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1\hypertarget{classEKF__unQ}{
2\section{EKF\_\-unQ Class Reference}
3\label{classEKF__unQ}\index{EKF\_\-unQ@{EKF\_\-unQ}}
4}
5Inheritance diagram for EKF\_\-unQ::\begin{figure}[H]
6\begin{center}
7\leavevmode
8\includegraphics[height=3.80952cm]{classEKF__unQ}
9\end{center}
10\end{figure}
11
12
13\subsection{Detailed Description}
14Extended Kalman filter with unknown {\tt Q}. \subsection*{Public Member Functions}
15\begin{CompactItemize}
16\item 
17\hypertarget{classEKF__unQ_cd06a8c662da244cf61bb5bd39688c99}{
18void \hyperlink{classEKF__unQ_cd06a8c662da244cf61bb5bd39688c99}{condition} (const vec \&Q0)}
19\label{classEKF__unQ_cd06a8c662da244cf61bb5bd39688c99}
20
21\begin{CompactList}\small\item\em Default constructor. \item\end{CompactList}\item 
22\hypertarget{classEKF__unQ_cd06a8c662da244cf61bb5bd39688c99}{
23void \hyperlink{classEKF__unQ_cd06a8c662da244cf61bb5bd39688c99}{condition} (const vec \&Q0)}
24\label{classEKF__unQ_cd06a8c662da244cf61bb5bd39688c99}
25
26\begin{CompactList}\small\item\em Default constructor. \item\end{CompactList}\item 
27\hypertarget{classEKF__unQ_44b49058c8eb27c7910ae31a1dfd3d21}{
28void \textbf{bayes} (const vec dt)}
29\label{classEKF__unQ_44b49058c8eb27c7910ae31a1dfd3d21}
30
31\item 
32\hypertarget{classEKF__unQ_cd06a8c662da244cf61bb5bd39688c99}{
33void \hyperlink{classEKF__unQ_cd06a8c662da244cf61bb5bd39688c99}{condition} (const vec \&Q0)}
34\label{classEKF__unQ_cd06a8c662da244cf61bb5bd39688c99}
35
36\begin{CompactList}\small\item\em Default constructor. \item\end{CompactList}\item 
37\hypertarget{classbdm_1_1EKFCh_50f9fbffad721f35e5ccb75d0f6b842a}{
38void \hyperlink{classbdm_1_1EKFCh_50f9fbffad721f35e5ccb75d0f6b842a}{set\_\-parameters} (diffbifn $\ast$\hyperlink{classbdm_1_1EKFCh_e1e895f994398a55bc425551fc275ba3}{pfxu}, diffbifn $\ast$\hyperlink{classbdm_1_1EKFCh_6b34c69641826322467b704e8252f317}{phxu}, const \hyperlink{classchmat}{chmat} Q0, const \hyperlink{classchmat}{chmat} R0)}
39\label{classbdm_1_1EKFCh_50f9fbffad721f35e5ccb75d0f6b842a}
40
41\begin{CompactList}\small\item\em Set nonlinear functions for mean values and covariance matrices. \item\end{CompactList}\item 
42\hypertarget{classbdm_1_1KalmanCh_20a4d4c664e8ac8a3f1bb7b0d11c6d87}{
43void \hyperlink{classbdm_1_1KalmanCh_20a4d4c664e8ac8a3f1bb7b0d11c6d87}{set\_\-parameters} (const mat \&A0, const mat \&B0, const mat \&C0, const mat \&D0, const \hyperlink{classchmat}{chmat} \&Q0, const \hyperlink{classchmat}{chmat} \&R0)}
44\label{classbdm_1_1KalmanCh_20a4d4c664e8ac8a3f1bb7b0d11c6d87}
45
46\begin{CompactList}\small\item\em Set parameters with check of relevance. \item\end{CompactList}\item 
47\hypertarget{classbdm_1_1EKFCh_4c8609c37290b158f88a31dae4047225}{
48void \hyperlink{classbdm_1_1EKFCh_4c8609c37290b158f88a31dae4047225}{bayes} (const vec \&dt)}
49\label{classbdm_1_1EKFCh_4c8609c37290b158f88a31dae4047225}
50
51\begin{CompactList}\small\item\em Here dt = \mbox{[}yt;ut\mbox{]} of appropriate dimensions. \item\end{CompactList}\item 
