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[172]1\hypertarget{classEKFful__unQR}{
[140]2\section{EKFful\_\-unQR Class Reference}
3\label{classEKFful__unQR}\index{EKFful\_\-unQR@{EKFful\_\-unQR}}
[172]4}
5Extended \hyperlink{classKalman}{Kalman} filter with unknown {\tt Q} and {\tt R}. 
[99]6
7
[140]8{\tt \#include $<$ekf\_\-templ.h$>$}
[99]9
[140]10Inheritance diagram for EKFful\_\-unQR:\nopagebreak
[99]11\begin{figure}[H]
12\begin{center}
13\leavevmode
[140]14\includegraphics[width=102pt]{classEKFful__unQR__inherit__graph}
[99]15\end{center}
16\end{figure}
[140]17Collaboration diagram for EKFful\_\-unQR:\nopagebreak
[99]18\begin{figure}[H]
19\begin{center}
20\leavevmode
[140]21\includegraphics[height=400pt]{classEKFful__unQR__coll__graph}
[99]22\end{center}
23\end{figure}
24\subsection*{Public Member Functions}
25\begin{CompactItemize}
26\item 
[172]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}
[99]30
31\begin{CompactList}\small\item\em Default constructor. \item\end{CompactList}\item 
[172]32\hypertarget{classEKFful__unQR_b586e534c8a8d219561b0c020329d412}{
33void \hyperlink{classEKFful__unQR_b586e534c8a8d219561b0c020329d412}{condition} (const vec \&QR0)}
34\label{classEKFful__unQR_b586e534c8a8d219561b0c020329d412}
[140]35
36\begin{CompactList}\small\item\em Substitute {\tt val} for {\tt rvc}. \item\end{CompactList}\item 
[172]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}
[99]40
41\begin{CompactList}\small\item\em Set nonlinear functions for mean values and covariance matrices. \item\end{CompactList}\item 
[172]42\hypertarget{classEKFfull_8ca46f177e395fa714bbd8bd29ea43e0}{
43void \hyperlink{classEKFfull_8ca46f177e395fa714bbd8bd29ea43e0}{bayes} (const vec \&dt)}
44\label{classEKFfull_8ca46f177e395fa714bbd8bd29ea43e0}
[99]45
[172]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}
[140]50
[99]51\begin{CompactList}\small\item\em set estimates \item\end{CompactList}\item 
[172]52\hypertarget{classEKFfull_170a748ad944bdebb0b3073463876abe}{
53const \hyperlink{classepdf}{epdf} \& \hyperlink{classEKFfull_170a748ad944bdebb0b3073463876abe}{\_\-epdf} () const }
54\label{classEKFfull_170a748ad944bdebb0b3073463876abe}
[99]55
56\begin{CompactList}\small\item\em dummy! \item\end{CompactList}\item 
[210]57\hypertarget{classEKFfull_820987401e922a03c7d36013e42d8c48}{
58const \hyperlink{classenorm}{enorm}$<$ \hyperlink{classfsqmat}{fsqmat} $>$ $\ast$ \hyperlink{classEKFfull_820987401e922a03c7d36013e42d8c48}{\_\-e} () const }
59\label{classEKFfull_820987401e922a03c7d36013e42d8c48}
60
61\begin{CompactList}\small\item\em Returns a pointer to the \hyperlink{classepdf}{epdf} representing posterior density on parameters. Use with care! \item\end{CompactList}\item 
[172]62\hypertarget{classBM_0186270f75189677f390fe088a9947e9}{
63virtual void \hyperlink{classBM_0186270f75189677f390fe088a9947e9}{bayesB} (const mat \&Dt)}
64\label{classBM_0186270f75189677f390fe088a9947e9}
[99]65
[172]66\begin{CompactList}\small\item\em Batch Bayes rule (columns of Dt are observations). \item\end{CompactList}\item 
