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  • doc/html/libKF_8h-source.html

    r354 r368  
    7171<a name="l00018"></a>00018 <span class="preprocessor">#include "../stat/libEF.h"</span> 
    7272<a name="l00019"></a>00019 <span class="preprocessor">#include "../math/chmat.h"</span> 
    73 <a name="l00020"></a>00020  
    74 <a name="l00021"></a>00021 <span class="keyword">namespace </span>bdm 
    75 <a name="l00022"></a>00022 { 
    76 <a name="l00023"></a>00023  
    77 <a name="l00028"></a><a class="code" href="classbdm_1_1KalmanFull.html">00028</a>         <span class="keyword">class </span><a class="code" href="classbdm_1_1KalmanFull.html" title="Basic Kalman filter with full matrices (education purpose only)! Will be deleted...">KalmanFull</a> 
    78 <a name="l00029"></a>00029         { 
    79 <a name="l00030"></a>00030                 <span class="keyword">protected</span>: 
    80 <a name="l00031"></a>00031                         <span class="keywordtype">int</span> dimx, dimy, dimu; 
    81 <a name="l00032"></a>00032                         mat A, B, C, D, R, Q; 
    82 <a name="l00033"></a>00033  
    83 <a name="l00034"></a>00034                         <span class="comment">//cache</span> 
    84 <a name="l00035"></a>00035                         mat _Pp, _Ry, _iRy, _K; 
    85 <a name="l00036"></a>00036                 <span class="keyword">public</span>: 
    86 <a name="l00037"></a>00037                         <span class="comment">//posterior</span> 
    87 <a name="l00039"></a><a class="code" href="classbdm_1_1KalmanFull.html#2defb75e58892615c5f95fd844f3a666">00039</a> <span class="comment"></span>                        vec <a class="code" href="classbdm_1_1KalmanFull.html#2defb75e58892615c5f95fd844f3a666" title="Mean value of the posterior density.">mu</a>; 
    88 <a name="l00041"></a><a class="code" href="classbdm_1_1KalmanFull.html#acacd228e100c3e937de575ad2d7cd9c">00041</a>                         mat <a class="code" href="classbdm_1_1KalmanFull.html#acacd228e100c3e937de575ad2d7cd9c" title="Variance of the posterior density.">P</a>; 
    89 <a name="l00042"></a>00042  
    90 <a name="l00043"></a>00043                         <span class="keywordtype">bool</span> evalll; 
    91 <a name="l00044"></a>00044                         <span class="keywordtype">double</span> ll; 
    92 <a name="l00045"></a>00045                 <span class="keyword">public</span>: 
    93 <a name="l00047"></a>00047                         <a class="code" href="classbdm_1_1KalmanFull.html#bdcc98c8b18c1cbdebdf218ae838fd11" title="For EKFfull;.">KalmanFull</a> ( mat A, mat B, mat C, mat D, mat R, mat Q, mat P0, vec mu0 ); 
    94 <a name="l00049"></a>00049                         <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1KalmanFull.html#081924bc97f453f674bb982b7951d053" title="Here dt = [yt;ut] of appropriate dimensions.">bayes</a> ( <span class="keyword">const</span> vec &amp;dt ); 
    95 <a name="l00051"></a>00051                         <span class="keyword">friend</span> std::ostream &amp;<a class="code" href="classbdm_1_1KalmanFull.html#86ba216243ed95bb46d80d88775d16af" title="print elements of KF">operator&lt;&lt; </a>( std::ostream &amp;os, <span class="keyword">const</span> <a class="code" href="classbdm_1_1KalmanFull.html" title="Basic Kalman filter with full matrices (education purpose only)! Will be deleted...">KalmanFull</a> &amp;kf ); 
    96 <a name="l00053"></a><a class="code" href="classbdm_1_1KalmanFull.html#bdcc98c8b18c1cbdebdf218ae838fd11">00053</a>                         <a class="code" href="classbdm_1_1KalmanFull.html#bdcc98c8b18c1cbdebdf218ae838fd11" title="For EKFfull;.">KalmanFull</a>() {}; 
    97 <a name="l00054"></a>00054         }; 
    98 <a name="l00055"></a>00055  
     73<a name="l00020"></a>00020 <span class="preprocessor">#include "../user_info.h"</span> 
     74<a name="l00021"></a>00021  
