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[261]1\hypertarget{classbdm_1_1EKFful__unQR}{
2\section{bdm::EKFful\_\-unQR Class Reference}
3\label{classbdm_1_1EKFful__unQR}\index{bdm::EKFful\_\-unQR@{bdm::EKFful\_\-unQR}}
4}
5{\tt \#include $<$ekf\_\-templ.h$>$}
6
[271]7Inheritance diagram for bdm::EKFful\_\-unQR::\begin{figure}[H]
[261]8\begin{center}
9\leavevmode
[271]10\includegraphics[height=4cm]{classbdm_1_1EKFful__unQR}
[261]11\end{center}
12\end{figure}
[270]13
14
15\subsection{Detailed Description}
16Extended \hyperlink{classbdm_1_1Kalman}{Kalman} filter with unknown {\tt Q} and {\tt R}. \subsection*{Public Member Functions}
[261]17\begin{CompactItemize}
18\item 
19\hypertarget{classbdm_1_1EKFful__unQR_58cd78b3bfcf989add9404de2982b281}{
20\hyperlink{classbdm_1_1EKFful__unQR_58cd78b3bfcf989add9404de2982b281}{EKFful\_\-unQR} (\hyperlink{classbdm_1_1RV}{RV} rx, \hyperlink{classbdm_1_1RV}{RV} ry, \hyperlink{classbdm_1_1RV}{RV} ru, \hyperlink{classbdm_1_1RV}{RV} rQR)}
21\label{classbdm_1_1EKFful__unQR_58cd78b3bfcf989add9404de2982b281}
22
23\begin{CompactList}\small\item\em Default constructor. \item\end{CompactList}\item 
24\hypertarget{classbdm_1_1EKFful__unQR_17a98c06f5efe38e0da0beb96d6f9584}{
25void \hyperlink{classbdm_1_1EKFful__unQR_17a98c06f5efe38e0da0beb96d6f9584}{condition} (const vec \&QR0)}
26\label{classbdm_1_1EKFful__unQR_17a98c06f5efe38e0da0beb96d6f9584}
27
28\begin{CompactList}\small\item\em Substitute {\tt val} for {\tt rvc}. \item\end{CompactList}\item 
29\hypertarget{classbdm_1_1EKFfull_78748da361ba61fef162b0d8956d1743}{
30void \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)}
31\label{classbdm_1_1EKFfull_78748da361ba61fef162b0d8956d1743}
32
33\begin{CompactList}\small\item\em Set nonlinear functions for mean values and covariance matrices. \item\end{CompactList}\item 
34\hypertarget{classbdm_1_1EKFfull_f149ae8e9ce14d9931a7bb2850736699}{
35void \hyperlink{classbdm_1_1EKFfull_f149ae8e9ce14d9931a7bb2850736699}{bayes} (const vec \&dt)}
36\label{classbdm_1_1EKFfull_f149ae8e9ce14d9931a7bb2850736699}
37
38\begin{CompactList}\small\item\em Here dt = \mbox{[}yt;ut\mbox{]} of appropriate dimensions. \item\end{CompactList}\item 
39\hypertarget{classbdm_1_1EKFfull_7562b3d3c17241dab3baf70258742eb2}{
40void \hyperlink{classbdm_1_1EKFfull_7562b3d3c17241dab3baf70258742eb2}{set\_\-est} (vec mu0, mat P0)}
41\label{classbdm_1_1EKFfull_7562b3d3c17241dab3baf70258742eb2}
42
43\begin{CompactList}\small\item\em set estimates \item\end{CompactList}\item 
[271]44\hypertarget{classbdm_1_1EKFfull_7e9a69f36a0a0615c9abb806772ef36d}{
45const \hyperlink{classbdm_1_1epdf}{epdf} \& \hyperlink{classbdm_1_1EKFfull_7e9a69f36a0a0615c9abb806772ef36d}{posterior} () const }
46\label{classbdm_1_1EKFfull_7e9a69f36a0a0615c9abb806772ef36d}
[261]47
