb342c0e1571f7}{rvy}, \hyperlink{classbdm_1_1RV}{RV} \hyperlink{classbdm_1_1Kalman_149e27424fd1a7cc1c998ea088618a94}{rvu})}
26\label{classbdm_1_1EKF_d087a8bb408d26ac4f5c542746b81059}
27
28\begin{CompactList}\small\item\em Default constructor. \item\end{CompactList}\item 
29\hypertarget{classbdm_1_1EKF_00fec1a0a6a467eb83fb36c65eba7bcb}{
30void \hyperlink{classbdm_1_1EKF_00fec1a0a6a467eb83fb36c65eba7bcb}{set\_\-parameters} (\hyperlink{classbdm_1_1diffbifn}{diffbifn} $\ast$pfxu, \hyperlink{classbdm_1_1diffbifn}{diffbifn} $\ast$phxu, const sq\_\-T Q0, const sq\_\-T R0)}
31\label{classbdm_1_1EKF_00fec1a0a6a467eb83fb36c65eba7bcb}
32
33\begin{CompactList}\small\item\em Set nonlinear functions for mean values and covariance matrices. \item\end{CompactList}\item 
34\hypertarget{classbdm_1_1EKF_3fb182ecc29b10ca1163cecbf3bcccfa}{
35void \hyperlink{classbdm_1_1EKF_3fb182ecc29b10ca1163cecbf3bcccfa}{bayes} (const vec \&dt)}
36\label{classbdm_1_1EKF_3fb182ecc29b10ca1163cecbf3bcccfa}
37
38\begin{CompactList}\small\item\em Here dt = \mbox{[}yt;ut\mbox{]} of appropriate dimensions. \item\end{CompactList}\item 
39\hypertarget{classbdm_1_1Kalman_94eb8cc31731210089db0ba4e1a08a6c}{
40void \hyperlink{classbdm_1_1Kalman_94eb8cc31731210089db0ba4e1a08a6c}{set\_\-parameters} (const mat \&A0, const mat \&B0, const mat \&C0, const mat \&D0, const \hyperlink{classfsqmat}{fsqmat} \&R0, const \hyperlink{classfsqmat}{fsqmat} \&Q0)}
41\label{classbdm_1_1Kalman_94eb8cc31731210089db0ba4e1a08a6c}
42
43\begin{CompactList}\small\item\em Set parameters with check of relevance. \item\end{CompactList}\item 
44\hypertarget{classbdm_1_1Kalman_9264fc6b173ecb803d2684b883f32c68}{
45void \hyperlink{classbdm_1_1Kalman_9264fc6b173ecb803d2684b883f32c68}{set\_\-est} (const vec \&mu0, const \hyperlink{classfsqmat}{fsqmat} \&P0)}
46\label{classbdm_1_1Kalman_9264fc6b173ecb803d2684b883f32c68}
47
48\begin{CompactList}\small\item\em Set estimate values, used e.g. in initialization. \item\end{CompactList}\item 
49\hypertarget{classbdm_1_1Kalman_93b5936ba397f13c05f52885c545f42d}{
50const \hyperlink{classbdm_1_1epdf}{epdf} \& \hyperlink{classbdm_1_1Kalman_93b5936ba397f13c05f52885c545f42d}{\_\-epdf} () const }
51\label{classbdm_1_1Kalman_93b5936ba397f13c05f52885c545f42d}
52
53\begin{CompactList}\small\item\em access function \item\end{CompactList}\item 
54\hypertarget{classbdm_1_1Kalman_c34989b1e53c7d4ecdaea63a95ddbd77}{
55const \hyperlink{classbdm_1_1enorm}{enorm}$<$ \hyperlink{classfsqmat}{fsqmat} $>$ $\ast$ \textbf{\_\-e} () const }
56\label{classbdm_1_1Kalman_c34989b1e53c7d4ecdaea63a95ddbd77}
57
58\item 
59\hypertarget{classbdm_1_1Kalman_c788ec6e6c6f5f5861ae8a56d8ede277}{
60mat \& \hyperlink{classbdm_1_1Kalman_c788ec6e6c6f5f5861ae8a56d8ede277}{\_\-\_\-K} ()}
61\label{classbdm_1_1Kalman_c788ec6e6c6f5f5861ae8a56d8ede277}
62
63\begin{CompactList}\small\item\em access function \item\end{CompactList}\item 
