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    r275 r280  
    180180<a name="l00229"></a><a class="code" href="classbdm_1_1EKFCh.html#6b34c69641826322467b704e8252f317">00229</a>         <a class="code" href="classbdm_1_1diffbifn.html" title="Class representing a differentiable function of two variables .">diffbifn</a>* <a class="code" href="classbdm_1_1EKFCh.html#6b34c69641826322467b704e8252f317" title="Observation Model h(x,u).">phxu</a>; 
    181181<a name="l00230"></a>00230 <span class="keyword">public</span>: 
    182 <a name="l00232"></a>00232         <a class="code" href="classbdm_1_1EKFCh.html#8b3228a594532b6a0db0fdc065bc5b9f" title="Default constructor.">EKFCh</a> (); 
    183 <a name="l00234"></a>00234         <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1EKFCh.html#50f9fbffad721f35e5ccb75d0f6b842a" title="Set nonlinear functions for mean values and covariance matrices.">set_parameters</a> ( <a class="code" href="classbdm_1_1diffbifn.html" title="Class representing a differentiable function of two variables .">diffbifn</a>* <a class="code" href="classbdm_1_1EKFCh.html#e1e895f994398a55bc425551fc275ba3" title="Internal Model f(x,u).">pfxu</a>, <a class="code" href="classbdm_1_1diffbifn.html" title="Class representing a differentiable function of two variables .">diffbifn</a>* <a class="code" href="classbdm_1_1EKFCh.html#6b34c69641826322467b704e8252f317" title="Observation Model h(x,u).">phxu</a>, <span class="keyword">const</span> <a class="code" href="classchmat.html" title="Symmetric matrix stored in square root decomposition using upper cholesky.">chmat</a> Q0, <span class="keyword">const</span> <a class="code" href="classchmat.html" title="Symmetric matrix stored in square root decomposition using upper cholesky.">chmat</a> R0 ); 
    184 <a name="l00236"></a>00236         <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1EKFCh.html#4c8609c37290b158f88a31dae4047225" title="Here dt = [yt;ut] of appropriate dimensions.">bayes</a> ( <span class="keyword">const</span> vec &amp;dt ); 
    185 <a name="l00237"></a>00237 }; 
    186 <a name="l00238"></a>00238  
    187 <a name="l00243"></a><a class="code" href="classbdm_1_1KFcondQR.html">00243</a> <span class="keyword">class </span><a class="code" href="classbdm_1_1KFcondQR.html" title="Kalman Filter with conditional diagonal matrices R and Q.">KFcondQR</a> : <span class="keyword">public</span> <a class="code" href="classbdm_1_1Kalman.html" title="Kalman filter with covariance matrices in square root form.">Kalman</a>&lt;ldmat&gt;, <span class="keyword">public</span> <a class="code" href="classbdm_1_1BMcond.html" title="Conditional Bayesian Filter.">BMcond</a> { 
    188 <a name="l00244"></a>00244 <span class="comment">//protected:</span> 
    189 <a name="l00245"></a>00245 <span class="keyword">public</span>: 
    190 <a name="l00247"></a><a class="code" href="classbdm_1_1KFcondQR.html#b586ac962751a6af76b2e0fd7e066194">00247</a>         <a class="code" href="classbdm_1_1KFcondQR.html#b586ac962751a6af76b2e0fd7e066194" title="Default constructor.">KFcondQR</a> ( ) : <a class="code" href="classbdm_1_1Kalman.html" title="Kalman filter with covariance matrices in square root form.">Kalman</a>&lt;<a class="code" href="classldmat.html" title="Matrix stored in LD form, (commonly known as UD).">ldmat</a>&gt; ( ),<a class="code" href="classbdm_1_1BMcond.html" title="Conditional Bayesian Filter.">BMcond</a> ( ) {}; 
    191 <a name="l00248"></a>00248  
    192 <a name="l00249"></a>00249         <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1KFcondQR.html#0288d47032757774a525f196ac3da21d" title="Substitute val for rvc.">condition</a> ( <span class="keyword">const</span> vec &amp;RQ ); 
    193 <a name="l00250"></a>00250 }; 
    194 <a name="l00251"></a>00251  
    195 <a name="l00256"></a><a class="code" href="classbdm_1_1KFcondR.html">00256</a> <span class="keyword">class </span><a class="code" href="classbdm_1_1KFcondR.html" title="Kalman Filter with conditional diagonal matrices R and Q.">KFcondR</a> : <span class="keyword">public</span> <a class="code" href="classbdm_1_1Kalman.html" title="Kalman filter with covariance matrices in square root form.">Kalman</a>&lt;ldmat&gt;, <span class="keyword">public</span> <a class="code" href="classbdm_1_1BMcond.html" title="Conditional Bayesian Filter.">BMcond</a> { 
    196 <a name="l00257"></a>00257 <span class="comment">//protected:</span> 
    197 <a name="l00258"></a>00258 <span class="keyword">public</span>: 
    198 <a name="l00260"></a><a class="code" href="classbdm_1_1KFcondR.html#f11639d79f10b1e7dad16a0d8233450d">00260</a>         <a class="code" href="classbdm_1_1KFcondR.html#f11639d79f10b1e7dad16a0d8233450d" title="Default constructor.">KFcondR</a> ( ) : <a class="code" href="classbdm_1_1Kalman.html" title="Kalman filter with covariance matrices in square root form.">Kalman</a>&lt;<a class="code" href="classldmat.html" title="Matrix stored in LD form, (commonly known as UD).">ldmat</a>&gt; ( ),<a class="code" href="classbdm_1_1BMcond.html" title="Conditional Bayesian Filter.">BMcond</a> ( ) {}; 
    199 <a name="l00261"></a>00261  
    200 <a name="l00262"></a>00262         <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1KFcondR.html#6086f02541f8f3bc8351990abf5cd538" title="Substitute val for rvc.">condition</a> ( <span class="keyword">const</span> vec &amp;<a class="code" href="classbdm_1_1Kalman.html#475b088287cdfbba4dc60a3d027728b7" title="Matrix R in square-root form.">R</a> ); 
    201 <a name="l00263"></a>00263 }; 
     182<a name="l00232"></a>00232         <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1EKFCh.html#50f9fbffad721f35e5ccb75d0f6b842a" title="Set nonlinear functions for mean values and covariance matrices.">set_parameters</a> ( <a class="code" href="classbdm_1_1diffbifn.html" title="Class representing a differentiable function of two variables .">diffbifn</a>* <a class="code" href="classbdm_1_1EKFCh.html#e1e895f994398a55bc425551fc275ba3" title="Internal Model f(x,u).">pfxu</a>, <a class="code" href="classbdm_1_1diffbifn.html" title="Class representing a differentiable function of two variables .">diffbifn</a>* <a class="code" href="classbdm_1_1EKFCh.html#6b34c69641826322467b704e8252f317" title="Observation Model h(x,u).">phxu</a>, <span class="keyword">const</span> <a class="code" href="classchmat.html" title="Symmetric matrix stored in square root decomposition using upper cholesky.">chmat</a> Q0, <span class="keyword">const</span> <a class="code" href="classchmat.html" title="Symmetric matrix stored in square root decomposition using upper cholesky.">chmat</a> R0 ); 
     183<a name="l00234"></a>00234         <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1EKFCh.html#4c8609c37290b158f88a31dae4047225" title="Here dt = [yt;ut] of appropriate dimensions.">bayes</a> ( <span class="keyword">const</span> vec &amp;dt ); 
     184<a name="l00235"></a>00235 }; 
     185<a name="l00236"></a>00236  
     186<a name="l00241"></a><a class="code" href="classbdm_1_1KFcondQR.html">00241</a> <span class="keyword">class </span><a class="code" href="classbdm_1_1KFcondQR.html" title="Kalman Filter with conditional diagonal matrices R and Q.">KFcondQR</a> : <span class="keyword">public</span> <a class="code" href="classbdm_1_1Kalman.html" title="Kalman filter with covariance matrices in square root form.">Kalman</a>&lt;ldmat&gt;, <span class="keyword">public</span> <a class="code" href="classbdm_1_1BMcond.html" title="Conditional Bayesian Filter.">BMcond</a> { 
     187<a name="l00242"></a>00242 <span class="comment">//protected:</span> 
     188<a name="l00243"></a>00243 <span class="keyword">public</span>: 
     189<a name="l00245"></a><a class="code" href="classbdm_1_1KFcondQR.html#b586ac962751a6af76b2e0fd7e066194">00245</a>         <a class="code" href="classbdm_1_1KFcondQR.html#b586ac962751a6af76b2e0fd7e066194" title="Default constructor.">KFcondQR</a> ( ) : <a class="code" href="classbdm_1_1Kalman.html" title="Kalman filter with covariance matrices in square root form.">Kalman</a>&lt;<a class="code" href="classldmat.html" title="Matrix stored in LD form, (commonly known as UD).">ldmat</a>&gt; ( ),<a class="code" href="classbdm_1_1BMcond.html" title="Conditional Bayesian Filter.">BMcond</a> ( ) {}; 