48\begin{CompactList}\small\item\em dummy! \item\end{CompactList}\item 
49\hypertarget{classbdm_1_1EKFfull_3d0e427d4d2fb7ac20358ce629f5d510}{
[270]50const \hyperlink{classbdm_1_1enorm}{enorm}$<$ \hyperlink{classfsqmat}{fsqmat} $>$ $\ast$ \textbf{\_\-e} () const }
[261]51\label{classbdm_1_1EKFfull_3d0e427d4d2fb7ac20358ce629f5d510}
52
[270]53\item 
[261]54\hypertarget{classbdm_1_1EKFfull_d4f57cb8af64b06c530f528c32596d4d}{
55const mat \textbf{\_\-R} ()}
56\label{classbdm_1_1EKFfull_d4f57cb8af64b06c530f528c32596d4d}
57
58\item 
[270]59\hypertarget{classbdm_1_1BMcond_7506910f93250b44fea505ec4ffb19dc}{
60const \hyperlink{classbdm_1_1RV}{RV} \& \hyperlink{classbdm_1_1BMcond_7506910f93250b44fea505ec4ffb19dc}{\_\-rvc} () const }
61\label{classbdm_1_1BMcond_7506910f93250b44fea505ec4ffb19dc}
62
63\begin{CompactList}\small\item\em access function \item\end{CompactList}\end{CompactItemize}
64\begin{Indent}{\bf Constructors}\par
65\begin{CompactItemize}
66\item 
67virtual \hyperlink{classbdm_1_1BM}{BM} $\ast$ \hyperlink{classbdm_1_1BM_c0f027ff91d8459937c6f60ff8e553ff}{\_\-copy\_\-} ()
68\end{CompactItemize}
69\end{Indent}
70\begin{Indent}{\bf Mathematical operations}\par
71\begin{CompactItemize}
72\item 
[261]73\hypertarget{classbdm_1_1BM_1dee3fddaf021e62d925289660a707dc}{
74virtual void \hyperlink{classbdm_1_1BM_1dee3fddaf021e62d925289660a707dc}{bayesB} (const mat \&Dt)}
75\label{classbdm_1_1BM_1dee3fddaf021e62d925289660a707dc}
76
77\begin{CompactList}\small\item\em Batch Bayes rule (columns of Dt are observations). \item\end{CompactList}\item 
78virtual double \hyperlink{classbdm_1_1BM_50257e0c1e5b5c73153ea6e716ad8ae0}{logpred} (const vec \&dt) const
79\item 
80\hypertarget{classbdm_1_1BM_0e8ebe61fb14990abe1254bd3dda5fae}{
81vec \hyperlink{classbdm_1_1BM_0e8ebe61fb14990abe1254bd3dda5fae}{logpred\_\-m} (const mat \&dt) const }
82\label{classbdm_1_1BM_0e8ebe61fb14990abe1254bd3dda5fae}
83
84\begin{CompactList}\small\item\em Matrix version of logpred. \item\end{CompactList}\item 
[270]85\hypertarget{classbdm_1_1BM_688d7a2aced1e06aa1c468d73a9e5eba}{
86virtual \hyperlink{classbdm_1_1epdf}{epdf} $\ast$ \hyperlink{classbdm_1_1BM_688d7a2aced1e06aa1c468d73a9e5eba}{epredictor} () const }
87\label{classbdm_1_1BM_688d7a2aced1e06aa1c468d73a9e5eba}
[261]88
[270]89\begin{CompactList}\small\item\em Constructs a predictive density $ f(d_{t+1} |d_{t}, \ldots d_{0}) $. \item\end{CompactList}\item 
90\hypertarget{classbdm_1_1BM_598b25e3f3d96a5bc00a5faeb5b3c912}{
91virtual \hyperlink{classbdm_1_1mpdf}{mpdf} $\ast$ \hyperlink{classbdm_1_1BM_598b25e3f3d96a5bc00a5faeb5b3c912}{predictor} () const }
92\label{classbdm_1_1BM_598b25e3f3d96a5bc00a5faeb5b3c912}
[261]93
[270]94\begin{CompactList}\small\item\em Constructs a conditional density 1-step ahead predictor. \item\end{CompactList}\end{CompactItemize}
