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1\hypertarget{classEKFful__unQR}{
2\section{EKFful\_\-unQR Class Reference}
3\label{classEKFful__unQR}\index{EKFful\_\-unQR@{EKFful\_\-unQR}}
4}
5Extended \hyperlink{classKalman}{Kalman} filter with unknown {\tt Q} and {\tt R}
6
7
8{\tt \#include $<$ekf\_\-templ.h$>$}
9
10Inheritance diagram for EKFful\_\-unQR:\nopagebreak
11\begin{figure}[H]
12\begin{center}
13\leavevmode
14\includegraphics[width=102pt]{classEKFful__unQR__inherit__graph}
15\end{center}
16\end{figure}
17Collaboration diagram for EKFful\_\-unQR:\nopagebreak
18\begin{figure}[H]
19\begin{center}
20\leavevmode
21\includegraphics[height=400pt]{classEKFful__unQR__coll__graph}
22\end{center}
23\end{figure}
24\subsection*{Public Member Functions}
25\begin{CompactItemize}
26\item 
27\hypertarget{classEKFful__unQR_873e3a72264f6e777c4443220db15d79}{
28\hyperlink{classEKFful__unQR_873e3a72264f6e777c4443220db15d79}{EKFful\_\-unQR} (\hyperlink{classRV}{RV} rx, \hyperlink{classRV}{RV} ry, \hyperlink{classRV}{RV} ru, \hyperlink{classRV}{RV} rQR)}
29\label{classEKFful__unQR_873e3a72264f6e777c4443220db15d79}
30
31\begin{CompactList}\small\item\em Default constructor. \item\end{CompactList}\item 
32\hypertarget{classEKFful__unQR_b586e534c8a8d219561b0c020329d412}{
33void \hyperlink{classEKFful__unQR_b586e534c8a8d219561b0c020329d412}{condition} (const vec \&QR0)}
34\label{classEKFful__unQR_b586e534c8a8d219561b0c020329d412}
35
36\begin{CompactList}\small\item\em Substitute {\tt val} for {\tt rvc}. \item\end{CompactList}\item 
37\hypertarget{classEKFfull_fc753106e0d4cf68e4f2160fd54458c0}{
38void \hyperlink{classEKFfull_fc753106e0d4cf68e4f2160fd54458c0}{set\_\-parameters} (\hyperlink{classdiffbifn}{diffbifn} $\ast$pfxu, \hyperlink{classdiffbifn}{diffbifn} $\ast$phxu, const mat Q0, const mat R0)}
39\label{classEKFfull_fc753106e0d4cf68e4f2160fd54458c0}
40
41\begin{CompactList}\small\item\em Set nonlinear functions for mean values and covariance matrices. \item\end{CompactList}\item 
42\hypertarget{classEKFfull_8ca46f177e395fa714bbd8bd29ea43e0}{
43void \hyperlink{classEKFfull_8ca46f177e395fa714bbd8bd29ea43e0}{bayes} (const vec \&dt)}
44\label{classEKFfull_8ca46f177e395fa714bbd8bd29ea43e0}
45
46\begin{CompactList}\small\item\em Here dt = \mbox{[}yt;ut\mbox{]} of appropriate dimensions. \item\end{CompactList}\item 
47\hypertarget{classEKFfull_7bb76ea74c144ea0b36db99f94750b7b}{
48void \hyperlink{classEKFfull_7bb76ea74c144ea0b36db99f94750b7b}{set\_\-est} (vec mu0, mat P0)}
49\label{classEKFfull_7bb76ea74c144ea0b36db99f94750b7b}
50
51\begin{CompactList}\small\item\em set estimates \item\end{CompactList}\item 
52\hypertarget{classEKFfull_170a748ad944bdebb0b3073463876abe}{
53const \hyperlink{classepdf}{epdf} \& \hyperlink{classEKFfull_170a748ad944bdebb0b3073463876abe}{\_\-epdf} () const }
54\label{classEKFfull_170a748ad944bdebb0b3073463876abe}
55