64\hypertarget{classbdm_1_1Kalman_a250d1dbe7bba861dba2a324520cfa48}{
65vec \hyperlink{classbdm_1_1Kalman_a250d1dbe7bba861dba2a324520cfa48}{\_\-dP} ()}
66\label{classbdm_1_1Kalman_a250d1dbe7bba861dba2a324520cfa48}
67
68\begin{CompactList}\small\item\em access function \item\end{CompactList}\end{CompactItemize}
69\begin{Indent}{\bf Constructors}\par
70\begin{CompactItemize}
71\item 
72virtual \hyperlink{classbdm_1_1BM}{BM} $\ast$ \hyperlink{classbdm_1_1BM_c0f027ff91d8459937c6f60ff8e553ff}{\_\-copy\_\-} ()
73\end{CompactItemize}
74\end{Indent}
75\begin{Indent}{\bf Mathematical operations}\par
76\begin{CompactItemize}
77\item 
78\hypertarget{classbdm_1_1BM_1dee3fddaf021e62d925289660a707dc}{
79virtual void \hyperlink{classbdm_1_1BM_1dee3fddaf021e62d925289660a707dc}{bayesB} (const mat \&Dt)}
80\label{classbdm_1_1BM_1dee3fddaf021e62d925289660a707dc}
81
82\begin{CompactList}\small\item\em Batch Bayes rule (columns of Dt are observations). \item\end{CompactList}\item 
83virtual double \hyperlink{classbdm_1_1BM_50257e0c1e5b5c73153ea6e716ad8ae0}{logpred} (const vec \&dt) const
84\item 
85\hypertarget{classbdm_1_1BM_0e8ebe61fb14990abe1254bd3dda5fae}{
86vec \hyperlink{classbdm_1_1BM_0e8ebe61fb14990abe1254bd3dda5fae}{logpred\_\-m} (const mat \&dt) const }
87\label{classbdm_1_1BM_0e8ebe61fb14990abe1254bd3dda5fae}
88
89\begin{CompactList}\small\item\em Matrix version of logpred. \item\end{CompactList}\item 
90\hypertarget{classbdm_1_1BM_688d7a2aced1e06aa1c468d73a9e5eba}{
91virtual \hyperlink{classbdm_1_1epdf}{epdf} $\ast$ \hyperlink{classbdm_1_1BM_688d7a2aced1e06aa1c468d73a9e5eba}{epredictor} () const }
92\label{classbdm_1_1BM_688d7a2aced1e06aa1c468d73a9e5eba}
93
94\begin{CompactList}\small\item\em Constructs a predictive density $ f(d_{t+1} |d_{t}, \ldots d_{0}) $. \item\end{CompactList}\item 
95\hypertarget{classbdm_1_1BM_598b25e3f3d96a5bc00a5faeb5b3c912}{
96virtual \hyperlink{classbdm_1_1mpdf}{mpdf} $\ast$ \hyperlink{classbdm_1_1BM_598b25e3f3d96a5bc00a5faeb5b3c912}{predictor} () const }
97\label{classbdm_1_1BM_598b25e3f3d96a5bc00a5faeb5b3c912}
98
99\begin{CompactList}\small\item\em Constructs a conditional density 1-step ahead predictor. \item\end{CompactList}\end{CompactItemize}
100\end{Indent}
101\begin{Indent}{\bf Access to attributes}\par
102\begin{CompactItemize}
103\item 
104\hypertarget{classbdm_1_1BM_ff2d8755ba0b3def927d31305c03b09c}{
105const \hyperlink{classbdm_1_1RV}{RV} \& \textbf{\_\-drv} () const }
106\label{classbdm_1_1BM_ff2d8755ba0b3def927d31305c03b09c}
107
108\item 
109\hypertarget{classbdm_1_1BM_f135ae6dce7e9f30c9f88229c7930b96}{
110void \textbf{set\_\-drv} (const \hyperlink{classbdm_1_1RV}{RV} \&rv)}
111\label{classbdm_1_1BM_f135ae6dce7e9f30c9f88229c7930b96}
112
113\item 
114\hypertarget{classbdm_1_1BM_5be65d37dedfe33a3671e7065f523a70}{
115double \textbf{\_\-ll} () const }
116\label{classbdm_1_1BM_5be65d37dedfe33a3671e7065f523a70}
117
118\item 
119\hypertarget{classbdm_1_1BM_236b3abbcc93594fc97cd86d82c1a83f}{