95\end{Indent}
96\begin{Indent}{\bf Access to attributes}\par
97\begin{CompactItemize}
98\item 
[269]99\hypertarget{classbdm_1_1BM_ff2d8755ba0b3def927d31305c03b09c}{
[270]100const \hyperlink{classbdm_1_1RV}{RV} \& \textbf{\_\-drv} () const }
[269]101\label{classbdm_1_1BM_ff2d8755ba0b3def927d31305c03b09c}
102
[270]103\item 
[269]104\hypertarget{classbdm_1_1BM_f135ae6dce7e9f30c9f88229c7930b96}{
[270]105void \textbf{set\_\-drv} (const \hyperlink{classbdm_1_1RV}{RV} \&rv)}
[269]106\label{classbdm_1_1BM_f135ae6dce7e9f30c9f88229c7930b96}
107
[270]108\item 
[271]109\hypertarget{classbdm_1_1BM_b38d92f17620813ad872d86e01a26e5e}{
110void \textbf{set\_\-rv} (const \hyperlink{classbdm_1_1RV}{RV} \&rv)}
111\label{classbdm_1_1BM_b38d92f17620813ad872d86e01a26e5e}
112
113\item 
[261]114\hypertarget{classbdm_1_1BM_5be65d37dedfe33a3671e7065f523a70}{
[270]115double \textbf{\_\-ll} () const }
[261]116\label{classbdm_1_1BM_5be65d37dedfe33a3671e7065f523a70}
117
[270]118\item 
[261]119\hypertarget{classbdm_1_1BM_236b3abbcc93594fc97cd86d82c1a83f}{
[270]120void \textbf{set\_\-evalll} (bool evl0)}
[261]121\label{classbdm_1_1BM_236b3abbcc93594fc97cd86d82c1a83f}
122
[270]123\end{CompactItemize}
124\end{Indent}
[261]125\subsection*{Public Attributes}
126\begin{CompactItemize}
127\item 
128\hypertarget{classbdm_1_1KalmanFull_2defb75e58892615c5f95fd844f3a666}{
129vec \hyperlink{classbdm_1_1KalmanFull_2defb75e58892615c5f95fd844f3a666}{mu}}
130\label{classbdm_1_1KalmanFull_2defb75e58892615c5f95fd844f3a666}
131
132\begin{CompactList}\small\item\em Mean value of the posterior density. \item\end{CompactList}\item 
133\hypertarget{classbdm_1_1KalmanFull_acacd228e100c3e937de575ad2d7cd9c}{
134mat \hyperlink{classbdm_1_1KalmanFull_acacd228e100c3e937de575ad2d7cd9c}{P}}
135\label{classbdm_1_1KalmanFull_acacd228e100c3e937de575ad2d7cd9c}
136
137\begin{CompactList}\small\item\em Variance of the posterior density. \item\end{CompactList}\item 
138\hypertarget{classbdm_1_1KalmanFull_0dba34bfba2aedd8c488692bcd14869b}{
139bool \textbf{evalll}}
140\label{classbdm_1_1KalmanFull_0dba34bfba2aedd8c488692bcd14869b}
141
142\item 
143\hypertarget{classbdm_1_1KalmanFull_363ade67bd5a06c6a45c41e4d8afe11e}{
144double \textbf{ll}}
145\label{classbdm_1_1KalmanFull_363ade67bd5a06c6a45c41e4d8afe11e}
146
147\end{CompactItemize}
148\subsection*{Protected Attributes}
149\begin{CompactItemize}
150\item 
151\hypertarget{classbdm_1_1KalmanFull_427886a66cde0354e041ddef5aa60eab}{
152int \textbf{dimx}}
153\label{classbdm_1_1KalmanFull_427886a66cde0354e041ddef5aa60eab}
154
155\item 
156\hypertarget{classbdm_1_1KalmanFull_2b0399b8904ccb81c2098cc3cc85ff8f}{
157int \textbf{dimy}}
158\label{classbdm_1_1KalmanFull_2b0399b8904ccb81c2098cc3cc85ff8f}
159
160\item 
