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1\hypertarget{classbdm_1_1EKFfull}{
2\section{bdm::EKFfull Class Reference}
3\label{classbdm_1_1EKFfull}\index{bdm::EKFfull@{bdm::EKFfull}}
4}
5{\tt \#include $<$libKF.h$>$}
6
7Inheritance diagram for bdm::EKFfull::\begin{figure}[H]
8\begin{center}
9\leavevmode
10\includegraphics[height=4cm]{classbdm_1_1EKFfull}
11\end{center}
12\end{figure}
13
14
15\subsection{Detailed Description}
16Extended \hyperlink{classbdm_1_1Kalman}{Kalman} Filter in full matrices.
17
18An approximation of the exact Bayesian filter with Gaussian noices and non-linear evolutions of their mean. \subsection*{Public Member Functions}
19\begin{CompactItemize}
20\item 
21\hypertarget{classbdm_1_1EKFfull_6939c345389abb8b2481457b4cfe1165}{
22\hyperlink{classbdm_1_1EKFfull_6939c345389abb8b2481457b4cfe1165}{EKFfull} ()}
23\label{classbdm_1_1EKFfull_6939c345389abb8b2481457b4cfe1165}
24
25\begin{CompactList}\small\item\em Default constructor. \item\end{CompactList}\item 
26\hypertarget{classbdm_1_1EKFfull_78748da361ba61fef162b0d8956d1743}{
27void \hyperlink{classbdm_1_1EKFfull_78748da361ba61fef162b0d8956d1743}{set\_\-parameters} (\hyperlink{classbdm_1_1diffbifn}{diffbifn} $\ast$pfxu, \hyperlink{classbdm_1_1diffbifn}{diffbifn} $\ast$phxu, const mat Q0, const mat R0)}
28\label{classbdm_1_1EKFfull_78748da361ba61fef162b0d8956d1743}
29
30\begin{CompactList}\small\item\em Set nonlinear functions for mean values and covariance matrices. \item\end{CompactList}\item 
31\hypertarget{classbdm_1_1EKFfull_f149ae8e9ce14d9931a7bb2850736699}{
32void \hyperlink{classbdm_1_1EKFfull_f149ae8e9ce14d9931a7bb2850736699}{bayes} (const vec \&dt)}
33\label{classbdm_1_1EKFfull_f149ae8e9ce14d9931a7bb2850736699}
34
35\begin{CompactList}\small\item\em Here dt = \mbox{[}yt;ut\mbox{]} of appropriate dimensions. \item\end{CompactList}\item 
36\hypertarget{classbdm_1_1EKFfull_7562b3d3c17241dab3baf70258742eb2}{
37void \hyperlink{classbdm_1_1EKFfull_7562b3d3c17241dab3baf70258742eb2}{set\_\-est} (vec mu0, mat P0)}
38\label{classbdm_1_1EKFfull_7562b3d3c17241dab3baf70258742eb2}
39
40\begin{CompactList}\small\item\em set estimates \item\end{CompactList}\item 
41\hypertarget{classbdm_1_1EKFfull_7e9a69f36a0a0615c9abb806772ef36d}{
42const \hyperlink{classbdm_1_1epdf}{epdf} \& \hyperlink{classbdm_1_1EKFfull_7e9a69f36a0a0615c9abb806772ef36d}{posterior} () const }
43\label{classbdm_1_1EKFfull_7e9a69f36a0a0615c9abb806772ef36d}
44
45\begin{CompactList}\small\item\em dummy! \item\end{CompactList}\item 
46\hypertarget{classbdm_1_1EKFfull_3d0e427d4d2fb7ac20358ce629f5d510}{
47const \hyperlink{classbdm_1_1enorm}{enorm}$<$ \hyperlink{classfsqmat}{fsqmat} $>$ $\ast$ \textbf{\_\-e} () const }
48\label{classbdm_1_1EKFfull_3d0e427d4d2fb7ac20358ce629f5d510}
49
50\item 
51\hypertarget{classbdm_1_1EKFfull_d4f57cb8af64b06c530f528c32596d4d}{
52const mat \textbf{\_\-R} ()}
53\label{classbdm_1_1EKFfull_d4f57cb8af64b06c530f528c32596d4d}
54
55\end{CompactItemize}
56\begin{Indent}{\bf Constructors}\par
57\begin{CompactItemize}
58\item 
59virtual \hyperlink{classbdm_1_1BM}{BM} $\ast$ \hyperlink{classbdm_1_1BM_c0f027ff91d8459937c6f60ff8e553ff}{\_\-copy\_\-} ()