67virtual double \hyperlink{classBM_8a8ce6df431689964c41cc6c849cfd06}{logpred} (const vec \&dt) const
68\item 
[180]69\hypertarget{classBM_cd0660f2a1a344b56ac39802708ff165}{
70vec \hyperlink{classBM_cd0660f2a1a344b56ac39802708ff165}{logpred\_\-m} (const mat \&dt) const }
71\label{classBM_cd0660f2a1a344b56ac39802708ff165}
72
73\begin{CompactList}\small\item\em Matrix version of logpred. \item\end{CompactList}\item 
[210]74\hypertarget{classBM_5594d68ee9aa6fc8c1e79019da5c9d56}{
75virtual \hyperlink{classepdf}{epdf} $\ast$ \hyperlink{classBM_5594d68ee9aa6fc8c1e79019da5c9d56}{predictor} (const \hyperlink{classRV}{RV} \&\hyperlink{classBM_af00f0612fabe66241dd507188cdbf88}{rv}) const }
76\label{classBM_5594d68ee9aa6fc8c1e79019da5c9d56}
[180]77
78\begin{CompactList}\small\item\em Constructs a predictive density (marginal density on data). \item\end{CompactList}\item 
[172]79\hypertarget{classBM_126bd2595c48e311fc2a7ab72876092a}{
80const \hyperlink{classRV}{RV} \& \hyperlink{classBM_126bd2595c48e311fc2a7ab72876092a}{\_\-rv} () const }
81\label{classBM_126bd2595c48e311fc2a7ab72876092a}
82
[99]83\begin{CompactList}\small\item\em access function \item\end{CompactList}\item 
[172]84\hypertarget{classBM_87f4a547d2c29180be88175e5eab9c88}{
85double \hyperlink{classBM_87f4a547d2c29180be88175e5eab9c88}{\_\-ll} () const }
86\label{classBM_87f4a547d2c29180be88175e5eab9c88}
[99]87
[140]88\begin{CompactList}\small\item\em access function \item\end{CompactList}\item 
[172]89\hypertarget{classBM_1ffa9f23669aabecc3760c06c6987522}{
90void \hyperlink{classBM_1ffa9f23669aabecc3760c06c6987522}{set\_\-evalll} (bool evl0)}
91\label{classBM_1ffa9f23669aabecc3760c06c6987522}
[140]92
[172]93\begin{CompactList}\small\item\em access function \item\end{CompactList}\item 
94virtual \hyperlink{classBM}{BM} $\ast$ \hyperlink{classBM_eb58c81d6a7b75b05fc6f276eed78887}{\_\-copy\_\-} (bool changerv=false)
95\item 
96\hypertarget{classBMcond_3fa60348b2da6b4208bb95b8d146900a}{
97const \hyperlink{classRV}{RV} \& \hyperlink{classBMcond_3fa60348b2da6b4208bb95b8d146900a}{\_\-rvc} () const }
98\label{classBMcond_3fa60348b2da6b4208bb95b8d146900a}
99
[99]100\begin{CompactList}\small\item\em access function \item\end{CompactList}\end{CompactItemize}
101\subsection*{Public Attributes}
102\begin{CompactItemize}
103\item 
[172]104\hypertarget{classKalmanFull_fb5aec635e2720cc5ac31bc01c18a68a}{
105vec \hyperlink{classKalmanFull_fb5aec635e2720cc5ac31bc01c18a68a}{mu}}
106\label{classKalmanFull_fb5aec635e2720cc5ac31bc01c18a68a}
[99]107
108\begin{CompactList}\small\item\em Mean value of the posterior density. \item\end{CompactList}\item 
[172]109\hypertarget{classKalmanFull_b75dc059e84fa8ffc076203b30f926cc}{
110mat \hyperlink{classKalmanFull_b75dc059e84fa8ffc076203b30f926cc}{P}}
111\label{classKalmanFull_b75dc059e84fa8ffc076203b30f926cc}
[99]112
113\begin{CompactList}\small\item\em Variance of the posterior density. \item\end{CompactList}\item 
[172]114\hypertarget{classKalmanFull_c17d69e125acd2673e6688fd86dd3f84}{
115bool \textbf{evalll}}
116\label{classKalmanFull_c17d69e125acd2673e6688fd86dd3f84}
[99]117
118\item 