     190<a name="l00246"></a>00246  
     191<a name="l00247"></a>00247         <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1KFcondQR.html#0288d47032757774a525f196ac3da21d" title="Substitute val for rvc.">condition</a> ( <span class="keyword">const</span> vec &amp;RQ ); 
     192<a name="l00248"></a>00248 }; 
     193<a name="l00249"></a>00249  
     194<a name="l00254"></a><a class="code" href="classbdm_1_1KFcondR.html">00254</a> <span class="keyword">class </span><a class="code" href="classbdm_1_1KFcondR.html" title="Kalman Filter with conditional diagonal matrices R and Q.">KFcondR</a> : <span class="keyword">public</span> <a class="code" href="classbdm_1_1Kalman.html" title="Kalman filter with covariance matrices in square root form.">Kalman</a>&lt;ldmat&gt;, <span class="keyword">public</span> <a class="code" href="classbdm_1_1BMcond.html" title="Conditional Bayesian Filter.">BMcond</a> { 
     195<a name="l00255"></a>00255 <span class="comment">//protected:</span> 
     196<a name="l00256"></a>00256 <span class="keyword">public</span>: 
     197<a name="l00258"></a><a class="code" href="classbdm_1_1KFcondR.html#f11639d79f10b1e7dad16a0d8233450d">00258</a>         <a class="code" href="classbdm_1_1KFcondR.html#f11639d79f10b1e7dad16a0d8233450d" title="Default constructor.">KFcondR</a> ( ) : <a class="code" href="classbdm_1_1Kalman.html" title="Kalman filter with covariance matrices in square root form.">Kalman</a>&lt;<a class="code" href="classldmat.html" title="Matrix stored in LD form, (commonly known as UD).">ldmat</a>&gt; ( ),<a class="code" href="classbdm_1_1BMcond.html" title="Conditional Bayesian Filter.">BMcond</a> ( ) {}; 
     198<a name="l00259"></a>00259  
     199<a name="l00260"></a>00260         <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1KFcondR.html#6086f02541f8f3bc8351990abf5cd538" title="Substitute val for rvc.">condition</a> ( <span class="keyword">const</span> vec &amp;<a class="code" href="classbdm_1_1Kalman.html#475b088287cdfbba4dc60a3d027728b7" title="Matrix R in square-root form.">R</a> ); 
     200<a name="l00261"></a>00261 }; 
     201<a name="l00262"></a>00262  
    202202<a name="l00264"></a>00264  
    203 <a name="l00266"></a>00266  
    204 <a name="l00267"></a>00267 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt; 
    205 <a name="l00268"></a><a class="code" href="classbdm_1_1Kalman.html#8b22c45cffa949d70b8e5ac92ed5ce25">00268</a> <a class="code" href="classbdm_1_1Kalman.html" title="Kalman filter with covariance matrices in square root form.">Kalman&lt;sq_T&gt;::Kalman</a> ( <span class="keyword">const</span> <a class="code" href="classbdm_1_1Kalman.html" title="Kalman filter with covariance matrices in square root form.">Kalman&lt;sq_T&gt;</a> &amp;K0 ) : <a class="code" href="classbdm_1_1BM.html" title="Bayesian Model of a system, i.e. all uncertainty is modeled by probabilities.">BM</a> ( ),rvy ( K0.rvy ),rvu ( K0.rvu ), 
    206 <a name="l00269"></a>00269                 dimx ( K0.dimx ), dimy ( K0.dimy ),dimu ( K0.dimu ), 
    207 <a name="l00270"></a>00270                 A ( K0.A ), B ( K0.B ), C ( K0.C ), D ( K0.D ), 
    208 <a name="l00271"></a>00271                 Q(K0.Q), R(K0.R), 
    209 <a name="l00272"></a>00272                 est ( K0.est ), fy ( K0.fy ), _yp(fy._mu()),_Ry(fy._R()), _mu(est._mu()), _P(est._R()) { 
    210 <a name="l00273"></a>00273  
    211 <a name="l00274"></a>00274 <span class="comment">// copy values in pointers</span> 
    212 <a name="l00275"></a>00275 <span class="comment">//      _mu = K0._mu;</span> 
    213 <a name="l00276"></a>00276 <span class="comment">//      _P = K0._P;</span> 
    214 <a name="l00277"></a>00277 <span class="comment">//      _yp = K0._yp;</span> 
    215 <a name="l00278"></a>00278 <span class="comment">//      _Ry = K0._Ry;</span> 
     203<a name="l00265"></a>00265 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt; 
     204<a name="l00266"></a><a class="code" href="classbdm_1_1Kalman.html#8b22c45cffa949d70b8e5ac92ed5ce25">00266</a> <a class="code" href="classbdm_1_1Kalman.html" title="Kalman filter with covariance matrices in square root form.">Kalman&lt;sq_T&gt;::Kalman</a> ( <span class="keyword">const</span> <a class="code" href="classbdm_1_1Kalman.html" title="Kalman filter with covariance matrices in square root form.">Kalman&lt;sq_T&gt;</a> &amp;K0 ) : <a class="code" href="classbdm_1_1BM.html" title="Bayesian Model of a system, i.e. all uncertainty is modeled by probabilities.">BM</a> ( ),rvy ( K0.rvy ),rvu ( K0.rvu ), 
     205<a name="l00267"></a>00267                 dimx ( K0.dimx ), dimy ( K0.dimy ),dimu ( K0.dimu ), 
     206<a name="l00268"></a>00268                 A ( K0.A ), B ( K0.B ), C ( K0.C ), D ( K0.D ), 
     207<a name="l00269"></a>00269                 Q(K0.Q), R(K0.R), 
     208<a name="l00270"></a>00270                 est ( K0.est ), fy ( K0.fy ), _yp(fy._mu()),_Ry(fy._R()), _mu(est._mu()), _P(est._R()) { 
     209<a name="l00271"></a>00271  
     210<a name="l00272"></a>00272 <span class="comment">// copy values in pointers</span> 
     211<a name="l00273"></a>00273 <span class="comment">//      _mu = K0._mu;</span> 
     212<a name="l00274"></a>00274 <span class="comment">//      _P = K0._P;</span> 
     213<a name="l00275"></a>00275 <span class="comment">//      _yp = K0._yp;</span> 
     214<a name="l00276"></a>00276 <span class="comment">//      _Ry = K0._Ry;</span> 
     215<a name="l00277"></a>00277  
     216<a name="l00278"></a>00278 } 
    216217<a name="l00279"></a>00279  
    217 <a name="l00280"></a>00280 } 
    218 <a name="l00281"></a>00281  
    219 <a name="l00282"></a>00282 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt; 
    220 <a name="l00283"></a><a class="code" href="classbdm_1_1Kalman.html#025a0196cbcc2e6adb13311f9d3d52b4">00283</a> <a class="code" href="classbdm_1_1Kalman.html" title="Kalman filter with covariance matrices in square root form.">Kalman&lt;sq_T&gt;::Kalman</a> ( ) : <a class="code" href="classbdm_1_1BM.html" title="Bayesian Model of a system, i.e. all uncertainty is modeled by probabilities.">BM</a> (), est ( ), fy (),  _yp(fy._mu()), _Ry(fy._R()), _mu(est._mu()), _P(est._R()) { 
    221 <a name="l00284"></a>00284 }; 
    222 <a name="l00285"></a>00285  
    223 <a name="l00286"></a>00286 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt; 
    224 <a name="l00287"></a><a class="code" href="classbdm_1_1Kalman.html#3c7fb87fb6b87d08deb6a5a7862da957">00287</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1Kalman.html" title="Kalman filter with covariance matrices in square root form.">Kalman&lt;sq_T&gt;::set_parameters</a> ( <span class="keyword">const</span> mat &amp;A0,<span class="keyword">const</span>  mat &amp;B0, <span class="keyword">const</span> mat &amp;C0, <span class="keyword">const</span> mat &amp;D0, <span class="keyword">const</span> sq_T &amp;Q0, <span class="keyword">const</span> sq_T &amp;R0 ) { 
    225 <a name="l00288"></a>00288         <a class="code" href="classbdm_1_1Kalman.html#ba7699cdb3b1382a54d3e28b9b7517fa" title="cache of rv.count()">dimx</a> = A0.rows(); 
    226 <a name="l00289"></a>00289         <a class="code" href="classbdm_1_1Kalman.html#d2c36ba01760bf207b985bf321b7817f" title="cache of rvy.count()">dimy</a> = C0.rows(); 
    227 <a name="l00290"></a>00290         <a class="code" href="classbdm_1_1Kalman.html#c5136ef617f6ac0e426bea222755d92b" title="cache of rvu.count()">dimu</a> = B0.cols(); 
    228 <a name="l00291"></a>00291          
    229 <a name="l00292"></a>00292         it_assert_debug ( A0.cols() ==<a class="code" href="classbdm_1_1Kalman.html#ba7699cdb3b1382a54d3e28b9b7517fa" title="cache of rv.count()">dimx</a>, <span class="stringliteral">"Kalman: A is not square"</span> ); 