52\hypertarget{classbdm_1_1KalmanCh_6e169272657ed101f3d128b49c59b890}{
53void \textbf{set\_\-statistics} (const vec \&mu0, const \hyperlink{classchmat}{chmat} \&P0)}
54\label{classbdm_1_1KalmanCh_6e169272657ed101f3d128b49c59b890}
55
56\item 
57\hypertarget{classbdm_1_1Kalman_9264fc6b173ecb803d2684b883f32c68}{
58void \hyperlink{classbdm_1_1Kalman_9264fc6b173ecb803d2684b883f32c68}{set\_\-est} (const vec \&mu0, const \hyperlink{classchmat}{chmat} \&P0)}
59\label{classbdm_1_1Kalman_9264fc6b173ecb803d2684b883f32c68}
60
61\begin{CompactList}\small\item\em Set estimate values, used e.g. in initialization. \item\end{CompactList}\item 
62\hypertarget{classbdm_1_1Kalman_f75e487ff6c129d7012d702030f8c890}{
63const epdf \& \hyperlink{classbdm_1_1Kalman_f75e487ff6c129d7012d702030f8c890}{posterior} () const }
64\label{classbdm_1_1Kalman_f75e487ff6c129d7012d702030f8c890}
65
66\begin{CompactList}\small\item\em access function \item\end{CompactList}\item 
67\hypertarget{classbdm_1_1Kalman_c34989b1e53c7d4ecdaea63a95ddbd77}{
68const enorm$<$ \hyperlink{classchmat}{chmat} $>$ $\ast$ \textbf{\_\-e} () const }
69\label{classbdm_1_1Kalman_c34989b1e53c7d4ecdaea63a95ddbd77}
70
71\item 
72\hypertarget{classbdm_1_1Kalman_c788ec6e6c6f5f5861ae8a56d8ede277}{
73mat \& \hyperlink{classbdm_1_1Kalman_c788ec6e6c6f5f5861ae8a56d8ede277}{\_\-\_\-K} ()}
74\label{classbdm_1_1Kalman_c788ec6e6c6f5f5861ae8a56d8ede277}
75
76\begin{CompactList}\small\item\em access function \item\end{CompactList}\item 
77\hypertarget{classbdm_1_1Kalman_a250d1dbe7bba861dba2a324520cfa48}{
78vec \hyperlink{classbdm_1_1Kalman_a250d1dbe7bba861dba2a324520cfa48}{\_\-dP} ()}
79\label{classbdm_1_1Kalman_a250d1dbe7bba861dba2a324520cfa48}
80
81\begin{CompactList}\small\item\em access function \item\end{CompactList}\item 
82\hypertarget{classbdm_1_1BMcond_7506910f93250b44fea505ec4ffb19dc}{
83const RV \& \hyperlink{classbdm_1_1BMcond_7506910f93250b44fea505ec4ffb19dc}{\_\-rvc} () const }
84\label{classbdm_1_1BMcond_7506910f93250b44fea505ec4ffb19dc}
85
86\begin{CompactList}\small\item\em access function \item\end{CompactList}\end{CompactItemize}
87\begin{Indent}{\bf Constructors}\par
88\begin{CompactItemize}
89\item 
90virtual BM $\ast$ \hyperlink{classbdm_1_1BM_c0f027ff91d8459937c6f60ff8e553ff}{\_\-copy\_\-} ()
91\end{CompactItemize}
92\end{Indent}
93\begin{Indent}{\bf Mathematical operations}\par
94\begin{CompactItemize}
95\item 
96\hypertarget{classbdm_1_1BM_1dee3fddaf021e62d925289660a707dc}{
97virtual void \hyperlink{classbdm_1_1BM_1dee3fddaf021e62d925289660a707dc}{bayesB} (const mat \&Dt)}
98\label{classbdm_1_1BM_1dee3fddaf021e62d925289660a707dc}
99
100\begin{CompactList}\small\item\em Batch Bayes rule (columns of Dt are observations). \item\end{CompactList}\item 
101virtual double \hyperlink{classbdm_1_1BM_50257e0c1e5b5c73153ea6e716ad8ae0}{logpred} (const vec \&dt) const
102\item 
103\hypertarget{classbdm_1_1BM_0e8ebe61fb14990abe1254bd3dda5fae}{
104vec \hyperlink{classbdm_1_1BM_0e8ebe61fb14990abe1254bd3dda5fae}{logpred\_\-m} (const mat \&dt) const }
105\label{classbdm_1_1BM_0e8ebe61fb14990abe1254bd3dda5fae}