120void \textbf{set\_\-evalll} (bool evl0)}
121\label{classbdm_1_1BM_236b3abbcc93594fc97cd86d82c1a83f}
122
123\end{CompactItemize}
124\end{Indent}
125\subsection*{Protected Attributes}
126\begin{CompactItemize}
127\item 
128\hypertarget{classbdm_1_1Kalman_3fe475a1e920b20b63bb342c0e1571f7}{
129\hyperlink{classbdm_1_1RV}{RV} \hyperlink{classbdm_1_1Kalman_3fe475a1e920b20b63bb342c0e1571f7}{rvy}}
130\label{classbdm_1_1Kalman_3fe475a1e920b20b63bb342c0e1571f7}
131
132\begin{CompactList}\small\item\em Indetifier of output rv. \item\end{CompactList}\item 
133\hypertarget{classbdm_1_1Kalman_149e27424fd1a7cc1c998ea088618a94}{
134\hyperlink{classbdm_1_1RV}{RV} \hyperlink{classbdm_1_1Kalman_149e27424fd1a7cc1c998ea088618a94}{rvu}}
135\label{classbdm_1_1Kalman_149e27424fd1a7cc1c998ea088618a94}
136
137\begin{CompactList}\small\item\em Indetifier of exogeneous rv. \item\end{CompactList}\item 
138\hypertarget{classbdm_1_1Kalman_ba7699cdb3b1382a54d3e28b9b7517fa}{
139int \hyperlink{classbdm_1_1Kalman_ba7699cdb3b1382a54d3e28b9b7517fa}{dimx}}
140\label{classbdm_1_1Kalman_ba7699cdb3b1382a54d3e28b9b7517fa}
141
142\begin{CompactList}\small\item\em cache of rv.count() \item\end{CompactList}\item 
143\hypertarget{classbdm_1_1Kalman_d2c36ba01760bf207b985bf321b7817f}{
144int \hyperlink{classbdm_1_1Kalman_d2c36ba01760bf207b985bf321b7817f}{dimy}}
145\label{classbdm_1_1Kalman_d2c36ba01760bf207b985bf321b7817f}
146
147\begin{CompactList}\small\item\em cache of rvy.count() \item\end{CompactList}\item 
148\hypertarget{classbdm_1_1Kalman_c5136ef617f6ac0e426bea222755d92b}{
149int \hyperlink{classbdm_1_1Kalman_c5136ef617f6ac0e426bea222755d92b}{dimu}}
150\label{classbdm_1_1Kalman_c5136ef617f6ac0e426bea222755d92b}
151
152\begin{CompactList}\small\item\em cache of rvu.count() \item\end{CompactList}\item 
153\hypertarget{classbdm_1_1Kalman_0a2072e2090c10fac74ad30a023a4ace}{
154mat \hyperlink{classbdm_1_1Kalman_0a2072e2090c10fac74ad30a023a4ace}{A}}
155\label{classbdm_1_1Kalman_0a2072e2090c10fac74ad30a023a4ace}
156
157\begin{CompactList}\small\item\em Matrix A. \item\end{CompactList}\item 
158\hypertarget{classbdm_1_1Kalman_5977b2c81857948a35105f0e7840203c}{
159mat \hyperlink{classbdm_1_1Kalman_5977b2c81857948a35105f0e7840203c}{B}}
160\label{classbdm_1_1Kalman_5977b2c81857948a35105f0e7840203c}
161
162\begin{CompactList}\small\item\em Matrix B. \item\end{CompactList}\item 
163\hypertarget{classbdm_1_1Kalman_818eba63a23972786a4579ad30294177}{
164mat \hyperlink{classbdm_1_1Kalman_818eba63a23972786a4579ad30294177}{C}}
165\label{classbdm_1_1Kalman_818eba63a23972786a4579ad30294177}
166
167\begin{CompactList}\small\item\em Matrix C. \item\end{CompactList}\item 
168\hypertarget{classbdm_1_1Kalman_7b56ac423d0654b5755e4f852a870456}{
169mat \hyperlink{classbdm_1_1Kalman_7b56ac423d0654b5755e4f852a870456}{D}}
170\label{classbdm_1_1Kalman_7b56ac423d0654b5755e4f852a870456}
171
172\begin{CompactList}\small\item\em Matrix D. \item\end{CompactList}\item 