    230 <a name="l00293"></a>00293         it_assert_debug ( B0.rows() ==<a class="code" href="classbdm_1_1Kalman.html#ba7699cdb3b1382a54d3e28b9b7517fa" title="cache of rv.count()">dimx</a>, <span class="stringliteral">"Kalman: B is not compatible"</span> ); 
    231 <a name="l00294"></a>00294         it_assert_debug ( C0.cols() ==<a class="code" href="classbdm_1_1Kalman.html#ba7699cdb3b1382a54d3e28b9b7517fa" title="cache of rv.count()">dimx</a>, <span class="stringliteral">"Kalman: C is not square"</span> ); 
    232 <a name="l00295"></a>00295         it_assert_debug ( ( D0.rows() ==<a class="code" href="classbdm_1_1Kalman.html#d2c36ba01760bf207b985bf321b7817f" title="cache of rvy.count()">dimy</a> ) || ( D0.cols() ==<a class="code" href="classbdm_1_1Kalman.html#c5136ef617f6ac0e426bea222755d92b" title="cache of rvu.count()">dimu</a> ), <span class="stringliteral">"Kalman: D is not compatible"</span> ); 
    233 <a name="l00296"></a>00296         it_assert_debug ( ( R0.cols() ==<a class="code" href="classbdm_1_1Kalman.html#d2c36ba01760bf207b985bf321b7817f" title="cache of rvy.count()">dimy</a> ) || ( R0.rows() ==<a class="code" href="classbdm_1_1Kalman.html#d2c36ba01760bf207b985bf321b7817f" title="cache of rvy.count()">dimy</a> ), <span class="stringliteral">"Kalman: R is not compatible"</span> ); 
    234 <a name="l00297"></a>00297         it_assert_debug ( ( Q0.cols() ==<a class="code" href="classbdm_1_1Kalman.html#ba7699cdb3b1382a54d3e28b9b7517fa" title="cache of rv.count()">dimx</a> ) || ( Q0.rows() ==<a class="code" href="classbdm_1_1Kalman.html#ba7699cdb3b1382a54d3e28b9b7517fa" title="cache of rv.count()">dimx</a> ), <span class="stringliteral">"Kalman: Q is not compatible"</span> ); 
    235 <a name="l00298"></a>00298  
    236 <a name="l00299"></a>00299         <a class="code" href="classbdm_1_1Kalman.html#0a2072e2090c10fac74ad30a023a4ace" title="Matrix A.">A</a> = A0; 
    237 <a name="l00300"></a>00300         <a class="code" href="classbdm_1_1Kalman.html#5977b2c81857948a35105f0e7840203c" title="Matrix B.">B</a> = B0; 
    238 <a name="l00301"></a>00301         <a class="code" href="classbdm_1_1Kalman.html#818eba63a23972786a4579ad30294177" title="Matrix C.">C</a> = C0; 
    239 <a name="l00302"></a>00302         <a class="code" href="classbdm_1_1Kalman.html#7b56ac423d0654b5755e4f852a870456" title="Matrix D.">D</a> = D0; 
    240 <a name="l00303"></a>00303         <a class="code" href="classbdm_1_1Kalman.html#475b088287cdfbba4dc60a3d027728b7" title="Matrix R in square-root form.">R</a> = R0; 
    241 <a name="l00304"></a>00304         <a class="code" href="classbdm_1_1Kalman.html#70f8bf19e81b532c60fd3a7a152425ee" title="Matrix Q in square-root form.">Q</a> = Q0; 
    242 <a name="l00305"></a>00305 } 
    243 <a name="l00306"></a>00306  
    244 <a name="l00307"></a>00307 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt; 
    245 <a name="l00308"></a><a class="code" href="classbdm_1_1Kalman.html#4a39330c14eff8d13179e868a1d1aa8c">00308</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1Kalman.html" title="Kalman filter with covariance matrices in square root form.">Kalman&lt;sq_T&gt;::bayes</a> ( <span class="keyword">const</span> vec &amp;dt ) { 
    246 <a name="l00309"></a>00309         it_assert_debug ( dt.length() == ( <a class="code" href="classbdm_1_1Kalman.html#d2c36ba01760bf207b985bf321b7817f" title="cache of rvy.count()">dimy</a>+<a class="code" href="classbdm_1_1Kalman.html#c5136ef617f6ac0e426bea222755d92b" title="cache of rvu.count()">dimu</a> ),<span class="stringliteral">"KalmanFull::bayes wrong size of dt"</span> ); 
    247 <a name="l00310"></a>00310  
    248 <a name="l00311"></a>00311         sq_T iRy(<a class="code" href="classbdm_1_1Kalman.html#d2c36ba01760bf207b985bf321b7817f" title="cache of rvy.count()">dimy</a>); 
    249 <a name="l00312"></a>00312         vec u = dt.get ( <a class="code" href="classbdm_1_1Kalman.html#d2c36ba01760bf207b985bf321b7817f" title="cache of rvy.count()">dimy</a>,<a class="code" href="classbdm_1_1Kalman.html#d2c36ba01760bf207b985bf321b7817f" title="cache of rvy.count()">dimy</a>+<a class="code" href="classbdm_1_1Kalman.html#c5136ef617f6ac0e426bea222755d92b" title="cache of rvu.count()">dimu</a>-1 ); 
    250 <a name="l00313"></a>00313         vec y = dt.get ( 0,<a class="code" href="classbdm_1_1Kalman.html#d2c36ba01760bf207b985bf321b7817f" title="cache of rvy.count()">dimy</a>-1 ); 
    251 <a name="l00314"></a>00314         <span class="comment">//Time update</span> 
    252 <a name="l00315"></a>00315         <a class="code" href="classbdm_1_1Kalman.html#fa172078091e45561343fa513dd573b0" title="cache of est.mu">_mu</a> = <a class="code" href="classbdm_1_1Kalman.html#0a2072e2090c10fac74ad30a023a4ace" title="Matrix A.">A</a>* <a class="code" href="classbdm_1_1Kalman.html#fa172078091e45561343fa513dd573b0" title="cache of est.mu">_mu</a> + <a class="code" href="classbdm_1_1Kalman.html#5977b2c81857948a35105f0e7840203c" title="Matrix B.">B</a>*u; 
    253 <a name="l00316"></a>00316         <span class="comment">//P  = A*P*A.transpose() + Q; in sq_T</span> 
    254 <a name="l00317"></a>00317         <a class="code" href="classbdm_1_1Kalman.html#00c27b0bf324f0018497921ca23c71ed" title="cache of est.R">_P</a>.mult_sym ( <a class="code" href="classbdm_1_1Kalman.html#0a2072e2090c10fac74ad30a023a4ace" title="Matrix A.">A</a> ); 
    255 <a name="l00318"></a>00318         <a class="code" href="classbdm_1_1Kalman.html#00c27b0bf324f0018497921ca23c71ed" title="cache of est.R">_P</a>  +=<a class="code" href="classbdm_1_1Kalman.html#70f8bf19e81b532c60fd3a7a152425ee" title="Matrix Q in square-root form.">Q</a>; 
    256 <a name="l00319"></a>00319  
    257 <a name="l00320"></a>00320         <span class="comment">//Data update</span> 
    258 <a name="l00321"></a>00321         <span class="comment">//_Ry = C*P*C.transpose() + R; in sq_T</span> 
    259 <a name="l00322"></a>00322         <a class="code" href="classbdm_1_1Kalman.html#00c27b0bf324f0018497921ca23c71ed" title="cache of est.R">_P</a>.mult_sym ( <a class="code" href="classbdm_1_1Kalman.html#818eba63a23972786a4579ad30294177" title="Matrix C.">C</a>, <a class="code" href="classbdm_1_1Kalman.html#2dd268f2d7fbe6382cb8825a1114192a" title="cache of fy.R">_Ry</a> ); 
    260 <a name="l00323"></a>00323         <a class="code" href="classbdm_1_1Kalman.html#2dd268f2d7fbe6382cb8825a1114192a" title="cache of fy.R">_Ry</a>  +=<a class="code" href="classbdm_1_1Kalman.html#475b088287cdfbba4dc60a3d027728b7" title="Matrix R in square-root form.">R</a>; 
     218<a name="l00280"></a>00280 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt; 
     219<a name="l00281"></a><a class="code" href="classbdm_1_1Kalman.html#025a0196cbcc2e6adb13311f9d3d52b4">00281</a> <a class="code" href="classbdm_1_1Kalman.html" title="Kalman filter with covariance matrices in square root form.">Kalman&lt;sq_T&gt;::Kalman</a> ( ) : <a class="code" href="classbdm_1_1BM.html" title="Bayesian Model of a system, i.e. all uncertainty is modeled by probabilities.">BM</a> (), est ( ), fy (),  _yp(fy._mu()), _Ry(fy._R()), _mu(est._mu()), _P(est._R()) { 
     220<a name="l00282"></a>00282 }; 
     221<a name="l00283"></a>00283  
     222<a name="l00284"></a>00284 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt; 
     223<a name="l00285"></a><a class="code" href="classbdm_1_1Kalman.html#3c7fb87fb6b87d08deb6a5a7862da957">00285</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1Kalman.html" title="Kalman filter with covariance matrices in square root form.">Kalman&lt;sq_T&gt;::set_parameters</a> ( <span class="keyword">const</span> mat &amp;A0,<span class="keyword">const</span>  mat &amp;B0, <span class="keyword">const</span> mat &amp;C0, <span class="keyword">const</span> mat &amp;D0, <span class="keyword">const</span> sq_T &amp;Q0, <span class="keyword">const</span> sq_T &amp;R0 ) { 
     224<a name="l00286"></a>00286         <a class="code" href="classbdm_1_1Kalman.html#ba7699cdb3b1382a54d3e28b9b7517fa" title="cache of rv.count()">dimx</a> = A0.rows(); 