60\end{CompactItemize}
61\end{Indent}
62\begin{Indent}{\bf Mathematical operations}\par
63\begin{CompactItemize}
64\item 
65\hypertarget{classbdm_1_1BM_1dee3fddaf021e62d925289660a707dc}{
66virtual void \hyperlink{classbdm_1_1BM_1dee3fddaf021e62d925289660a707dc}{bayesB} (const mat \&Dt)}
67\label{classbdm_1_1BM_1dee3fddaf021e62d925289660a707dc}
68
69\begin{CompactList}\small\item\em Batch Bayes rule (columns of Dt are observations). \item\end{CompactList}\item 
70virtual double \hyperlink{classbdm_1_1BM_50257e0c1e5b5c73153ea6e716ad8ae0}{logpred} (const vec \&dt) const
71\item 
72\hypertarget{classbdm_1_1BM_0e8ebe61fb14990abe1254bd3dda5fae}{
73vec \hyperlink{classbdm_1_1BM_0e8ebe61fb14990abe1254bd3dda5fae}{logpred\_\-m} (const mat \&dt) const }
74\label{classbdm_1_1BM_0e8ebe61fb14990abe1254bd3dda5fae}
75
76\begin{CompactList}\small\item\em Matrix version of logpred. \item\end{CompactList}\item 
77\hypertarget{classbdm_1_1BM_688d7a2aced1e06aa1c468d73a9e5eba}{
78virtual \hyperlink{classbdm_1_1epdf}{epdf} $\ast$ \hyperlink{classbdm_1_1BM_688d7a2aced1e06aa1c468d73a9e5eba}{epredictor} () const }
79\label{classbdm_1_1BM_688d7a2aced1e06aa1c468d73a9e5eba}
80
81\begin{CompactList}\small\item\em Constructs a predictive density $ f(d_{t+1} |d_{t}, \ldots d_{0}) $. \item\end{CompactList}\item 
82\hypertarget{classbdm_1_1BM_598b25e3f3d96a5bc00a5faeb5b3c912}{
83virtual \hyperlink{classbdm_1_1mpdf}{mpdf} $\ast$ \hyperlink{classbdm_1_1BM_598b25e3f3d96a5bc00a5faeb5b3c912}{predictor} () const }
84\label{classbdm_1_1BM_598b25e3f3d96a5bc00a5faeb5b3c912}
85
86\begin{CompactList}\small\item\em Constructs a conditional density 1-step ahead predictor. \item\end{CompactList}\end{CompactItemize}
87\end{Indent}
88\begin{Indent}{\bf Access to attributes}\par
89\begin{CompactItemize}
90\item 
91\hypertarget{classbdm_1_1BM_ff2d8755ba0b3def927d31305c03b09c}{
92const \hyperlink{classbdm_1_1RV}{RV} \& \textbf{\_\-drv} () const }
93\label{classbdm_1_1BM_ff2d8755ba0b3def927d31305c03b09c}
94
95\item 
96\hypertarget{classbdm_1_1BM_f135ae6dce7e9f30c9f88229c7930b96}{
97void \textbf{set\_\-drv} (const \hyperlink{classbdm_1_1RV}{RV} \&rv)}
98\label{classbdm_1_1BM_f135ae6dce7e9f30c9f88229c7930b96}
99
100\item 
101\hypertarget{classbdm_1_1BM_b38d92f17620813ad872d86e01a26e5e}{
102void \textbf{set\_\-rv} (const \hyperlink{classbdm_1_1RV}{RV} \&rv)}
103\label{classbdm_1_1BM_b38d92f17620813ad872d86e01a26e5e}
104
105\item 
106\hypertarget{classbdm_1_1BM_5be65d37dedfe33a3671e7065f523a70}{
107double \textbf{\_\-ll} () const }
108\label{classbdm_1_1BM_5be65d37dedfe33a3671e7065f523a70}
109
110\item 
111\hypertarget{classbdm_1_1BM_236b3abbcc93594fc97cd86d82c1a83f}{
112void \textbf{set\_\-evalll} (bool evl0)}
113\label{classbdm_1_1BM_236b3abbcc93594fc97cd86d82c1a83f}
114
115\end{CompactItemize}
116\end{Indent}
117\subsection*{Public Attributes}
118\begin{CompactItemize}
119\item 
120\hypertarget{classbdm_1_1KalmanFull_2defb75e58892615c5f95fd844f3a666}{
121vec \hyperlink{classbdm_1_1KalmanFull_2defb75e58892615c5f95fd844f3a666}{mu}}
122\label{classbdm_1_1KalmanFull_2defb75e58892615c5f95fd844f3a666}
123
124\begin{CompactList}\small\item\em Mean value of the posterior density. \item\end{CompactList}\item 