106
107\begin{CompactList}\small\item\em Matrix version of logpred. \item\end{CompactList}\item 
108\hypertarget{classbdm_1_1BM_688d7a2aced1e06aa1c468d73a9e5eba}{
109virtual epdf $\ast$ \hyperlink{classbdm_1_1BM_688d7a2aced1e06aa1c468d73a9e5eba}{epredictor} () const }
110\label{classbdm_1_1BM_688d7a2aced1e06aa1c468d73a9e5eba}
111
112\begin{CompactList}\small\item\em Constructs a predictive density $ f(d_{t+1} |d_{t}, \ldots d_{0}) $. \item\end{CompactList}\item 
113\hypertarget{classbdm_1_1BM_598b25e3f3d96a5bc00a5faeb5b3c912}{
114virtual mpdf $\ast$ \hyperlink{classbdm_1_1BM_598b25e3f3d96a5bc00a5faeb5b3c912}{predictor} () const }
115\label{classbdm_1_1BM_598b25e3f3d96a5bc00a5faeb5b3c912}
116
117\begin{CompactList}\small\item\em Constructs a conditional density 1-step ahead predictor. \item\end{CompactList}\end{CompactItemize}
118\end{Indent}
119\begin{Indent}{\bf Access to attributes}\par
120\begin{CompactItemize}
121\item 
122\hypertarget{classbdm_1_1BM_ff2d8755ba0b3def927d31305c03b09c}{
123const RV \& \textbf{\_\-drv} () const }
124\label{classbdm_1_1BM_ff2d8755ba0b3def927d31305c03b09c}
125
126\item 
127\hypertarget{classbdm_1_1BM_f135ae6dce7e9f30c9f88229c7930b96}{
128void \textbf{set\_\-drv} (const RV \&rv)}
129\label{classbdm_1_1BM_f135ae6dce7e9f30c9f88229c7930b96}
130
131\item 
132\hypertarget{classbdm_1_1BM_b38d92f17620813ad872d86e01a26e5e}{
133void \textbf{set\_\-rv} (const RV \&rv)}
134\label{classbdm_1_1BM_b38d92f17620813ad872d86e01a26e5e}
135
136\item 
137\hypertarget{classbdm_1_1BM_5be65d37dedfe33a3671e7065f523a70}{
138double \textbf{\_\-ll} () const }
139\label{classbdm_1_1BM_5be65d37dedfe33a3671e7065f523a70}
140
141\item 
142\hypertarget{classbdm_1_1BM_236b3abbcc93594fc97cd86d82c1a83f}{
143void \textbf{set\_\-evalll} (bool evl0)}
144\label{classbdm_1_1BM_236b3abbcc93594fc97cd86d82c1a83f}
145
146\end{CompactItemize}
147\end{Indent}
148\subsection*{Protected Attributes}
149\begin{CompactItemize}
150\item 
151\hypertarget{classbdm_1_1EKFCh_e1e895f994398a55bc425551fc275ba3}{
152diffbifn $\ast$ \hyperlink{classbdm_1_1EKFCh_e1e895f994398a55bc425551fc275ba3}{pfxu}}
153\label{classbdm_1_1EKFCh_e1e895f994398a55bc425551fc275ba3}
154
155\begin{CompactList}\small\item\em Internal Model f(x,u). \item\end{CompactList}\item 
156\hypertarget{classbdm_1_1EKFCh_6b34c69641826322467b704e8252f317}{
157diffbifn $\ast$ \hyperlink{classbdm_1_1EKFCh_6b34c69641826322467b704e8252f317}{phxu}}
158\label{classbdm_1_1EKFCh_6b34c69641826322467b704e8252f317}
159
160\begin{CompactList}\small\item\em Observation Model h(x,u). \item\end{CompactList}\item 
161\hypertarget{classbdm_1_1KalmanCh_48611c8582706cfa62e832be0972e75d}{
162mat \hyperlink{classbdm_1_1KalmanCh_48611c8582706cfa62e832be0972e75d}{preA}}
163\label{classbdm_1_1KalmanCh_48611c8582706cfa62e832be0972e75d}
164
165\begin{CompactList}\small\item\em pre array (triangular matrix) \item\end{CompactList}\item 
166\hypertarget{classbdm_1_1KalmanCh_bcbd68f51d4b57246e7784ca5900171f}{
167mat \hyperlink{classbdm_1_1KalmanCh_bcbd68f51d4b57246e7784ca5900171f}{postA}}