     225<a name="l00287"></a>00287         <a class="code" href="classbdm_1_1Kalman.html#d2c36ba01760bf207b985bf321b7817f" title="cache of rvy.count()">dimy</a> = C0.rows(); 
     226<a name="l00288"></a>00288         <a class="code" href="classbdm_1_1Kalman.html#c5136ef617f6ac0e426bea222755d92b" title="cache of rvu.count()">dimu</a> = B0.cols(); 
     227<a name="l00289"></a>00289          
     228<a name="l00290"></a>00290         it_assert_debug ( A0.cols() ==<a class="code" href="classbdm_1_1Kalman.html#ba7699cdb3b1382a54d3e28b9b7517fa" title="cache of rv.count()">dimx</a>, <span class="stringliteral">"Kalman: A is not square"</span> ); 
     229<a name="l00291"></a>00291         it_assert_debug ( B0.rows() ==<a class="code" href="classbdm_1_1Kalman.html#ba7699cdb3b1382a54d3e28b9b7517fa" title="cache of rv.count()">dimx</a>, <span class="stringliteral">"Kalman: B is not compatible"</span> ); 
     230<a name="l00292"></a>00292         it_assert_debug ( C0.cols() ==<a class="code" href="classbdm_1_1Kalman.html#ba7699cdb3b1382a54d3e28b9b7517fa" title="cache of rv.count()">dimx</a>, <span class="stringliteral">"Kalman: C is not square"</span> ); 
     231<a name="l00293"></a>00293         it_assert_debug ( ( D0.rows() ==<a class="code" href="classbdm_1_1Kalman.html#d2c36ba01760bf207b985bf321b7817f" title="cache of rvy.count()">dimy</a> ) || ( D0.cols() ==<a class="code" href="classbdm_1_1Kalman.html#c5136ef617f6ac0e426bea222755d92b" title="cache of rvu.count()">dimu</a> ), <span class="stringliteral">"Kalman: D is not compatible"</span> ); 
     232<a name="l00294"></a>00294         it_assert_debug ( ( R0.cols() ==<a class="code" href="classbdm_1_1Kalman.html#d2c36ba01760bf207b985bf321b7817f" title="cache of rvy.count()">dimy</a> ) || ( R0.rows() ==<a class="code" href="classbdm_1_1Kalman.html#d2c36ba01760bf207b985bf321b7817f" title="cache of rvy.count()">dimy</a> ), <span class="stringliteral">"Kalman: R is not compatible"</span> ); 
     233<a name="l00295"></a>00295         it_assert_debug ( ( Q0.cols() ==<a class="code" href="classbdm_1_1Kalman.html#ba7699cdb3b1382a54d3e28b9b7517fa" title="cache of rv.count()">dimx</a> ) || ( Q0.rows() ==<a class="code" href="classbdm_1_1Kalman.html#ba7699cdb3b1382a54d3e28b9b7517fa" title="cache of rv.count()">dimx</a> ), <span class="stringliteral">"Kalman: Q is not compatible"</span> ); 
     234<a name="l00296"></a>00296  
     235<a name="l00297"></a>00297         <a class="code" href="classbdm_1_1Kalman.html#0a2072e2090c10fac74ad30a023a4ace" title="Matrix A.">A</a> = A0; 
     236<a name="l00298"></a>00298         <a class="code" href="classbdm_1_1Kalman.html#5977b2c81857948a35105f0e7840203c" title="Matrix B.">B</a> = B0; 
     237<a name="l00299"></a>00299         <a class="code" href="classbdm_1_1Kalman.html#818eba63a23972786a4579ad30294177" title="Matrix C.">C</a> = C0; 
     238<a name="l00300"></a>00300         <a class="code" href="classbdm_1_1Kalman.html#7b56ac423d0654b5755e4f852a870456" title="Matrix D.">D</a> = D0; 
     239<a name="l00301"></a>00301         <a class="code" href="classbdm_1_1Kalman.html#475b088287cdfbba4dc60a3d027728b7" title="Matrix R in square-root form.">R</a> = R0; 
     240<a name="l00302"></a>00302         <a class="code" href="classbdm_1_1Kalman.html#70f8bf19e81b532c60fd3a7a152425ee" title="Matrix Q in square-root form.">Q</a> = Q0; 
     241<a name="l00303"></a>00303 } 
     242<a name="l00304"></a>00304  
     243<a name="l00305"></a>00305 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt; 
     244<a name="l00306"></a><a class="code" href="classbdm_1_1Kalman.html#4a39330c14eff8d13179e868a1d1aa8c">00306</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1Kalman.html" title="Kalman filter with covariance matrices in square root form.">Kalman&lt;sq_T&gt;::bayes</a> ( <span class="keyword">const</span> vec &amp;dt ) { 
     245<a name="l00307"></a>00307         it_assert_debug ( dt.length() == ( <a class="code" href="classbdm_1_1Kalman.html#d2c36ba01760bf207b985bf321b7817f" title="cache of rvy.count()">dimy</a>+<a class="code" href="classbdm_1_1Kalman.html#c5136ef617f6ac0e426bea222755d92b" title="cache of rvu.count()">dimu</a> ),<span class="stringliteral">"KalmanFull::bayes wrong size of dt"</span> ); 
     246<a name="l00308"></a>00308  
     247<a name="l00309"></a>00309         sq_T iRy(<a class="code" href="classbdm_1_1Kalman.html#d2c36ba01760bf207b985bf321b7817f" title="cache of rvy.count()">dimy</a>); 
     248<a name="l00310"></a>00310         vec u = dt.get ( <a class="code" href="classbdm_1_1Kalman.html#d2c36ba01760bf207b985bf321b7817f" title="cache of rvy.count()">dimy</a>,<a class="code" href="classbdm_1_1Kalman.html#d2c36ba01760bf207b985bf321b7817f" title="cache of rvy.count()">dimy</a>+<a class="code" href="classbdm_1_1Kalman.html#c5136ef617f6ac0e426bea222755d92b" title="cache of rvu.count()">dimu</a>-1 ); 
     249<a name="l00311"></a>00311         vec y = dt.get ( 0,<a class="code" href="classbdm_1_1Kalman.html#d2c36ba01760bf207b985bf321b7817f" title="cache of rvy.count()">dimy</a>-1 ); 
     250<a name="l00312"></a>00312         <span class="comment">//Time update</span> 
     251<a name="l00313"></a>00313         <a class="code" href="classbdm_1_1Kalman.html#fa172078091e45561343fa513dd573b0" title="cache of est.mu">_mu</a> = <a class="code" href="classbdm_1_1Kalman.html#0a2072e2090c10fac74ad30a023a4ace" title="Matrix A.">A</a>* <a class="code" href="classbdm_1_1Kalman.html#fa172078091e45561343fa513dd573b0" title="cache of est.mu">_mu</a> + <a class="code" href="classbdm_1_1Kalman.html#5977b2c81857948a35105f0e7840203c" title="Matrix B.">B</a>*u; 
     252<a name="l00314"></a>00314         <span class="comment">//P  = A*P*A.transpose() + Q; in sq_T</span> 
     253<a name="l00315"></a>00315         <a class="code" href="classbdm_1_1Kalman.html#00c27b0bf324f0018497921ca23c71ed" title="cache of est.R">_P</a>.mult_sym ( <a class="code" href="classbdm_1_1Kalman.html#0a2072e2090c10fac74ad30a023a4ace" title="Matrix A.">A</a> ); 
     254<a name="l00316"></a>00316         <a class="code" href="classbdm_1_1Kalman.html#00c27b0bf324f0018497921ca23c71ed" title="cache of est.R">_P</a>  +=<a class="code" href="classbdm_1_1Kalman.html#70f8bf19e81b532c60fd3a7a152425ee" title="Matrix Q in square-root form.">Q</a>; 
     255<a name="l00317"></a>00317  
     256<a name="l00318"></a>00318         <span class="comment">//Data update</span> 
     257<a name="l00319"></a>00319         <span class="comment">//_Ry = C*P*C.transpose() + R; in sq_T</span> 
     258<a name="l00320"></a>00320         <a class="code" href="classbdm_1_1Kalman.html#00c27b0bf324f0018497921ca23c71ed" title="cache of est.R">_P</a>.mult_sym ( <a class="code" href="classbdm_1_1Kalman.html#818eba63a23972786a4579ad30294177" title="Matrix C.">C</a>, <a class="code" href="classbdm_1_1Kalman.html#2dd268f2d7fbe6382cb8825a1114192a" title="cache of fy.R">_Ry</a> ); 
     259<a name="l00321"></a>00321         <a class="code" href="classbdm_1_1Kalman.html#2dd268f2d7fbe6382cb8825a1114192a" title="cache of fy.R">_Ry</a>  +=<a class="code" href="classbdm_1_1Kalman.html#475b088287cdfbba4dc60a3d027728b7" title="Matrix R in square-root form.">R</a>; 
     260<a name="l00322"></a>00322  
     261<a name="l00323"></a>00323         mat Pfull = <a class="code" href="classbdm_1_1Kalman.html#00c27b0bf324f0018497921ca23c71ed" title="cache of est.R">_P</a>.to_mat(); 
    261262<a name="l00324"></a>00324  
    262 <a name="l00325"></a>00325         mat Pfull = <a class="code" href="classbdm_1_1Kalman.html#00c27b0bf324f0018497921ca23c71ed" title="cache of est.R">_P</a>.to_mat(); 
    263 <a name="l00326"></a>00326  
    264 <a name="l00327"></a>00327         <a class="code" href="classbdm_1_1Kalman.html#2dd268f2d7fbe6382cb8825a1114192a" title="cache of fy.R">_Ry</a>.inv ( iRy ); <span class="comment">// result is in _iRy;</span> 
    265 <a name="l00328"></a>00328         <a class="code" href="classbdm_1_1Kalman.html#bd69dfb802465f22dd84d73a180d5c92" title="placeholder for Kalman gain">_K</a> = Pfull*<a class="code" href="classbdm_1_1Kalman.html#818eba63a23972786a4579ad30294177" title="Matrix C.">C</a>.transpose() * ( iRy.to_mat() ); 