173\hypertarget{classbdm_1_1Kalman_70f8bf19e81b532c60fd3a7a152425ee}{
174\hyperlink{classfsqmat}{fsqmat} \hyperlink{classbdm_1_1Kalman_70f8bf19e81b532c60fd3a7a152425ee}{Q}}
175\label{classbdm_1_1Kalman_70f8bf19e81b532c60fd3a7a152425ee}
176
177\begin{CompactList}\small\item\em Matrix Q in square-root form. \item\end{CompactList}\item 
178\hypertarget{classbdm_1_1Kalman_475b088287cdfbba4dc60a3d027728b7}{
179\hyperlink{classfsqmat}{fsqmat} \hyperlink{classbdm_1_1Kalman_475b088287cdfbba4dc60a3d027728b7}{R}}
180\label{classbdm_1_1Kalman_475b088287cdfbba4dc60a3d027728b7}
181
182\begin{CompactList}\small\item\em Matrix R in square-root form. \item\end{CompactList}\item 
183\hypertarget{classbdm_1_1Kalman_383f329ff18bbe219254c8b3b916f40d}{
184\hyperlink{classbdm_1_1enorm}{enorm}$<$ \hyperlink{classfsqmat}{fsqmat} $>$ \hyperlink{classbdm_1_1Kalman_383f329ff18bbe219254c8b3b916f40d}{est}}
185\label{classbdm_1_1Kalman_383f329ff18bbe219254c8b3b916f40d}
186
187\begin{CompactList}\small\item\em posterior density on \$x\_\-t\$ \item\end{CompactList}\item 
188\hypertarget{classbdm_1_1Kalman_ba555c394c429f6831c9bbabfa2c944c}{
189\hyperlink{classbdm_1_1enorm}{enorm}$<$ \hyperlink{classfsqmat}{fsqmat} $>$ \hyperlink{classbdm_1_1Kalman_ba555c394c429f6831c9bbabfa2c944c}{fy}}
190\label{classbdm_1_1Kalman_ba555c394c429f6831c9bbabfa2c944c}
191
192\begin{CompactList}\small\item\em preditive density on \$y\_\-t\$ \item\end{CompactList}\item 
193\hypertarget{classbdm_1_1Kalman_bd69dfb802465f22dd84d73a180d5c92}{
194mat \hyperlink{classbdm_1_1Kalman_bd69dfb802465f22dd84d73a180d5c92}{\_\-K}}
195\label{classbdm_1_1Kalman_bd69dfb802465f22dd84d73a180d5c92}
196
197\begin{CompactList}\small\item\em placeholder for Kalman gain \item\end{CompactList}\item 
198\hypertarget{classbdm_1_1Kalman_c249d45258c8578b13858ad3e7b729b1}{
199vec \& \hyperlink{classbdm_1_1Kalman_c249d45258c8578b13858ad3e7b729b1}{\_\-yp}}
200\label{classbdm_1_1Kalman_c249d45258c8578b13858ad3e7b729b1}
201
202\begin{CompactList}\small\item\em cache of fy.mu \item\end{CompactList}\item 
203\hypertarget{classbdm_1_1Kalman_2dd268f2d7fbe6382cb8825a1114192a}{
204\hyperlink{classfsqmat}{fsqmat} \& \hyperlink{classbdm_1_1Kalman_2dd268f2d7fbe6382cb8825a1114192a}{\_\-Ry}}
205\label{classbdm_1_1Kalman_2dd268f2d7fbe6382cb8825a1114192a}
206
207\begin{CompactList}\small\item\em cache of fy.R \item\end{CompactList}\item 
208\hypertarget{classbdm_1_1Kalman_fa172078091e45561343fa513dd573b0}{
209vec \& \hyperlink{classbdm_1_1Kalman_fa172078091e45561343fa513dd573b0}{\_\-mu}}
210\label{classbdm_1_1Kalman_fa172078091e45561343fa513dd573b0}
211
212\begin{CompactList}\small\item\em cache of est.mu \item\end{CompactList}\item 
213\hypertarget{classbdm_1_1Kalman_00c27b0bf324f0018497921ca23c71ed}{
214\hyperlink{classfsqmat}{fsqmat} \& \hyperlink{classbdm_1_1Kalman_00c27b0bf324f0018497921ca23c71ed}{\_\-P}}