168\label{classbdm_1_1KalmanCh_bcbd68f51d4b57246e7784ca5900171f}
169
170\begin{CompactList}\small\item\em post array (triangular matrix) \item\end{CompactList}\item 
171\hypertarget{classbdm_1_1Kalman_3fe475a1e920b20b63bb342c0e1571f7}{
172RV \hyperlink{classbdm_1_1Kalman_3fe475a1e920b20b63bb342c0e1571f7}{rvy}}
173\label{classbdm_1_1Kalman_3fe475a1e920b20b63bb342c0e1571f7}
174
175\begin{CompactList}\small\item\em Indetifier of output rv. \item\end{CompactList}\item 
176\hypertarget{classbdm_1_1Kalman_149e27424fd1a7cc1c998ea088618a94}{
177RV \hyperlink{classbdm_1_1Kalman_149e27424fd1a7cc1c998ea088618a94}{rvu}}
178\label{classbdm_1_1Kalman_149e27424fd1a7cc1c998ea088618a94}
179
180\begin{CompactList}\small\item\em Indetifier of exogeneous rv. \item\end{CompactList}\item 
181\hypertarget{classbdm_1_1Kalman_ba7699cdb3b1382a54d3e28b9b7517fa}{
182int \hyperlink{classbdm_1_1Kalman_ba7699cdb3b1382a54d3e28b9b7517fa}{dimx}}
183\label{classbdm_1_1Kalman_ba7699cdb3b1382a54d3e28b9b7517fa}
184
185\begin{CompactList}\small\item\em cache of rv.count() \item\end{CompactList}\item 
186\hypertarget{classbdm_1_1Kalman_d2c36ba01760bf207b985bf321b7817f}{
187int \hyperlink{classbdm_1_1Kalman_d2c36ba01760bf207b985bf321b7817f}{dimy}}
188\label{classbdm_1_1Kalman_d2c36ba01760bf207b985bf321b7817f}
189
190\begin{CompactList}\small\item\em cache of rvy.count() \item\end{CompactList}\item 
191\hypertarget{classbdm_1_1Kalman_c5136ef617f6ac0e426bea222755d92b}{
192int \hyperlink{classbdm_1_1Kalman_c5136ef617f6ac0e426bea222755d92b}{dimu}}
193\label{classbdm_1_1Kalman_c5136ef617f6ac0e426bea222755d92b}
194
195\begin{CompactList}\small\item\em cache of rvu.count() \item\end{CompactList}\item 
196\hypertarget{classbdm_1_1Kalman_0a2072e2090c10fac74ad30a023a4ace}{
197mat \hyperlink{classbdm_1_1Kalman_0a2072e2090c10fac74ad30a023a4ace}{A}}
198\label{classbdm_1_1Kalman_0a2072e2090c10fac74ad30a023a4ace}
199
200\begin{CompactList}\small\item\em Matrix A. \item\end{CompactList}\item 
201\hypertarget{classbdm_1_1Kalman_5977b2c81857948a35105f0e7840203c}{
202mat \hyperlink{classbdm_1_1Kalman_5977b2c81857948a35105f0e7840203c}{B}}
203\label{classbdm_1_1Kalman_5977b2c81857948a35105f0e7840203c}
204
205\begin{CompactList}\small\item\em Matrix B. \item\end{CompactList}\item 
206\hypertarget{classbdm_1_1Kalman_818eba63a23972786a4579ad30294177}{
207mat \hyperlink{classbdm_1_1Kalman_818eba63a23972786a4579ad30294177}{C}}
208\label{classbdm_1_1Kalman_818eba63a23972786a4579ad30294177}
209
210\begin{CompactList}\small\item\em Matrix C. \item\end{CompactList}\item 
211\hypertarget{classbdm_1_1Kalman_7b56ac423d0654b5755e4f852a870456}{
212mat \hyperlink{classbdm_1_1Kalman_7b56ac423d0654b5755e4f852a870456}{D}}
213\label{classbdm_1_1Kalman_7b56ac423d0654b5755e4f852a870456}
214
215\begin{CompactList}\small\item\em Matrix D. \item\end{CompactList}\item 
216\hypertarget{classbdm_1_1Kalman_70f8bf19e81b532c60fd3a7a152425ee}{
217\hyperlink{classchmat}{chmat} \hyperlink{classbdm_1_1Kalman_70f8bf19e81b532c60fd3a7a152425ee}{Q}}
218\label{classbdm_1_1Kalman_70f8bf19e81b532c60fd3a7a152425ee}