    266 <a name="l00329"></a>00329  
    267 <a name="l00330"></a>00330         sq_T pom ( ( <span class="keywordtype">int</span> ) Pfull.rows() ); 
    268 <a name="l00331"></a>00331         iRy.mult_sym_t ( <a class="code" href="classbdm_1_1Kalman.html#818eba63a23972786a4579ad30294177" title="Matrix C.">C</a>*Pfull,pom ); 
    269 <a name="l00332"></a>00332         (<a class="code" href="classbdm_1_1Kalman.html#00c27b0bf324f0018497921ca23c71ed" title="cache of est.R">_P</a> ) -= pom; <span class="comment">// P = P -PC'iRy*CP;</span> 
    270 <a name="l00333"></a>00333         (<a class="code" href="classbdm_1_1Kalman.html#c249d45258c8578b13858ad3e7b729b1" title="cache of fy.mu">_yp</a> ) = <a class="code" href="classbdm_1_1Kalman.html#818eba63a23972786a4579ad30294177" title="Matrix C.">C</a>* <a class="code" href="classbdm_1_1Kalman.html#fa172078091e45561343fa513dd573b0" title="cache of est.mu">_mu</a>  +<a class="code" href="classbdm_1_1Kalman.html#7b56ac423d0654b5755e4f852a870456" title="Matrix D.">D</a>*u; <span class="comment">//y prediction</span> 
    271 <a name="l00334"></a>00334         (<a class="code" href="classbdm_1_1Kalman.html#fa172078091e45561343fa513dd573b0" title="cache of est.mu">_mu</a> ) += <a class="code" href="classbdm_1_1Kalman.html#bd69dfb802465f22dd84d73a180d5c92" title="placeholder for Kalman gain">_K</a>* ( y- <a class="code" href="classbdm_1_1Kalman.html#c249d45258c8578b13858ad3e7b729b1" title="cache of fy.mu">_yp</a>  ); 
    272 <a name="l00335"></a>00335  
    273 <a name="l00336"></a>00336  
    274 <a name="l00337"></a>00337         <span class="keywordflow">if</span> ( <a class="code" href="classbdm_1_1BM.html#faff0ad12556fe7dc0e2807d4fd938ee" title="If true, the filter will compute likelihood of the data record and store it in ll...">evalll</a>==<span class="keyword">true</span> ) { <span class="comment">//likelihood of observation y</span> 
    275 <a name="l00338"></a>00338                 <a class="code" href="classbdm_1_1BM.html#4064b6559d962633e4372b12f4cd204a" title="Logarithm of marginalized data likelihood.">ll</a>=<a class="code" href="classbdm_1_1Kalman.html#ba555c394c429f6831c9bbabfa2c944c" title="preditive density on $y_t$">fy</a>.evallog ( y ); 
    276 <a name="l00339"></a>00339         } 
     263<a name="l00325"></a>00325         <a class="code" href="classbdm_1_1Kalman.html#2dd268f2d7fbe6382cb8825a1114192a" title="cache of fy.R">_Ry</a>.inv ( iRy ); <span class="comment">// result is in _iRy;</span> 
     264<a name="l00326"></a>00326         <a class="code" href="classbdm_1_1Kalman.html#bd69dfb802465f22dd84d73a180d5c92" title="placeholder for Kalman gain">_K</a> = Pfull*<a class="code" href="classbdm_1_1Kalman.html#818eba63a23972786a4579ad30294177" title="Matrix C.">C</a>.transpose() * ( iRy.to_mat() ); 
     265<a name="l00327"></a>00327  
     266<a name="l00328"></a>00328         sq_T pom ( ( <span class="keywordtype">int</span> ) Pfull.rows() ); 
     267<a name="l00329"></a>00329         iRy.mult_sym_t ( <a class="code" href="classbdm_1_1Kalman.html#818eba63a23972786a4579ad30294177" title="Matrix C.">C</a>*Pfull,pom ); 
     268<a name="l00330"></a>00330         (<a class="code" href="classbdm_1_1Kalman.html#00c27b0bf324f0018497921ca23c71ed" title="cache of est.R">_P</a> ) -= pom; <span class="comment">// P = P -PC'iRy*CP;</span> 
     269<a name="l00331"></a>00331         (<a class="code" href="classbdm_1_1Kalman.html#c249d45258c8578b13858ad3e7b729b1" title="cache of fy.mu">_yp</a> ) = <a class="code" href="classbdm_1_1Kalman.html#818eba63a23972786a4579ad30294177" title="Matrix C.">C</a>* <a class="code" href="classbdm_1_1Kalman.html#fa172078091e45561343fa513dd573b0" title="cache of est.mu">_mu</a>  +<a class="code" href="classbdm_1_1Kalman.html#7b56ac423d0654b5755e4f852a870456" title="Matrix D.">D</a>*u; <span class="comment">//y prediction</span> 
     270<a name="l00332"></a>00332         (<a class="code" href="classbdm_1_1Kalman.html#fa172078091e45561343fa513dd573b0" title="cache of est.mu">_mu</a> ) += <a class="code" href="classbdm_1_1Kalman.html#bd69dfb802465f22dd84d73a180d5c92" title="placeholder for Kalman gain">_K</a>* ( y- <a class="code" href="classbdm_1_1Kalman.html#c249d45258c8578b13858ad3e7b729b1" title="cache of fy.mu">_yp</a>  ); 
     271<a name="l00333"></a>00333  
     272<a name="l00334"></a>00334  
     273<a name="l00335"></a>00335         <span class="keywordflow">if</span> ( <a class="code" href="classbdm_1_1BM.html#faff0ad12556fe7dc0e2807d4fd938ee" title="If true, the filter will compute likelihood of the data record and store it in ll...">evalll</a>==<span class="keyword">true</span> ) { <span class="comment">//likelihood of observation y</span> 
     274<a name="l00336"></a>00336                 <a class="code" href="classbdm_1_1BM.html#4064b6559d962633e4372b12f4cd204a" title="Logarithm of marginalized data likelihood.">ll</a>=<a class="code" href="classbdm_1_1Kalman.html#ba555c394c429f6831c9bbabfa2c944c" title="preditive density on $y_t$">fy</a>.evallog ( y ); 
     275<a name="l00337"></a>00337         } 
     276<a name="l00338"></a>00338  
     277<a name="l00339"></a>00339 <span class="comment">//cout &lt;&lt; "y: " &lt;&lt; y-(*_yp) &lt;&lt;" R: " &lt;&lt; _Ry-&gt;to_mat() &lt;&lt; " iR: " &lt;&lt; _iRy-&gt;to_mat() &lt;&lt; " ll: " &lt;&lt; ll &lt;&lt;endl;</span> 
    277278<a name="l00340"></a>00340  
    278 <a name="l00341"></a>00341 <span class="comment">//cout &lt;&lt; "y: " &lt;&lt; y-(*_yp) &lt;&lt;" R: " &lt;&lt; _Ry-&gt;to_mat() &lt;&lt; " iR: " &lt;&lt; _iRy-&gt;to_mat() &lt;&lt; " ll: " &lt;&lt; ll &lt;&lt;endl;</span> 
    279 <a name="l00342"></a>00342  
    280 <a name="l00343"></a>00343 }; 
    281 <a name="l00344"></a>00344   
    282 <a name="l00345"></a>00345  
     279<a name="l00341"></a>00341 }; 
     280<a name="l00342"></a>00342   
     281<a name="l00343"></a>00343  
     282<a name="l00344"></a>00344  
     283<a name="l00345"></a>00345 <span class="comment">//TODO why not const pointer??</span> 
    283284<a name="l00346"></a>00346  
    284 <a name="l00347"></a>00347 <span class="comment">//TODO why not const pointer??</span> 
    285 <a name="l00348"></a>00348  
    286 <a name="l00349"></a>00349 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt; 
    287 <a name="l00350"></a><a class="code" href="classbdm_1_1EKF.html#d087a8bb408d26ac4f5c542746b81059">00350</a> <a class="code" href="classbdm_1_1EKF.html" title="Extended Kalman Filter.">EKF&lt;sq_T&gt;::EKF</a> ( <a class="code" href="classbdm_1_1RV.html" title="Class representing variables, most often random variables.">RV</a> rvx0, <a class="code" href="classbdm_1_1RV.html" title="Class representing variables, most often random variables.">RV</a> rvy0, <a class="code" href="classbdm_1_1RV.html" title="Class representing variables, most often random variables.">RV</a> rvu0 ) : <a class="code" href="classbdm_1_1Kalman.html" title="Kalman filter with covariance matrices in square root form.">Kalman</a>&lt;sq_T&gt; ( rvx0,rvy0,rvu0 ) {} 
    288 <a name="l00351"></a>00351  
    289 <a name="l00352"></a>00352 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt; 
    290 <a name="l00353"></a><a class="code" href="classbdm_1_1EKF.html#00fec1a0a6a467eb83fb36c65eba7bcb">00353</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1EKF.html" title="Extended Kalman Filter.">EKF&lt;sq_T&gt;::set_parameters</a> ( <a class="code" href="classbdm_1_1diffbifn.html" title="Class representing a differentiable function of two variables .">diffbifn</a>* pfxu0,  <a class="code" href="classbdm_1_1diffbifn.html" title="Class representing a differentiable function of two variables .">diffbifn</a>* phxu0,<span class="keyword">const</span> sq_T Q0,<span class="keyword">const</span> sq_T R0 ) { 
    291 <a name="l00354"></a>00354         pfxu = pfxu0; 
    292 <a name="l00355"></a>00355         phxu = phxu0; 