56\begin{CompactList}\small\item\em dummy! \item\end{CompactList}\item 
57\hypertarget{classBM_0186270f75189677f390fe088a9947e9}{
58virtual void \hyperlink{classBM_0186270f75189677f390fe088a9947e9}{bayesB} (const mat \&Dt)}
59\label{classBM_0186270f75189677f390fe088a9947e9}
60
61\begin{CompactList}\small\item\em Batch Bayes rule (columns of Dt are observations). \item\end{CompactList}\item 
62virtual double \hyperlink{classBM_8a8ce6df431689964c41cc6c849cfd06}{logpred} (const vec \&dt) const
63\item 
64\hypertarget{classBM_126bd2595c48e311fc2a7ab72876092a}{
65const \hyperlink{classRV}{RV} \& \hyperlink{classBM_126bd2595c48e311fc2a7ab72876092a}{\_\-rv} () const }
66\label{classBM_126bd2595c48e311fc2a7ab72876092a}
67
68\begin{CompactList}\small\item\em access function \item\end{CompactList}\item 
69\hypertarget{classBM_87f4a547d2c29180be88175e5eab9c88}{
70double \hyperlink{classBM_87f4a547d2c29180be88175e5eab9c88}{\_\-ll} () const }
71\label{classBM_87f4a547d2c29180be88175e5eab9c88}
72
73\begin{CompactList}\small\item\em access function \item\end{CompactList}\item 
74\hypertarget{classBM_1ffa9f23669aabecc3760c06c6987522}{
75void \hyperlink{classBM_1ffa9f23669aabecc3760c06c6987522}{set\_\-evalll} (bool evl0)}
76\label{classBM_1ffa9f23669aabecc3760c06c6987522}
77
78\begin{CompactList}\small\item\em access function \item\end{CompactList}\item 
79virtual \hyperlink{classBM}{BM} $\ast$ \hyperlink{classBM_eb58c81d6a7b75b05fc6f276eed78887}{\_\-copy\_\-} (bool changerv=false)
80\item 
81\hypertarget{classBMcond_3fa60348b2da6b4208bb95b8d146900a}{
82const \hyperlink{classRV}{RV} \& \hyperlink{classBMcond_3fa60348b2da6b4208bb95b8d146900a}{\_\-rvc} () const }
83\label{classBMcond_3fa60348b2da6b4208bb95b8d146900a}
84
85\begin{CompactList}\small\item\em access function \item\end{CompactList}\end{CompactItemize}
86\subsection*{Public Attributes}
87\begin{CompactItemize}
88\item 
89\hypertarget{classKalmanFull_fb5aec635e2720cc5ac31bc01c18a68a}{
90vec \hyperlink{classKalmanFull_fb5aec635e2720cc5ac31bc01c18a68a}{mu}}
91\label{classKalmanFull_fb5aec635e2720cc5ac31bc01c18a68a}
92
93\begin{CompactList}\small\item\em Mean value of the posterior density. \item\end{CompactList}\item 
94\hypertarget{classKalmanFull_b75dc059e84fa8ffc076203b30f926cc}{
95mat \hyperlink{classKalmanFull_b75dc059e84fa8ffc076203b30f926cc}{P}}
96\label{classKalmanFull_b75dc059e84fa8ffc076203b30f926cc}
97
98\begin{CompactList}\small\item\em Variance of the posterior density. \item\end{CompactList}\item 
99\hypertarget{classKalmanFull_c17d69e125acd2673e6688fd86dd3f84}{
100bool \textbf{evalll}}
101\label{classKalmanFull_c17d69e125acd2673e6688fd86dd3f84}
102
103\item 
104\hypertarget{classKalmanFull_3aa4bf6128980d0627413dcf9cd07308}{
105double \textbf{ll}}
106\label{classKalmanFull_3aa4bf6128980d0627413dcf9cd07308}
107
108\end{CompactItemize}
109\subsection*{Protected Attributes}
110\begin{CompactItemize}
111\item 