219
220\begin{CompactList}\small\item\em Matrix Q in square-root form. \item\end{CompactList}\item 
221\hypertarget{classbdm_1_1Kalman_475b088287cdfbba4dc60a3d027728b7}{
222\hyperlink{classchmat}{chmat} \hyperlink{classbdm_1_1Kalman_475b088287cdfbba4dc60a3d027728b7}{R}}
223\label{classbdm_1_1Kalman_475b088287cdfbba4dc60a3d027728b7}
224
225\begin{CompactList}\small\item\em Matrix R in square-root form. \item\end{CompactList}\item 
226\hypertarget{classbdm_1_1Kalman_383f329ff18bbe219254c8b3b916f40d}{
227enorm$<$ \hyperlink{classchmat}{chmat} $>$ \hyperlink{classbdm_1_1Kalman_383f329ff18bbe219254c8b3b916f40d}{est}}
228\label{classbdm_1_1Kalman_383f329ff18bbe219254c8b3b916f40d}
229
230\begin{CompactList}\small\item\em posterior density on \$x\_\-t\$ \item\end{CompactList}\item 
231\hypertarget{classbdm_1_1Kalman_ba555c394c429f6831c9bbabfa2c944c}{
232enorm$<$ \hyperlink{classchmat}{chmat} $>$ \hyperlink{classbdm_1_1Kalman_ba555c394c429f6831c9bbabfa2c944c}{fy}}
233\label{classbdm_1_1Kalman_ba555c394c429f6831c9bbabfa2c944c}
234
235\begin{CompactList}\small\item\em preditive density on \$y\_\-t\$ \item\end{CompactList}\item 
236\hypertarget{classbdm_1_1Kalman_bd69dfb802465f22dd84d73a180d5c92}{
237mat \hyperlink{classbdm_1_1Kalman_bd69dfb802465f22dd84d73a180d5c92}{\_\-K}}
238\label{classbdm_1_1Kalman_bd69dfb802465f22dd84d73a180d5c92}
239
240\begin{CompactList}\small\item\em placeholder for Kalman gain \item\end{CompactList}\item 
241\hypertarget{classbdm_1_1Kalman_c249d45258c8578b13858ad3e7b729b1}{
242vec \& \hyperlink{classbdm_1_1Kalman_c249d45258c8578b13858ad3e7b729b1}{\_\-yp}}
243\label{classbdm_1_1Kalman_c249d45258c8578b13858ad3e7b729b1}
244
245\begin{CompactList}\small\item\em cache of fy.mu \item\end{CompactList}\item 
246\hypertarget{classbdm_1_1Kalman_2dd268f2d7fbe6382cb8825a1114192a}{
247\hyperlink{classchmat}{chmat} \& \hyperlink{classbdm_1_1Kalman_2dd268f2d7fbe6382cb8825a1114192a}{\_\-Ry}}
248\label{classbdm_1_1Kalman_2dd268f2d7fbe6382cb8825a1114192a}
249
250\begin{CompactList}\small\item\em cache of fy.R \item\end{CompactList}\item 
251\hypertarget{classbdm_1_1Kalman_fa172078091e45561343fa513dd573b0}{
252vec \& \hyperlink{classbdm_1_1Kalman_fa172078091e45561343fa513dd573b0}{\_\-mu}}
253\label{classbdm_1_1Kalman_fa172078091e45561343fa513dd573b0}
254
255\begin{CompactList}\small\item\em cache of est.mu \item\end{CompactList}\item 
256\hypertarget{classbdm_1_1Kalman_00c27b0bf324f0018497921ca23c71ed}{
257\hyperlink{classchmat}{chmat} \& \hyperlink{classbdm_1_1Kalman_00c27b0bf324f0018497921ca23c71ed}{\_\-P}}
258\label{classbdm_1_1Kalman_00c27b0bf324f0018497921ca23c71ed}
259
260\begin{CompactList}\small\item\em cache of est.R \item\end{CompactList}\item 
261\hypertarget{classbdm_1_1BM_c400357e37d27a4834b2b1d9211009ed}{
262RV \hyperlink{classbdm_1_1BM_c400357e37d27a4834b2b1d9211009ed}{drv}}
263\label{classbdm_1_1BM_c400357e37d27a4834b2b1d9211009ed}
264
265\begin{CompactList}\small\item\em Random variable of the data (optional). \item\end{CompactList}\item 