161\hypertarget{classbdm_1_1KalmanFull_8e886b5d535ba7f9a39e66be34116788}{
162int \textbf{dimu}}
163\label{classbdm_1_1KalmanFull_8e886b5d535ba7f9a39e66be34116788}
164
165\item 
166\hypertarget{classbdm_1_1KalmanFull_a24914cfc0297b9f3885df86e5011733}{
167mat \textbf{A}}
168\label{classbdm_1_1KalmanFull_a24914cfc0297b9f3885df86e5011733}
169
170\item 
171\hypertarget{classbdm_1_1KalmanFull_ef28133db32cc60b710925266c37376d}{
172mat \textbf{B}}
173\label{classbdm_1_1KalmanFull_ef28133db32cc60b710925266c37376d}
174
175\item 
176\hypertarget{classbdm_1_1KalmanFull_89ed156e063e19b32df2218bfaef42cf}{
177mat \textbf{C}}
178\label{classbdm_1_1KalmanFull_89ed156e063e19b32df2218bfaef42cf}
179
180\item 
181\hypertarget{classbdm_1_1KalmanFull_74e9f43b5b4d4a5e012e6178542d3e8f}{
182mat \textbf{D}}
183\label{classbdm_1_1KalmanFull_74e9f43b5b4d4a5e012e6178542d3e8f}
184
185\item 
186\hypertarget{classbdm_1_1KalmanFull_5c1fc8685511d21ba0e1688452105b7c}{
187mat \textbf{R}}
188\label{classbdm_1_1KalmanFull_5c1fc8685511d21ba0e1688452105b7c}
189
190\item 
191\hypertarget{classbdm_1_1KalmanFull_17d9a3316ecf81c149c2c1affb11af58}{
192mat \textbf{Q}}
193\label{classbdm_1_1KalmanFull_17d9a3316ecf81c149c2c1affb11af58}
194
195\item 
196\hypertarget{classbdm_1_1KalmanFull_f7fc60eca2893328d42f92246526d4b9}{
197mat \textbf{\_\-Pp}}
198\label{classbdm_1_1KalmanFull_f7fc60eca2893328d42f92246526d4b9}
199
200\item 
201\hypertarget{classbdm_1_1KalmanFull_b85742b33f95077f360a03ca2de05261}{
202mat \textbf{\_\-Ry}}
203\label{classbdm_1_1KalmanFull_b85742b33f95077f360a03ca2de05261}
204
205\item 
206\hypertarget{classbdm_1_1KalmanFull_09472aa8c06e79944d7637b70bf4e401}{
207mat \textbf{\_\-iRy}}
208\label{classbdm_1_1KalmanFull_09472aa8c06e79944d7637b70bf4e401}
209
210\item 
211\hypertarget{classbdm_1_1KalmanFull_7455b5deee5f14d978c82c5cc9357e29}{
212mat \textbf{\_\-K}}
213\label{classbdm_1_1KalmanFull_7455b5deee5f14d978c82c5cc9357e29}
214
215\item 
216\hypertarget{classbdm_1_1BM_faff0ad12556fe7dc0e2807d4fd938ee}{
217bool \hyperlink{classbdm_1_1BM_faff0ad12556fe7dc0e2807d4fd938ee}{evalll}}
218\label{classbdm_1_1BM_faff0ad12556fe7dc0e2807d4fd938ee}
219
220\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}\item 
221\hypertarget{classbdm_1_1BM_4064b6559d962633e4372b12f4cd204a}{
222double \hyperlink{classbdm_1_1BM_4064b6559d962633e4372b12f4cd204a}{ll}}
223\label{classbdm_1_1BM_4064b6559d962633e4372b12f4cd204a}
224
225\begin{CompactList}\small\item\em Logarithm of marginalized data likelihood. \item\end{CompactList}\item 
[269]226\hypertarget{classbdm_1_1BM_c400357e37d27a4834b2b1d9211009ed}{
227\hyperlink{classbdm_1_1RV}{RV} \hyperlink{classbdm_1_1BM_c400357e37d27a4834b2b1d9211009ed}{drv}}
228\label{classbdm_1_1BM_c400357e37d27a4834b2b1d9211009ed}
229
230\begin{CompactList}\small\item\em Random variable of the data (optional). \item\end{CompactList}\item 