    293 <a name="l00356"></a>00356  
    294 <a name="l00357"></a>00357         <span class="comment">//initialize matrices A C, later, these will be only updated!</span> 
    295 <a name="l00358"></a>00358         pfxu-&gt;<a class="code" href="classbdm_1_1diffbifn.html#651184f808a35f236dbfea21aca1b6ac" title="Evaluates  and writes result into A .">dfdx_cond</a> ( <a class="code" href="classbdm_1_1Kalman.html#fa172078091e45561343fa513dd573b0" title="cache of est.mu">_mu</a>,zeros ( <a class="code" href="classbdm_1_1Kalman.html#c5136ef617f6ac0e426bea222755d92b" title="cache of rvu.count()">dimu</a> ),<a class="code" href="classbdm_1_1Kalman.html#0a2072e2090c10fac74ad30a023a4ace" title="Matrix A.">A</a>,<span class="keyword">true</span> ); 
    296 <a name="l00359"></a>00359 <span class="comment">//      pfxu-&gt;dfdu_cond ( *_mu,zeros ( dimu ),B,true );</span> 
    297 <a name="l00360"></a>00360         <a class="code" href="classbdm_1_1Kalman.html#5977b2c81857948a35105f0e7840203c" title="Matrix B.">B</a>.clear(); 
    298 <a name="l00361"></a>00361         phxu-&gt;<a class="code" href="classbdm_1_1diffbifn.html#651184f808a35f236dbfea21aca1b6ac" title="Evaluates  and writes result into A .">dfdx_cond</a> ( <a class="code" href="classbdm_1_1Kalman.html#fa172078091e45561343fa513dd573b0" title="cache of est.mu">_mu</a>,zeros ( <a class="code" href="classbdm_1_1Kalman.html#c5136ef617f6ac0e426bea222755d92b" title="cache of rvu.count()">dimu</a> ),<a class="code" href="classbdm_1_1Kalman.html#818eba63a23972786a4579ad30294177" title="Matrix C.">C</a>,<span class="keyword">true</span> ); 
    299 <a name="l00362"></a>00362 <span class="comment">//      phxu-&gt;dfdu_cond ( *_mu,zeros ( dimu ),D,true );</span> 
    300 <a name="l00363"></a>00363         <a class="code" href="classbdm_1_1Kalman.html#7b56ac423d0654b5755e4f852a870456" title="Matrix D.">D</a>.clear(); 
    301 <a name="l00364"></a>00364  
    302 <a name="l00365"></a>00365         <a class="code" href="classbdm_1_1Kalman.html#475b088287cdfbba4dc60a3d027728b7" title="Matrix R in square-root form.">R</a> = R0; 
    303 <a name="l00366"></a>00366         <a class="code" href="classbdm_1_1Kalman.html#70f8bf19e81b532c60fd3a7a152425ee" title="Matrix Q in square-root form.">Q</a> = Q0; 
    304 <a name="l00367"></a>00367 } 
    305 <a name="l00368"></a>00368  
    306 <a name="l00369"></a>00369 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt; 
    307 <a name="l00370"></a><a class="code" href="classbdm_1_1EKF.html#3fb182ecc29b10ca1163cecbf3bcccfa">00370</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1EKF.html" title="Extended Kalman Filter.">EKF&lt;sq_T&gt;::bayes</a> ( <span class="keyword">const</span> vec &amp;dt ) { 
    308 <a name="l00371"></a>00371         it_assert_debug ( dt.length() == ( <a class="code" href="classbdm_1_1Kalman.html#d2c36ba01760bf207b985bf321b7817f" title="cache of rvy.count()">dimy</a>+<a class="code" href="classbdm_1_1Kalman.html#c5136ef617f6ac0e426bea222755d92b" title="cache of rvu.count()">dimu</a> ),<span class="stringliteral">"KalmanFull::bayes wrong size of dt"</span> ); 
    309 <a name="l00372"></a>00372  
    310 <a name="l00373"></a>00373         sq_T iRy(<a class="code" href="classbdm_1_1Kalman.html#d2c36ba01760bf207b985bf321b7817f" title="cache of rvy.count()">dimy</a>,<a class="code" href="classbdm_1_1Kalman.html#d2c36ba01760bf207b985bf321b7817f" title="cache of rvy.count()">dimy</a>); 
    311 <a name="l00374"></a>00374         vec u = dt.get ( <a class="code" href="classbdm_1_1Kalman.html#d2c36ba01760bf207b985bf321b7817f" title="cache of rvy.count()">dimy</a>,<a class="code" href="classbdm_1_1Kalman.html#d2c36ba01760bf207b985bf321b7817f" title="cache of rvy.count()">dimy</a>+<a class="code" href="classbdm_1_1Kalman.html#c5136ef617f6ac0e426bea222755d92b" title="cache of rvu.count()">dimu</a>-1 ); 
    312 <a name="l00375"></a>00375         vec y = dt.get ( 0,<a class="code" href="classbdm_1_1Kalman.html#d2c36ba01760bf207b985bf321b7817f" title="cache of rvy.count()">dimy</a>-1 ); 
    313 <a name="l00376"></a>00376         <span class="comment">//Time update</span> 
    314 <a name="l00377"></a>00377         <a class="code" href="classbdm_1_1Kalman.html#fa172078091e45561343fa513dd573b0" title="cache of est.mu">_mu</a> = pfxu-&gt;<a class="code" href="classbdm_1_1diffbifn.html#188f31066bd72e1bf0ddacd1eb0e6af3" title="Evaluates  (VS: Do we really need common eval? ).">eval</a> ( <a class="code" href="classbdm_1_1Kalman.html#fa172078091e45561343fa513dd573b0" title="cache of est.mu">_mu</a>, u ); 
    315 <a name="l00378"></a>00378         pfxu-&gt;<a class="code" href="classbdm_1_1diffbifn.html#651184f808a35f236dbfea21aca1b6ac" title="Evaluates  and writes result into A .">dfdx_cond</a> ( <a class="code" href="classbdm_1_1Kalman.html#fa172078091e45561343fa513dd573b0" title="cache of est.mu">_mu</a>,u,<a class="code" href="classbdm_1_1Kalman.html#0a2072e2090c10fac74ad30a023a4ace" title="Matrix A.">A</a>,<span class="keyword">false</span> ); <span class="comment">//update A by a derivative of fx</span> 
    316 <a name="l00379"></a>00379  
    317 <a name="l00380"></a>00380         <span class="comment">//P  = A*P*A.transpose() + Q; in sq_T</span> 
    318 <a name="l00381"></a>00381         <a class="code" href="classbdm_1_1Kalman.html#00c27b0bf324f0018497921ca23c71ed" title="cache of est.R">_P</a>.<a class="code" href="classfsqmat.html#5530d2756b5d991de755e6121c9a452e" title="Inplace symmetric multiplication by a SQUARE matrix , i.e. .">mult_sym</a> ( <a class="code" href="classbdm_1_1Kalman.html#0a2072e2090c10fac74ad30a023a4ace" title="Matrix A.">A</a> ); 
    319 <a name="l00382"></a>00382         <a class="code" href="classbdm_1_1Kalman.html#00c27b0bf324f0018497921ca23c71ed" title="cache of est.R">_P</a> +=<a class="code" href="classbdm_1_1Kalman.html#70f8bf19e81b532c60fd3a7a152425ee" title="Matrix Q in square-root form.">Q</a>; 
    320 <a name="l00383"></a>00383  
    321 <a name="l00384"></a>00384         <span class="comment">//Data update</span> 
    322 <a name="l00385"></a>00385         phxu-&gt;<a class="code" href="classbdm_1_1diffbifn.html#651184f808a35f236dbfea21aca1b6ac" title="Evaluates  and writes result into A .">dfdx_cond</a> ( <a class="code" href="classbdm_1_1Kalman.html#fa172078091e45561343fa513dd573b0" title="cache of est.mu">_mu</a>,u,<a class="code" href="classbdm_1_1Kalman.html#818eba63a23972786a4579ad30294177" title="Matrix C.">C</a>,<span class="keyword">false</span> ); <span class="comment">//update C by a derivative hx</span> 
    323 <a name="l00386"></a>00386         <span class="comment">//_Ry = C*P*C.transpose() + R; in sq_T</span> 
    324 <a name="l00387"></a>00387         <a class="code" href="classbdm_1_1Kalman.html#00c27b0bf324f0018497921ca23c71ed" title="cache of est.R">_P</a>.<a class="code" href="classfsqmat.html#5530d2756b5d991de755e6121c9a452e" title="Inplace symmetric multiplication by a SQUARE matrix , i.e. .">mult_sym</a> ( <a class="code" href="classbdm_1_1Kalman.html#818eba63a23972786a4579ad30294177" title="Matrix C.">C</a>, <a class="code" href="classbdm_1_1Kalman.html#2dd268f2d7fbe6382cb8825a1114192a" title="cache of fy.R">_Ry</a> ); 
    325 <a name="l00388"></a>00388         ( <a class="code" href="classbdm_1_1Kalman.html#2dd268f2d7fbe6382cb8825a1114192a" title="cache of fy.R">_Ry</a> ) +=<a class="code" href="classbdm_1_1Kalman.html#475b088287cdfbba4dc60a3d027728b7" title="Matrix R in square-root form.">R</a>; 
     285<a name="l00347"></a>00347 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt; 
     286<a name="l00348"></a><a class="code" href="classbdm_1_1EKF.html#d087a8bb408d26ac4f5c542746b81059">00348</a> <a class="code" href="classbdm_1_1EKF.html" title="Extended Kalman Filter.">EKF&lt;sq_T&gt;::EKF</a> ( <a class="code" href="classbdm_1_1RV.html" title="Class representing variables, most often random variables.">RV</a> rvx0, <a class="code" href="classbdm_1_1RV.html" title="Class representing variables, most often random variables.">RV</a> rvy0, <a class="code" href="classbdm_1_1RV.html" title="Class representing variables, most often random variables.">RV</a> rvu0 ) : <a class="code" href="classbdm_1_1Kalman.html" title="Kalman filter with covariance matrices in square root form.">Kalman</a>&lt;sq_T&gt; ( rvx0,rvy0,rvu0 ) {} 