[172]119\hypertarget{classKalmanFull_3aa4bf6128980d0627413dcf9cd07308}{
120double \textbf{ll}}
121\label{classKalmanFull_3aa4bf6128980d0627413dcf9cd07308}
[99]122
123\end{CompactItemize}
124\subsection*{Protected Attributes}
125\begin{CompactItemize}
126\item 
[172]127\hypertarget{classKalmanFull_c5353e66238ed717dba79e0499118226}{
128int \textbf{dimx}}
129\label{classKalmanFull_c5353e66238ed717dba79e0499118226}
[99]130
131\item 
[172]132\hypertarget{classKalmanFull_761fadcc12dd4cb83bb8b5e27db01947}{
133int \textbf{dimy}}
134\label{classKalmanFull_761fadcc12dd4cb83bb8b5e27db01947}
[99]135
136\item 
[172]137\hypertarget{classKalmanFull_609a4a0fcde78fd7aac2f01b34e952c9}{
138int \textbf{dimu}}
139\label{classKalmanFull_609a4a0fcde78fd7aac2f01b34e952c9}
[99]140
141\item 
[172]142\hypertarget{classKalmanFull_554de4c953761380cd5a14a02542e007}{
143mat \textbf{A}}
144\label{classKalmanFull_554de4c953761380cd5a14a02542e007}
[99]145
146\item 
[172]147\hypertarget{classKalmanFull_ac7ade2a603a1b05419e36c5aae21755}{
148mat \textbf{B}}
149\label{classKalmanFull_ac7ade2a603a1b05419e36c5aae21755}
[99]150
151\item 
[172]152\hypertarget{classKalmanFull_5a9a8326ae17b519109fcdad59ea74a3}{
153mat \textbf{C}}
154\label{classKalmanFull_5a9a8326ae17b519109fcdad59ea74a3}
[99]155
156\item 
[172]157\hypertarget{classKalmanFull_8f992a2d6b66d2e8bd9174b28cc0f074}{
158mat \textbf{D}}
159\label{classKalmanFull_8f992a2d6b66d2e8bd9174b28cc0f074}
[99]160
161\item 
[172]162\hypertarget{classKalmanFull_bbd2dab10da47237a5f0d9e55fd61f24}{
163mat \textbf{R}}
164\label{classKalmanFull_bbd2dab10da47237a5f0d9e55fd61f24}
[99]165
166\item 
[172]167\hypertarget{classKalmanFull_a8777c1fe67763395d3ddeb326239851}{
168mat \textbf{Q}}
169\label{classKalmanFull_a8777c1fe67763395d3ddeb326239851}
[99]170
171\item 
[172]172\hypertarget{classKalmanFull_905823cf4157a11b8b824e45809dac55}{
173mat \textbf{\_\-Pp}}
174\label{classKalmanFull_905823cf4157a11b8b824e45809dac55}
[99]175
176\item 
[172]177\hypertarget{classKalmanFull_b1b946b3a43f7d86cf4b6dc0dd6e3210}{
178mat \textbf{\_\-Ry}}
179\label{classKalmanFull_b1b946b3a43f7d86cf4b6dc0dd6e3210}
[99]180
181\item 
[172]182\hypertarget{classKalmanFull_c7d915386a9d60b1bc309ae9166764f6}{
183mat \textbf{\_\-iRy}}
184\label{classKalmanFull_c7d915386a9d60b1bc309ae9166764f6}
[99]185
186\item 
[172]187\hypertarget{classKalmanFull_4c8354ea4801529f3071189ddd10d760}{
188mat \textbf{\_\-K}}
189\label{classKalmanFull_4c8354ea4801529f3071189ddd10d760}
[99]190
191\item 
[172]192\hypertarget{classBM_bf6fb59b30141074f8ee1e2f43d03129}{
193bool \hyperlink{classBM_bf6fb59b30141074f8ee1e2f43d03129}{evalll}}
194\label{classBM_bf6fb59b30141074f8ee1e2f43d03129}
[99]195
[172]196\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 
197\hypertarget{classBM_5623fef6572a08c2b53b8c87b82dc979}{
198double \hyperlink{classBM_5623fef6572a08c2b53b8c87b82dc979}{ll}}
199\label{classBM_5623fef6572a08c2b53b8c87b82dc979}
[99]200
201\begin{CompactList}\small\item\em Logarithm of marginalized data likelihood. \item\end{CompactList}\item 
[172]202\hypertarget{classBM_af00f0612fabe66241dd507188cdbf88}{