215\label{classbdm_1_1Kalman_00c27b0bf324f0018497921ca23c71ed}
216
217\begin{CompactList}\small\item\em cache of est.R \item\end{CompactList}\item 
218\hypertarget{classbdm_1_1BM_c400357e37d27a4834b2b1d9211009ed}{
219\hyperlink{classbdm_1_1RV}{RV} \hyperlink{classbdm_1_1BM_c400357e37d27a4834b2b1d9211009ed}{drv}}
220\label{classbdm_1_1BM_c400357e37d27a4834b2b1d9211009ed}
221
222\begin{CompactList}\small\item\em Random variable of the data (optional). \item\end{CompactList}\item 
223\hypertarget{classbdm_1_1BM_4064b6559d962633e4372b12f4cd204a}{
224double \hyperlink{classbdm_1_1BM_4064b6559d962633e4372b12f4cd204a}{ll}}
225\label{classbdm_1_1BM_4064b6559d962633e4372b12f4cd204a}
226
227\begin{CompactList}\small\item\em Logarithm of marginalized data likelihood. \item\end{CompactList}\item 
228\hypertarget{classbdm_1_1BM_faff0ad12556fe7dc0e2807d4fd938ee}{
229bool \hyperlink{classbdm_1_1BM_faff0ad12556fe7dc0e2807d4fd938ee}{evalll}}
230\label{classbdm_1_1BM_faff0ad12556fe7dc0e2807d4fd938ee}
231
232\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}
233
234
235\subsection{Member Function Documentation}
236\hypertarget{classbdm_1_1BM_c0f027ff91d8459937c6f60ff8e553ff}{
237\index{bdm::EKF@{bdm::EKF}!\_\-copy\_\-@{\_\-copy\_\-}}
238\index{\_\-copy\_\-@{\_\-copy\_\-}!bdm::EKF@{bdm::EKF}}
239\subsubsection[\_\-copy\_\-]{\setlength{\rightskip}{0pt plus 5cm}virtual {\bf BM}$\ast$ bdm::BM::\_\-copy\_\- ()\hspace{0.3cm}{\tt  \mbox{[}inline, virtual, inherited\mbox{]}}}}
240\label{classbdm_1_1BM_c0f027ff91d8459937c6f60ff8e553ff}
241
242
243Copy function required in vectors, Arrays of \hyperlink{classbdm_1_1BM}{BM} etc. Have to be DELETED manually! Prototype:
244
245\begin{Code}\begin{verbatim} BM* _copy_(){return new BM(*this);} 
246\end{verbatim}
247\end{Code}
248
249 
250
251Reimplemented in \hyperlink{classbdm_1_1ARX_60c40b5c6abc4c7e464b4ccae64a5a61}{bdm::ARX}.\hypertarget{classbdm_1_1BM_50257e0c1e5b5c73153ea6e716ad8ae0}{
252\index{bdm::EKF@{bdm::EKF}!logpred@{logpred}}
253\index{logpred@{logpred}!bdm::EKF@{bdm::EKF}}
254\subsubsection[logpred]{\setlength{\rightskip}{0pt plus 5cm}virtual double bdm::BM::logpred (const vec \& {\em dt}) const\hspace{0.3cm}{\tt  \mbox{[}inline, virtual, inherited\mbox{]}}}}
255\label{classbdm_1_1BM_50257e0c1e5b5c73153ea6e716ad8ae0}
256
257
258Evaluates predictive log-likelihood of the given data record I.e. marginal likelihood of the data with the posterior integrated out.
259
260Reimplemented in \hyperlink{classbdm_1_1ARX_080a7e531e3aa06694112863b15bc6a4}{bdm::ARX}, \hyperlink{classbdm_1_1MixEF_da724da464a75e07521941e430929efa}{bdm::MixEF}, and \hyperlink{classbdm_1_1multiBM_e157b607c1e3fa91d42aeea44458e2bf}{bdm::multiBM}.
261
262Referenced by bdm::BM::logpred\_\-m().
263
264The documentation for this class was generated from the following file:\begin{CompactItemize}
265\item 
266\hyperlink{libKF_8h}{libKF.h}\end{CompactItemize}
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