     287<a name="l00349"></a>00349  
     288<a name="l00350"></a>00350 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt; 
     289<a name="l00351"></a><a class="code" href="classbdm_1_1EKF.html#00fec1a0a6a467eb83fb36c65eba7bcb">00351</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1EKF.html" title="Extended Kalman Filter.">EKF&lt;sq_T&gt;::set_parameters</a> ( <a class="code" href="classbdm_1_1diffbifn.html" title="Class representing a differentiable function of two variables .">diffbifn</a>* pfxu0,  <a class="code" href="classbdm_1_1diffbifn.html" title="Class representing a differentiable function of two variables .">diffbifn</a>* phxu0,<span class="keyword">const</span> sq_T Q0,<span class="keyword">const</span> sq_T R0 ) { 
     290<a name="l00352"></a>00352         pfxu = pfxu0; 
     291<a name="l00353"></a>00353         phxu = phxu0; 
     292<a name="l00354"></a>00354  
     293<a name="l00355"></a>00355         <span class="comment">//initialize matrices A C, later, these will be only updated!</span> 
     294<a name="l00356"></a>00356         pfxu-&gt;<a class="code" href="classbdm_1_1diffbifn.html#651184f808a35f236dbfea21aca1b6ac" title="Evaluates  and writes result into A .">dfdx_cond</a> ( <a class="code" href="classbdm_1_1Kalman.html#fa172078091e45561343fa513dd573b0" title="cache of est.mu">_mu</a>,zeros ( <a class="code" href="classbdm_1_1Kalman.html#c5136ef617f6ac0e426bea222755d92b" title="cache of rvu.count()">dimu</a> ),<a class="code" href="classbdm_1_1Kalman.html#0a2072e2090c10fac74ad30a023a4ace" title="Matrix A.">A</a>,<span class="keyword">true</span> ); 
     295<a name="l00357"></a>00357 <span class="comment">//      pfxu-&gt;dfdu_cond ( *_mu,zeros ( dimu ),B,true );</span> 
     296<a name="l00358"></a>00358         <a class="code" href="classbdm_1_1Kalman.html#5977b2c81857948a35105f0e7840203c" title="Matrix B.">B</a>.clear(); 
     297<a name="l00359"></a>00359         phxu-&gt;<a class="code" href="classbdm_1_1diffbifn.html#651184f808a35f236dbfea21aca1b6ac" title="Evaluates  and writes result into A .">dfdx_cond</a> ( <a class="code" href="classbdm_1_1Kalman.html#fa172078091e45561343fa513dd573b0" title="cache of est.mu">_mu</a>,zeros ( <a class="code" href="classbdm_1_1Kalman.html#c5136ef617f6ac0e426bea222755d92b" title="cache of rvu.count()">dimu</a> ),<a class="code" href="classbdm_1_1Kalman.html#818eba63a23972786a4579ad30294177" title="Matrix C.">C</a>,<span class="keyword">true</span> ); 
     298<a name="l00360"></a>00360 <span class="comment">//      phxu-&gt;dfdu_cond ( *_mu,zeros ( dimu ),D,true );</span> 
     299<a name="l00361"></a>00361         <a class="code" href="classbdm_1_1Kalman.html#7b56ac423d0654b5755e4f852a870456" title="Matrix D.">D</a>.clear(); 
     300<a name="l00362"></a>00362  
     301<a name="l00363"></a>00363         <a class="code" href="classbdm_1_1Kalman.html#475b088287cdfbba4dc60a3d027728b7" title="Matrix R in square-root form.">R</a> = R0; 
     302<a name="l00364"></a>00364         <a class="code" href="classbdm_1_1Kalman.html#70f8bf19e81b532c60fd3a7a152425ee" title="Matrix Q in square-root form.">Q</a> = Q0; 
     303<a name="l00365"></a>00365 } 
     304<a name="l00366"></a>00366  
     305<a name="l00367"></a>00367 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt; 
     306<a name="l00368"></a><a class="code" href="classbdm_1_1EKF.html#3fb182ecc29b10ca1163cecbf3bcccfa">00368</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1EKF.html" title="Extended Kalman Filter.">EKF&lt;sq_T&gt;::bayes</a> ( <span class="keyword">const</span> vec &amp;dt ) { 
     307<a name="l00369"></a>00369         it_assert_debug ( dt.length() == ( <a class="code" href="classbdm_1_1Kalman.html#d2c36ba01760bf207b985bf321b7817f" title="cache of rvy.count()">dimy</a>+<a class="code" href="classbdm_1_1Kalman.html#c5136ef617f6ac0e426bea222755d92b" title="cache of rvu.count()">dimu</a> ),<span class="stringliteral">"KalmanFull::bayes wrong size of dt"</span> ); 
     308<a name="l00370"></a>00370  
     309<a name="l00371"></a>00371         sq_T iRy(<a class="code" href="classbdm_1_1Kalman.html#d2c36ba01760bf207b985bf321b7817f" title="cache of rvy.count()">dimy</a>,<a class="code" href="classbdm_1_1Kalman.html#d2c36ba01760bf207b985bf321b7817f" title="cache of rvy.count()">dimy</a>); 
     310<a name="l00372"></a>00372         vec u = dt.get ( <a class="code" href="classbdm_1_1Kalman.html#d2c36ba01760bf207b985bf321b7817f" title="cache of rvy.count()">dimy</a>,<a class="code" href="classbdm_1_1Kalman.html#d2c36ba01760bf207b985bf321b7817f" title="cache of rvy.count()">dimy</a>+<a class="code" href="classbdm_1_1Kalman.html#c5136ef617f6ac0e426bea222755d92b" title="cache of rvu.count()">dimu</a>-1 ); 
     311<a name="l00373"></a>00373         vec y = dt.get ( 0,<a class="code" href="classbdm_1_1Kalman.html#d2c36ba01760bf207b985bf321b7817f" title="cache of rvy.count()">dimy</a>-1 ); 
     312<a name="l00374"></a>00374         <span class="comment">//Time update</span> 
     313<a name="l00375"></a>00375         <a class="code" href="classbdm_1_1Kalman.html#fa172078091e45561343fa513dd573b0" title="cache of est.mu">_mu</a> = pfxu-&gt;<a class="code" href="classbdm_1_1diffbifn.html#188f31066bd72e1bf0ddacd1eb0e6af3" title="Evaluates  (VS: Do we really need common eval? ).">eval</a> ( <a class="code" href="classbdm_1_1Kalman.html#fa172078091e45561343fa513dd573b0" title="cache of est.mu">_mu</a>, u ); 
     314<a name="l00376"></a>00376         pfxu-&gt;<a class="code" href="classbdm_1_1diffbifn.html#651184f808a35f236dbfea21aca1b6ac" title="Evaluates  and writes result into A .">dfdx_cond</a> ( <a class="code" href="classbdm_1_1Kalman.html#fa172078091e45561343fa513dd573b0" title="cache of est.mu">_mu</a>,u,<a class="code" href="classbdm_1_1Kalman.html#0a2072e2090c10fac74ad30a023a4ace" title="Matrix A.">A</a>,<span class="keyword">false</span> ); <span class="comment">//update A by a derivative of fx</span> 
     315<a name="l00377"></a>00377  
     316<a name="l00378"></a>00378         <span class="comment">//P  = A*P*A.transpose() + Q; in sq_T</span> 
     317<a name="l00379"></a>00379         <a class="code" href="classbdm_1_1Kalman.html#00c27b0bf324f0018497921ca23c71ed" title="cache of est.R">_P</a>.<a class="code" href="classfsqmat.html#5530d2756b5d991de755e6121c9a452e" title="Inplace symmetric multiplication by a SQUARE matrix , i.e. .">mult_sym</a> ( <a class="code" href="classbdm_1_1Kalman.html#0a2072e2090c10fac74ad30a023a4ace" title="Matrix A.">A</a> ); 
     318<a name="l00380"></a>00380         <a class="code" href="classbdm_1_1Kalman.html#00c27b0bf324f0018497921ca23c71ed" title="cache of est.R">_P</a> +=<a class="code" href="classbdm_1_1Kalman.html#70f8bf19e81b532c60fd3a7a152425ee" title="Matrix Q in square-root form.">Q</a>; 
     319<a name="l00381"></a>00381  
     320<a name="l00382"></a>00382         <span class="comment">//Data update</span> 
     321<a name="l00383"></a>00383         phxu-&gt;<a class="code" href="classbdm_1_1diffbifn.html#651184f808a35f236dbfea21aca1b6ac" title="Evaluates  and writes result into A .">dfdx_cond</a> ( <a class="code" href="classbdm_1_1Kalman.html#fa172078091e45561343fa513dd573b0" title="cache of est.mu">_mu</a>,u,<a class="code" href="classbdm_1_1Kalman.html#818eba63a23972786a4579ad30294177" title="Matrix C.">C</a>,<span class="keyword">false</span> ); <span class="comment">//update C by a derivative hx</span> 
     322<a name="l00384"></a>00384         <span class="comment">//_Ry = C*P*C.transpose() + R; in sq_T</span> 