266\hypertarget{classbdm_1_1BM_4064b6559d962633e4372b12f4cd204a}{
267double \hyperlink{classbdm_1_1BM_4064b6559d962633e4372b12f4cd204a}{ll}}
268\label{classbdm_1_1BM_4064b6559d962633e4372b12f4cd204a}
269
270\begin{CompactList}\small\item\em Logarithm of marginalized data likelihood. \item\end{CompactList}\item 
271\hypertarget{classbdm_1_1BM_faff0ad12556fe7dc0e2807d4fd938ee}{
272bool \hyperlink{classbdm_1_1BM_faff0ad12556fe7dc0e2807d4fd938ee}{evalll}}
273\label{classbdm_1_1BM_faff0ad12556fe7dc0e2807d4fd938ee}
274
275\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 
276\hypertarget{classbdm_1_1BMcond_1164a90f782a2a323b1ee17242100b39}{
277int \hyperlink{classbdm_1_1BMcond_1164a90f782a2a323b1ee17242100b39}{dimc}}
278\label{classbdm_1_1BMcond_1164a90f782a2a323b1ee17242100b39}
279
280\begin{CompactList}\small\item\em dimension of the conditioning variable \item\end{CompactList}\item 
281\hypertarget{classbdm_1_1BMcond_9a12750776d977408aada06a70093297}{
282RV \hyperlink{classbdm_1_1BMcond_9a12750776d977408aada06a70093297}{rvc}}
283\label{classbdm_1_1BMcond_9a12750776d977408aada06a70093297}
284
285\begin{CompactList}\small\item\em Identificator of the conditioning variable. \item\end{CompactList}\end{CompactItemize}
286
287
288\subsection{Member Function Documentation}
289\hypertarget{classbdm_1_1BM_c0f027ff91d8459937c6f60ff8e553ff}{
290\index{EKF\_\-unQ@{EKF\_\-unQ}!\_\-copy\_\-@{\_\-copy\_\-}}
291\index{\_\-copy\_\-@{\_\-copy\_\-}!EKF_unQ@{EKF\_\-unQ}}
292\subsubsection[\_\-copy\_\-]{\setlength{\rightskip}{0pt plus 5cm}virtual BM$\ast$ bdm::BM::\_\-copy\_\- ()\hspace{0.3cm}{\tt  \mbox{[}inline, virtual, inherited\mbox{]}}}}
293\label{classbdm_1_1BM_c0f027ff91d8459937c6f60ff8e553ff}
294
295
296Copy function required in vectors, Arrays of \hyperlink{classbdm_1_1BM}{BM} etc. Have to be DELETED manually! Prototype:
297
298\begin{Code}\begin{verbatim} BM* _copy_(){return new BM(*this);} 
299\end{verbatim}
300\end{Code}
301
302 
303
304Reimplemented in \hyperlink{classbdm_1_1ARX_60c40b5c6abc4c7e464b4ccae64a5a61}{bdm::ARX}.\hypertarget{classbdm_1_1BM_50257e0c1e5b5c73153ea6e716ad8ae0}{
305\index{EKF\_\-unQ@{EKF\_\-unQ}!logpred@{logpred}}
306\index{logpred@{logpred}!EKF_unQ@{EKF\_\-unQ}}
307\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{]}}}}
308\label{classbdm_1_1BM_50257e0c1e5b5c73153ea6e716ad8ae0}
309
310
311Evaluates predictive log-likelihood of the given data record I.e. marginal likelihood of the data with the posterior integrated out.
312
313Reimplemented in \hyperlink{classbdm_1_1ARX_080a7e531e3aa06694112863b15bc6a4}{bdm::ARX}, \hyperlink{classbdm_1_1MixEF_da724da464a75e07521941e430929efa}{bdm::MixEF}, and \hyperlink{classbdm_1_1multiBM_e157b607c1e3fa91d42aeea44458e2bf}{bdm::multiBM}.
314
315Referenced by bdm::BM::logpred\_\-m().
316
317The documentation for this class was generated from the following files:\begin{CompactItemize}
318\item 
319pmsm\_\-sim.cpp\item 
320pmsm\_\-sim2.cpp\item 
321\hyperlink{pmsm__unkQpf_8cpp}{pmsm\_\-unkQpf.cpp}\end{CompactItemize}
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