125\hypertarget{classbdm_1_1KalmanFull_acacd228e100c3e937de575ad2d7cd9c}{
126mat \hyperlink{classbdm_1_1KalmanFull_acacd228e100c3e937de575ad2d7cd9c}{P}}
127\label{classbdm_1_1KalmanFull_acacd228e100c3e937de575ad2d7cd9c}
128
129\begin{CompactList}\small\item\em Variance of the posterior density. \item\end{CompactList}\item 
130\hypertarget{classbdm_1_1KalmanFull_0dba34bfba2aedd8c488692bcd14869b}{
131bool \textbf{evalll}}
132\label{classbdm_1_1KalmanFull_0dba34bfba2aedd8c488692bcd14869b}
133
134\item 
135\hypertarget{classbdm_1_1KalmanFull_363ade67bd5a06c6a45c41e4d8afe11e}{
136double \textbf{ll}}
137\label{classbdm_1_1KalmanFull_363ade67bd5a06c6a45c41e4d8afe11e}
138
139\end{CompactItemize}
140\subsection*{Protected Attributes}
141\begin{CompactItemize}
142\item 
143\hypertarget{classbdm_1_1KalmanFull_427886a66cde0354e041ddef5aa60eab}{
144int \textbf{dimx}}
145\label{classbdm_1_1KalmanFull_427886a66cde0354e041ddef5aa60eab}
146
147\item 
148\hypertarget{classbdm_1_1KalmanFull_2b0399b8904ccb81c2098cc3cc85ff8f}{
149int \textbf{dimy}}
150\label{classbdm_1_1KalmanFull_2b0399b8904ccb81c2098cc3cc85ff8f}
151
152\item 
153\hypertarget{classbdm_1_1KalmanFull_8e886b5d535ba7f9a39e66be34116788}{
154int \textbf{dimu}}
155\label{classbdm_1_1KalmanFull_8e886b5d535ba7f9a39e66be34116788}
156
157\item 
158\hypertarget{classbdm_1_1KalmanFull_a24914cfc0297b9f3885df86e5011733}{
159mat \textbf{A}}
160\label{classbdm_1_1KalmanFull_a24914cfc0297b9f3885df86e5011733}
161
162\item 
163\hypertarget{classbdm_1_1KalmanFull_ef28133db32cc60b710925266c37376d}{
164mat \textbf{B}}
165\label{classbdm_1_1KalmanFull_ef28133db32cc60b710925266c37376d}
166
167\item 
168\hypertarget{classbdm_1_1KalmanFull_89ed156e063e19b32df2218bfaef42cf}{
169mat \textbf{C}}
170\label{classbdm_1_1KalmanFull_89ed156e063e19b32df2218bfaef42cf}
171
172\item 
173\hypertarget{classbdm_1_1KalmanFull_74e9f43b5b4d4a5e012e6178542d3e8f}{
174mat \textbf{D}}
175\label{classbdm_1_1KalmanFull_74e9f43b5b4d4a5e012e6178542d3e8f}
176
177\item 
178\hypertarget{classbdm_1_1KalmanFull_5c1fc8685511d21ba0e1688452105b7c}{
179mat \textbf{R}}
180\label{classbdm_1_1KalmanFull_5c1fc8685511d21ba0e1688452105b7c}
181
182\item 
183\hypertarget{classbdm_1_1KalmanFull_17d9a3316ecf81c149c2c1affb11af58}{
184mat \textbf{Q}}
185\label{classbdm_1_1KalmanFull_17d9a3316ecf81c149c2c1affb11af58}
186
187\item 
188\hypertarget{classbdm_1_1KalmanFull_f7fc60eca2893328d42f92246526d4b9}{
189mat \textbf{\_\-Pp}}
190\label{classbdm_1_1KalmanFull_f7fc60eca2893328d42f92246526d4b9}
191
192\item 
193\hypertarget{classbdm_1_1KalmanFull_b85742b33f95077f360a03ca2de05261}{
194mat \textbf{\_\-Ry}}
195\label{classbdm_1_1KalmanFull_b85742b33f95077f360a03ca2de05261}
196
197\item 
198\hypertarget{classbdm_1_1KalmanFull_09472aa8c06e79944d7637b70bf4e401}{
199mat \textbf{\_\-iRy}}
200\label{classbdm_1_1KalmanFull_09472aa8c06e79944d7637b70bf4e401}
201
202\item 
203\hypertarget{classbdm_1_1KalmanFull_7455b5deee5f14d978c82c5cc9357e29}{
204mat \textbf{\_\-K}}
205\label{classbdm_1_1KalmanFull_7455b5deee5f14d978c82c5cc9357e29}
206
207\item 
208\hypertarget{classbdm_1_1BM_c400357e37d27a4834b2b1d9211009ed}{