     323<a name="l00385"></a>00385         <a class="code" href="classbdm_1_1Kalman.html#00c27b0bf324f0018497921ca23c71ed" title="cache of est.R">_P</a>.<a class="code" href="classfsqmat.html#5530d2756b5d991de755e6121c9a452e" title="Inplace symmetric multiplication by a SQUARE matrix , i.e. .">mult_sym</a> ( <a class="code" href="classbdm_1_1Kalman.html#818eba63a23972786a4579ad30294177" title="Matrix C.">C</a>, <a class="code" href="classbdm_1_1Kalman.html#2dd268f2d7fbe6382cb8825a1114192a" title="cache of fy.R">_Ry</a> ); 
     324<a name="l00386"></a>00386         ( <a class="code" href="classbdm_1_1Kalman.html#2dd268f2d7fbe6382cb8825a1114192a" title="cache of fy.R">_Ry</a> ) +=<a class="code" href="classbdm_1_1Kalman.html#475b088287cdfbba4dc60a3d027728b7" title="Matrix R in square-root form.">R</a>; 
     325<a name="l00387"></a>00387  
     326<a name="l00388"></a>00388         mat Pfull = <a class="code" href="classbdm_1_1Kalman.html#00c27b0bf324f0018497921ca23c71ed" title="cache of est.R">_P</a>.<a class="code" href="classfsqmat.html#f54fc955e8e3b43d15afa92124bc24b3" title="Conversion to full matrix.">to_mat</a>(); 
    326327<a name="l00389"></a>00389  
    327 <a name="l00390"></a>00390         mat Pfull = <a class="code" href="classbdm_1_1Kalman.html#00c27b0bf324f0018497921ca23c71ed" title="cache of est.R">_P</a>.<a class="code" href="classfsqmat.html#f54fc955e8e3b43d15afa92124bc24b3" title="Conversion to full matrix.">to_mat</a>(); 
    328 <a name="l00391"></a>00391  
    329 <a name="l00392"></a>00392         <a class="code" href="classbdm_1_1Kalman.html#2dd268f2d7fbe6382cb8825a1114192a" title="cache of fy.R">_Ry</a>.<a class="code" href="classfsqmat.html#9fa853e1ca28f2a1a1c43377e798ecb1" title="Matrix inversion preserving the chosen form.">inv</a> ( iRy ); <span class="comment">// result is in _iRy;</span> 
    330 <a name="l00393"></a>00393         <a class="code" href="classbdm_1_1Kalman.html#bd69dfb802465f22dd84d73a180d5c92" title="placeholder for Kalman gain">_K</a> = Pfull*<a class="code" href="classbdm_1_1Kalman.html#818eba63a23972786a4579ad30294177" title="Matrix C.">C</a>.transpose() * ( iRy.to_mat() ); 
    331 <a name="l00394"></a>00394  
    332 <a name="l00395"></a>00395         sq_T pom ( ( <span class="keywordtype">int</span> ) Pfull.rows() ); 
    333 <a name="l00396"></a>00396         iRy.mult_sym_t ( <a class="code" href="classbdm_1_1Kalman.html#818eba63a23972786a4579ad30294177" title="Matrix C.">C</a>*Pfull,pom ); 
    334 <a name="l00397"></a>00397         (<a class="code" href="classbdm_1_1Kalman.html#00c27b0bf324f0018497921ca23c71ed" title="cache of est.R">_P</a> ) -= pom; <span class="comment">// P = P -PC'iRy*CP;</span> 
    335 <a name="l00398"></a>00398         <a class="code" href="classbdm_1_1Kalman.html#c249d45258c8578b13858ad3e7b729b1" title="cache of fy.mu">_yp</a> = phxu-&gt;<a class="code" href="classbdm_1_1diffbifn.html#188f31066bd72e1bf0ddacd1eb0e6af3" title="Evaluates  (VS: Do we really need common eval? ).">eval</a> ( <a class="code" href="classbdm_1_1Kalman.html#fa172078091e45561343fa513dd573b0" title="cache of est.mu">_mu</a>,u ); <span class="comment">//y prediction</span> 
    336 <a name="l00399"></a>00399         ( <a class="code" href="classbdm_1_1Kalman.html#fa172078091e45561343fa513dd573b0" title="cache of est.mu">_mu</a> ) += <a class="code" href="classbdm_1_1Kalman.html#bd69dfb802465f22dd84d73a180d5c92" title="placeholder for Kalman gain">_K</a>* ( y-<a class="code" href="classbdm_1_1Kalman.html#c249d45258c8578b13858ad3e7b729b1" title="cache of fy.mu">_yp</a> ); 
    337 <a name="l00400"></a>00400  
    338 <a name="l00401"></a>00401         <span class="keywordflow">if</span> ( <a class="code" href="classbdm_1_1BM.html#faff0ad12556fe7dc0e2807d4fd938ee" title="If true, the filter will compute likelihood of the data record and store it in ll...">evalll</a>==<span class="keyword">true</span> ) {<a class="code" href="classbdm_1_1BM.html#4064b6559d962633e4372b12f4cd204a" title="Logarithm of marginalized data likelihood.">ll</a>+=<a class="code" href="classbdm_1_1Kalman.html#ba555c394c429f6831c9bbabfa2c944c" title="preditive density on $y_t$">fy</a>.<a class="code" href="classbdm_1_1eEF.html#a36d06ecdd6f4c79dc122510eaccc692" title="Evaluate normalized log-probability.">evallog</a> ( y );} 
    339 <a name="l00402"></a>00402 }; 
    340 <a name="l00403"></a>00403  
    341 <a name="l00404"></a>00404  
    342 <a name="l00405"></a>00405 } 
    343 <a name="l00406"></a>00406 <span class="preprocessor">#endif // KF_H</span> 
    344 <a name="l00407"></a>00407 <span class="preprocessor"></span> 
    345 <a name="l00408"></a>00408  
     328<a name="l00390"></a>00390         <a class="code" href="classbdm_1_1Kalman.html#2dd268f2d7fbe6382cb8825a1114192a" title="cache of fy.R">_Ry</a>.<a class="code" href="classfsqmat.html#9fa853e1ca28f2a1a1c43377e798ecb1" title="Matrix inversion preserving the chosen form.">inv</a> ( iRy ); <span class="comment">// result is in _iRy;</span> 
     329<a name="l00391"></a>00391         <a class="code" href="classbdm_1_1Kalman.html#bd69dfb802465f22dd84d73a180d5c92" title="placeholder for Kalman gain">_K</a> = Pfull*<a class="code" href="classbdm_1_1Kalman.html#818eba63a23972786a4579ad30294177" title="Matrix C.">C</a>.transpose() * ( iRy.to_mat() ); 
     330<a name="l00392"></a>00392  
     331<a name="l00393"></a>00393         sq_T pom ( ( <span class="keywordtype">int</span> ) Pfull.rows() ); 
     332<a name="l00394"></a>00394         iRy.mult_sym_t ( <a class="code" href="classbdm_1_1Kalman.html#818eba63a23972786a4579ad30294177" title="Matrix C.">C</a>*Pfull,pom ); 
     333<a name="l00395"></a>00395         (<a class="code" href="classbdm_1_1Kalman.html#00c27b0bf324f0018497921ca23c71ed" title="cache of est.R">_P</a> ) -= pom; <span class="comment">// P = P -PC'iRy*CP;</span> 
     334<a name="l00396"></a>00396         <a class="code" href="classbdm_1_1Kalman.html#c249d45258c8578b13858ad3e7b729b1" title="cache of fy.mu">_yp</a> = phxu-&gt;<a class="code" href="classbdm_1_1diffbifn.html#188f31066bd72e1bf0ddacd1eb0e6af3" title="Evaluates  (VS: Do we really need common eval? ).">eval</a> ( <a class="code" href="classbdm_1_1Kalman.html#fa172078091e45561343fa513dd573b0" title="cache of est.mu">_mu</a>,u ); <span class="comment">//y prediction</span> 
     335<a name="l00397"></a>00397         ( <a class="code" href="classbdm_1_1Kalman.html#fa172078091e45561343fa513dd573b0" title="cache of est.mu">_mu</a> ) += <a class="code" href="classbdm_1_1Kalman.html#bd69dfb802465f22dd84d73a180d5c92" title="placeholder for Kalman gain">_K</a>* ( y-<a class="code" href="classbdm_1_1Kalman.html#c249d45258c8578b13858ad3e7b729b1" title="cache of fy.mu">_yp</a> ); 
     336<a name="l00398"></a>00398  
     337<a name="l00399"></a>00399         <span class="keywordflow">if</span> ( <a class="code" href="classbdm_1_1BM.html#faff0ad12556fe7dc0e2807d4fd938ee" title="If true, the filter will compute likelihood of the data record and store it in ll...">evalll</a>==<span class="keyword">true</span> ) {<a class="code" href="classbdm_1_1BM.html#4064b6559d962633e4372b12f4cd204a" title="Logarithm of marginalized data likelihood.">ll</a>+=<a class="code" href="classbdm_1_1Kalman.html#ba555c394c429f6831c9bbabfa2c944c" title="preditive density on $y_t$">fy</a>.<a class="code" href="classbdm_1_1eEF.html#a36d06ecdd6f4c79dc122510eaccc692" title="Evaluate normalized log-probability.">evallog</a> ( y );} 
     338<a name="l00400"></a>00400 }; 
     339<a name="l00401"></a>00401  
     340<a name="l00402"></a>00402  
     341<a name="l00403"></a>00403 } 
     342<a name="l00404"></a>00404 <span class="preprocessor">#endif // KF_H</span> 
     343<a name="l00405"></a>00405 <span class="preprocessor"></span> 
     344<a name="l00406"></a>00406  
    346345</pre></div></div> 
    347 <hr size="1"><address style="text-align: right;"><small>Generated on Mon Feb 16 10:06:24 2009 for mixpp by&nbsp; 
     346<hr size="1"><address style="text-align: right;"><small>Generated on Wed Feb 18 17:38:40 2009 for mixpp by&nbsp; 
    348347<a href="http://www.doxygen.org/index.html"> 
    349348<img src="doxygen.png" alt="doxygen" align="middle" border="0"></a> 1.5.6 </small></address>