203\hyperlink{classRV}{RV} \hyperlink{classBM_af00f0612fabe66241dd507188cdbf88}{rv}}
204\label{classBM_af00f0612fabe66241dd507188cdbf88}
[99]205
[140]206\begin{CompactList}\small\item\em Random variable of the posterior. \item\end{CompactList}\item 
[172]207\hypertarget{classBMcond_9ba793c8ec453f04d372d17195ed8dec}{
208\hyperlink{classRV}{RV} \hyperlink{classBMcond_9ba793c8ec453f04d372d17195ed8dec}{rvc}}
209\label{classBMcond_9ba793c8ec453f04d372d17195ed8dec}
[140]210
211\begin{CompactList}\small\item\em Identificator of the conditioning variable. \item\end{CompactList}\end{CompactItemize}
[99]212\subsection*{Friends}
213\begin{CompactItemize}
214\item 
[172]215\hypertarget{classKalmanFull_86ba216243ed95bb46d80d88775d16af}{
216std::ostream \& \hyperlink{classKalmanFull_86ba216243ed95bb46d80d88775d16af}{operator$<$$<$} (std::ostream \&os, const \hyperlink{classKalmanFull}{KalmanFull} \&kf)}
217\label{classKalmanFull_86ba216243ed95bb46d80d88775d16af}
[99]218
219\begin{CompactList}\small\item\em print elements of KF \item\end{CompactList}\end{CompactItemize}
220
221
222\subsection{Detailed Description}
[172]223Extended \hyperlink{classKalman}{Kalman} filter with unknown {\tt Q} and {\tt R}.
[99]224
[172]225\subsection{Member Function Documentation}
226\hypertarget{classBM_8a8ce6df431689964c41cc6c849cfd06}{
227\index{EKFful\_\-unQR@{EKFful\_\-unQR}!logpred@{logpred}}
228\index{logpred@{logpred}!EKFful_unQR@{EKFful\_\-unQR}}
229\subsubsection[logpred]{\setlength{\rightskip}{0pt plus 5cm}virtual double BM::logpred (const vec \& {\em dt}) const\hspace{0.3cm}{\tt  \mbox{[}inline, virtual, inherited\mbox{]}}}}
230\label{classBM_8a8ce6df431689964c41cc6c849cfd06}
231
232
233Evaluates predictive log-likelihood of the given data record I.e. marginal likelihood of the data with the posterior integrated out.
234
[180]235Reimplemented in \hyperlink{classARX_e7f9e7823aec9bf7ddc3b42d9b3304c4}{ARX}, \hyperlink{classMixEF_424ca64f36d4e41de7a7e7ae921d35ea}{MixEF}, and \hyperlink{classmultiBM_13e26a61757278981fd8cac9a7ef91eb}{multiBM}.
236
237Referenced by BM::logpred\_\-m().\hypertarget{classBM_eb58c81d6a7b75b05fc6f276eed78887}{
[172]238\index{EKFful\_\-unQR@{EKFful\_\-unQR}!\_\-copy\_\-@{\_\-copy\_\-}}
239\index{\_\-copy\_\-@{\_\-copy\_\-}!EKFful_unQR@{EKFful\_\-unQR}}
240\subsubsection[\_\-copy\_\-]{\setlength{\rightskip}{0pt plus 5cm}virtual {\bf BM}$\ast$ BM::\_\-copy\_\- (bool {\em changerv} = {\tt false})\hspace{0.3cm}{\tt  \mbox{[}inline, virtual, inherited\mbox{]}}}}
241\label{classBM_eb58c81d6a7b75b05fc6f276eed78887}
242
243
244Copy 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; \} 
245
[210]246Reimplemented in \hyperlink{classARX_5de61fbd4f97fa3216760b1f733f5af0}{ARX}, and \hyperlink{classBMEF_97f5312efe4a5bedb86d2daec59d8651}{BMEF}.
[172]247
[140]248The documentation for this class was generated from the following file:\begin{CompactItemize}
[99]249\item 
[172]250work/git/mixpp/bdm/estim/\hyperlink{ekf__templ_8h}{ekf\_\-templ.h}\end{CompactItemize}
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