209\hyperlink{classbdm_1_1RV}{RV} \hyperlink{classbdm_1_1BM_c400357e37d27a4834b2b1d9211009ed}{drv}}
210\label{classbdm_1_1BM_c400357e37d27a4834b2b1d9211009ed}
211
212\begin{CompactList}\small\item\em Random variable of the data (optional). \item\end{CompactList}\item 
213\hypertarget{classbdm_1_1BM_4064b6559d962633e4372b12f4cd204a}{
214double \hyperlink{classbdm_1_1BM_4064b6559d962633e4372b12f4cd204a}{ll}}
215\label{classbdm_1_1BM_4064b6559d962633e4372b12f4cd204a}
216
217\begin{CompactList}\small\item\em Logarithm of marginalized data likelihood. \item\end{CompactList}\item 
218\hypertarget{classbdm_1_1BM_faff0ad12556fe7dc0e2807d4fd938ee}{
219bool \hyperlink{classbdm_1_1BM_faff0ad12556fe7dc0e2807d4fd938ee}{evalll}}
220\label{classbdm_1_1BM_faff0ad12556fe7dc0e2807d4fd938ee}
221
222\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}
223\subsection*{Friends}
224\begin{CompactItemize}
225\item 
226\hypertarget{classbdm_1_1KalmanFull_86ba216243ed95bb46d80d88775d16af}{
227std::ostream \& \hyperlink{classbdm_1_1KalmanFull_86ba216243ed95bb46d80d88775d16af}{operator$<$$<$} (std::ostream \&os, const \hyperlink{classbdm_1_1KalmanFull}{KalmanFull} \&kf)}
228\label{classbdm_1_1KalmanFull_86ba216243ed95bb46d80d88775d16af}
229
230\begin{CompactList}\small\item\em print elements of KF \item\end{CompactList}\end{CompactItemize}
231
232
233\subsection{Member Function Documentation}
234\hypertarget{classbdm_1_1BM_c0f027ff91d8459937c6f60ff8e553ff}{
235\index{bdm::EKFfull@{bdm::EKFfull}!\_\-copy\_\-@{\_\-copy\_\-}}
236\index{\_\-copy\_\-@{\_\-copy\_\-}!bdm::EKFfull@{bdm::EKFfull}}
237\subsubsection[\_\-copy\_\-]{\setlength{\rightskip}{0pt plus 5cm}virtual {\bf BM}$\ast$ bdm::BM::\_\-copy\_\- ()\hspace{0.3cm}{\tt  \mbox{[}inline, virtual, inherited\mbox{]}}}}
238\label{classbdm_1_1BM_c0f027ff91d8459937c6f60ff8e553ff}
239
240
241Copy function required in vectors, Arrays of \hyperlink{classbdm_1_1BM}{BM} etc. Have to be DELETED manually! Prototype:
242
243\begin{Code}\begin{verbatim} BM* _copy_(){return new BM(*this);} 
244\end{verbatim}
245\end{Code}
246
247 
248
249Reimplemented in \hyperlink{classbdm_1_1ARX_60c40b5c6abc4c7e464b4ccae64a5a61}{bdm::ARX}.\hypertarget{classbdm_1_1BM_50257e0c1e5b5c73153ea6e716ad8ae0}{
250\index{bdm::EKFfull@{bdm::EKFfull}!logpred@{logpred}}
251\index{logpred@{logpred}!bdm::EKFfull@{bdm::EKFfull}}
252\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{]}}}}
253\label{classbdm_1_1BM_50257e0c1e5b5c73153ea6e716ad8ae0}
254
255
256Evaluates predictive log-likelihood of the given data record I.e. marginal likelihood of the data with the posterior integrated out.
257
258Reimplemented in \hyperlink{classbdm_1_1ARX_080a7e531e3aa06694112863b15bc6a4}{bdm::ARX}, \hyperlink{classbdm_1_1MixEF_da724da464a75e07521941e430929efa}{bdm::MixEF}, and \hyperlink{classbdm_1_1multiBM_e157b607c1e3fa91d42aeea44458e2bf}{bdm::multiBM}.
259
260Referenced by bdm::BM::logpred\_\-m().
261
262The documentation for this class was generated from the following files:\begin{CompactItemize}
263\item 
264\hyperlink{libKF_8h}{libKF.h}\item 
265libKF.cpp\end{CompactItemize}
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