112\hypertarget{classKalmanFull_c5353e66238ed717dba79e0499118226}{
113int \textbf{dimx}}
114\label{classKalmanFull_c5353e66238ed717dba79e0499118226}
115
116\item 
117\hypertarget{classKalmanFull_761fadcc12dd4cb83bb8b5e27db01947}{
118int \textbf{dimy}}
119\label{classKalmanFull_761fadcc12dd4cb83bb8b5e27db01947}
120
121\item 
122\hypertarget{classKalmanFull_609a4a0fcde78fd7aac2f01b34e952c9}{
123int \textbf{dimu}}
124\label{classKalmanFull_609a4a0fcde78fd7aac2f01b34e952c9}
125
126\item 
127\hypertarget{classKalmanFull_554de4c953761380cd5a14a02542e007}{
128mat \textbf{A}}
129\label{classKalmanFull_554de4c953761380cd5a14a02542e007}
130
131\item 
132\hypertarget{classKalmanFull_ac7ade2a603a1b05419e36c5aae21755}{
133mat \textbf{B}}
134\label{classKalmanFull_ac7ade2a603a1b05419e36c5aae21755}
135
136\item 
137\hypertarget{classKalmanFull_5a9a8326ae17b519109fcdad59ea74a3}{
138mat \textbf{C}}
139\label{classKalmanFull_5a9a8326ae17b519109fcdad59ea74a3}
140
141\item 
142\hypertarget{classKalmanFull_8f992a2d6b66d2e8bd9174b28cc0f074}{
143mat \textbf{D}}
144\label{classKalmanFull_8f992a2d6b66d2e8bd9174b28cc0f074}
145
146\item 
147\hypertarget{classKalmanFull_bbd2dab10da47237a5f0d9e55fd61f24}{
148mat \textbf{R}}
149\label{classKalmanFull_bbd2dab10da47237a5f0d9e55fd61f24}
150
151\item 
152\hypertarget{classKalmanFull_a8777c1fe67763395d3ddeb326239851}{
153mat \textbf{Q}}
154\label{classKalmanFull_a8777c1fe67763395d3ddeb326239851}
155
156\item 
157\hypertarget{classKalmanFull_905823cf4157a11b8b824e45809dac55}{
158mat \textbf{\_\-Pp}}
159\label{classKalmanFull_905823cf4157a11b8b824e45809dac55}
160
161\item 
162\hypertarget{classKalmanFull_b1b946b3a43f7d86cf4b6dc0dd6e3210}{
163mat \textbf{\_\-Ry}}
164\label{classKalmanFull_b1b946b3a43f7d86cf4b6dc0dd6e3210}
165
166\item 
167\hypertarget{classKalmanFull_c7d915386a9d60b1bc309ae9166764f6}{
168mat \textbf{\_\-iRy}}
169\label{classKalmanFull_c7d915386a9d60b1bc309ae9166764f6}
170
171\item 
172\hypertarget{classKalmanFull_4c8354ea4801529f3071189ddd10d760}{
173mat \textbf{\_\-K}}
174\label{classKalmanFull_4c8354ea4801529f3071189ddd10d760}
175
176\item 
177\hypertarget{classBM_bf6fb59b30141074f8ee1e2f43d03129}{
178bool \hyperlink{classBM_bf6fb59b30141074f8ee1e2f43d03129}{evalll}}
179\label{classBM_bf6fb59b30141074f8ee1e2f43d03129}
180
181\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 
182\hypertarget{classBM_5623fef6572a08c2b53b8c87b82dc979}{
183double \hyperlink{classBM_5623fef6572a08c2b53b8c87b82dc979}{ll}}
184\label{classBM_5623fef6572a08c2b53b8c87b82dc979}
185
186\begin{CompactList}\small\item\em Logarithm of marginalized data likelihood. \item\end{CompactList}\item 
187\hypertarget{classBM_af00f0612fabe66241dd507188cdbf88}{
188\hyperlink{classRV}{RV} \hyperlink{classBM_af00f0612fabe66241dd507188cdbf88}{rv}}
189\label{classBM_af00f0612fabe66241dd507188cdbf88}
190
191\begin{CompactList}\small\item\em Random variable of the posterior. \item\end{CompactList}\item 