[261]231\hypertarget{classbdm_1_1BMcond_9a12750776d977408aada06a70093297}{
232\hyperlink{classbdm_1_1RV}{RV} \hyperlink{classbdm_1_1BMcond_9a12750776d977408aada06a70093297}{rvc}}
233\label{classbdm_1_1BMcond_9a12750776d977408aada06a70093297}
234
235\begin{CompactList}\small\item\em Identificator of the conditioning variable. \item\end{CompactList}\end{CompactItemize}
236\subsection*{Friends}
237\begin{CompactItemize}
238\item 
239\hypertarget{classbdm_1_1KalmanFull_86ba216243ed95bb46d80d88775d16af}{
240std::ostream \& \hyperlink{classbdm_1_1KalmanFull_86ba216243ed95bb46d80d88775d16af}{operator$<$$<$} (std::ostream \&os, const \hyperlink{classbdm_1_1KalmanFull}{KalmanFull} \&kf)}
241\label{classbdm_1_1KalmanFull_86ba216243ed95bb46d80d88775d16af}
242
243\begin{CompactList}\small\item\em print elements of KF \item\end{CompactList}\end{CompactItemize}
244
245
[270]246\subsection{Member Function Documentation}
247\hypertarget{classbdm_1_1BM_c0f027ff91d8459937c6f60ff8e553ff}{
248\index{bdm::EKFful\_\-unQR@{bdm::EKFful\_\-unQR}!\_\-copy\_\-@{\_\-copy\_\-}}
249\index{\_\-copy\_\-@{\_\-copy\_\-}!bdm::EKFful_unQR@{bdm::EKFful\_\-unQR}}
250\subsubsection[\_\-copy\_\-]{\setlength{\rightskip}{0pt plus 5cm}virtual {\bf BM}$\ast$ bdm::BM::\_\-copy\_\- ()\hspace{0.3cm}{\tt  \mbox{[}inline, virtual, inherited\mbox{]}}}}
251\label{classbdm_1_1BM_c0f027ff91d8459937c6f60ff8e553ff}
[261]252
[270]253
254Copy function required in vectors, Arrays of \hyperlink{classbdm_1_1BM}{BM} etc. Have to be DELETED manually! Prototype:
255
256\begin{Code}\begin{verbatim} BM* _copy_(){return new BM(*this);} 
257\end{verbatim}
258\end{Code}
259
260 
261
262Reimplemented in \hyperlink{classbdm_1_1ARX_60c40b5c6abc4c7e464b4ccae64a5a61}{bdm::ARX}.\hypertarget{classbdm_1_1BM_50257e0c1e5b5c73153ea6e716ad8ae0}{
[261]263\index{bdm::EKFful\_\-unQR@{bdm::EKFful\_\-unQR}!logpred@{logpred}}
264\index{logpred@{logpred}!bdm::EKFful_unQR@{bdm::EKFful\_\-unQR}}
265\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{]}}}}
266\label{classbdm_1_1BM_50257e0c1e5b5c73153ea6e716ad8ae0}
267
268
269Evaluates predictive log-likelihood of the given data record I.e. marginal likelihood of the data with the posterior integrated out.
270
271Reimplemented in \hyperlink{classbdm_1_1ARX_080a7e531e3aa06694112863b15bc6a4}{bdm::ARX}, \hyperlink{classbdm_1_1MixEF_da724da464a75e07521941e430929efa}{bdm::MixEF}, and \hyperlink{classbdm_1_1multiBM_e157b607c1e3fa91d42aeea44458e2bf}{bdm::multiBM}.
272
[270]273Referenced by bdm::BM::logpred\_\-m().
[261]274
275The documentation for this class was generated from the following file:\begin{CompactItemize}
276\item 
277\hyperlink{ekf__templ_8h}{ekf\_\-templ.h}\end{CompactItemize}
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