192\hypertarget{classBMcond_9ba793c8ec453f04d372d17195ed8dec}{
193\hyperlink{classRV}{RV} \hyperlink{classBMcond_9ba793c8ec453f04d372d17195ed8dec}{rvc}}
194\label{classBMcond_9ba793c8ec453f04d372d17195ed8dec}
195
196\begin{CompactList}\small\item\em Identificator of the conditioning variable. \item\end{CompactList}\end{CompactItemize}
197\subsection*{Friends}
198\begin{CompactItemize}
199\item 
200\hypertarget{classKalmanFull_86ba216243ed95bb46d80d88775d16af}{
201std::ostream \& \hyperlink{classKalmanFull_86ba216243ed95bb46d80d88775d16af}{operator$<$$<$} (std::ostream \&os, const \hyperlink{classKalmanFull}{KalmanFull} \&kf)}
202\label{classKalmanFull_86ba216243ed95bb46d80d88775d16af}
203
204\begin{CompactList}\small\item\em print elements of KF \item\end{CompactList}\end{CompactItemize}
205
206
207\subsection{Detailed Description}
208Extended \hyperlink{classKalman}{Kalman} filter with unknown {\tt Q} and {\tt R}.
209
210\subsection{Member Function Documentation}
211\hypertarget{classBM_8a8ce6df431689964c41cc6c849cfd06}{
212\index{EKFful\_\-unQR@{EKFful\_\-unQR}!logpred@{logpred}}
213\index{logpred@{logpred}!EKFful_unQR@{EKFful\_\-unQR}}
214\subsubsection[logpred]{\setlength{\rightskip}{0pt plus 5cm}virtual double BM::logpred (const vec \& {\em dt}) const\hspace{0.3cm}{\tt  \mbox{[}inline, virtual, inherited\mbox{]}}}}
215\label{classBM_8a8ce6df431689964c41cc6c849cfd06}
216
217
218Evaluates predictive log-likelihood of the given data record I.e. marginal likelihood of the data with the posterior integrated out.
219
220Reimplemented in \hyperlink{classARX_e7f9e7823aec9bf7ddc3b42d9b3304c4}{ARX}, \hyperlink{classMixEF_424ca64f36d4e41de7a7e7ae921d35ea}{MixEF}, and \hyperlink{classmultiBM_13e26a61757278981fd8cac9a7ef91eb}{multiBM}.\hypertarget{classBM_eb58c81d6a7b75b05fc6f276eed78887}{
221\index{EKFful\_\-unQR@{EKFful\_\-unQR}!\_\-copy\_\-@{\_\-copy\_\-}}
222\index{\_\-copy\_\-@{\_\-copy\_\-}!EKFful_unQR@{EKFful\_\-unQR}}
223\subsubsection[\_\-copy\_\-]{\setlength{\rightskip}{0pt plus 5cm}virtual {\bf BM}$\ast$ BM::\_\-copy\_\- (bool {\em changerv} = {\tt false})\hspace{0.3cm}{\tt  \mbox{[}inline, virtual, inherited\mbox{]}}}}
224\label{classBM_eb58c81d6a7b75b05fc6f276eed78887}
225
226
227Copy function required in vectors, Arrays of \hyperlink{classBM}{BM} etc. Have to be DELETED manually! Prototype: BM$\ast$ \hyperlink{classBM_eb58c81d6a7b75b05fc6f276eed78887}{\_\-copy\_\-()}\{\hyperlink{classBM}{BM} Tmp$\ast$=new Tmp(this$\ast$); return Tmp; \} 
228
229Reimplemented in \hyperlink{classARX_d2751057811c6fb8f4ff86e1648bcddc}{ARX}.
230
231Referenced by MixEF::MixEF().
232
233The documentation for this class was generated from the following file:\begin{CompactItemize}
234\item 
235work/git/mixpp/bdm/estim/\hyperlink{ekf__templ_8h}{ekf\_\-templ.h}\end{CompactItemize}
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