     75<a name="l00022"></a>00022 <span class="keyword">namespace </span>bdm 
     76<a name="l00023"></a>00023 { 
     77<a name="l00024"></a>00024  
     78<a name="l00029"></a><a class="code" href="classbdm_1_1KalmanFull.html">00029</a>         <span class="keyword">class </span><a class="code" href="classbdm_1_1KalmanFull.html" title="Basic Kalman filter with full matrices (education purpose only)! Will be deleted...">KalmanFull</a> 
     79<a name="l00030"></a>00030         { 
     80<a name="l00031"></a>00031                 <span class="keyword">protected</span>: 
     81<a name="l00032"></a>00032                         <span class="keywordtype">int</span> dimx, dimy, dimu; 
     82<a name="l00033"></a>00033                         mat A, B, C, D, R, Q; 
     83<a name="l00034"></a>00034  
     84<a name="l00035"></a>00035                         <span class="comment">//cache</span> 
     85<a name="l00036"></a>00036                         mat _Pp, _Ry, _iRy, _K; 
     86<a name="l00037"></a>00037                 <span class="keyword">public</span>: 
     87<a name="l00038"></a>00038                         <span class="comment">//posterior</span> 
     88<a name="l00040"></a><a class="code" href="classbdm_1_1KalmanFull.html#2defb75e58892615c5f95fd844f3a666">00040</a> <span class="comment"></span>                        vec <a class="code" href="classbdm_1_1KalmanFull.html#2defb75e58892615c5f95fd844f3a666" title="Mean value of the posterior density.">mu</a>; 
     89<a name="l00042"></a><a class="code" href="classbdm_1_1KalmanFull.html#acacd228e100c3e937de575ad2d7cd9c">00042</a>                         mat <a class="code" href="classbdm_1_1KalmanFull.html#acacd228e100c3e937de575ad2d7cd9c" title="Variance of the posterior density.">P</a>; 
     90<a name="l00043"></a>00043  
     91<a name="l00044"></a>00044                         <span class="keywordtype">bool</span> evalll; 
     92<a name="l00045"></a>00045                         <span class="keywordtype">double</span> ll; 
     93<a name="l00046"></a>00046                 <span class="keyword">public</span>: 
     94<a name="l00048"></a>00048                         <a class="code" href="classbdm_1_1KalmanFull.html#bdcc98c8b18c1cbdebdf218ae838fd11" title="For EKFfull;.">KalmanFull</a> ( mat A, mat B, mat C, mat D, mat R, mat Q, mat P0, vec mu0 ); 
     95<a name="l00050"></a>00050                         <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1KalmanFull.html#081924bc97f453f674bb982b7951d053" title="Here dt = [yt;ut] of appropriate dimensions.">bayes</a> ( <span class="keyword">const</span> vec &amp;dt ); 
     96<a name="l00052"></a>00052                         <span class="keyword">friend</span> std::ostream &amp;<a class="code" href="classbdm_1_1KalmanFull.html#86ba216243ed95bb46d80d88775d16af" title="print elements of KF">operator&lt;&lt; </a>( std::ostream &amp;os, <span class="keyword">const</span> <a class="code" href="classbdm_1_1KalmanFull.html" title="Basic Kalman filter with full matrices (education purpose only)! Will be deleted...">KalmanFull</a> &amp;kf ); 
     97<a name="l00054"></a><a class="code" href="classbdm_1_1KalmanFull.html#bdcc98c8b18c1cbdebdf218ae838fd11">00054</a>                         <a class="code" href="classbdm_1_1KalmanFull.html#bdcc98c8b18c1cbdebdf218ae838fd11" title="For EKFfull;.">KalmanFull</a>() {}; 
     98<a name="l00055"></a>00055         }; 
    9999<a name="l00056"></a>00056  
    100 <a name="l00064"></a>00064         <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt; 
    101 <a name="l00065"></a>00065  
    102 <a name="l00066"></a><a class="code" href="classbdm_1_1Kalman.html">00066</a>         <span class="keyword">class </span><a class="code" href="classbdm_1_1Kalman.html" title="Kalman filter with covariance matrices in square root form.">Kalman</a> : <span class="keyword">public</span> <a class="code" href="classbdm_1_1BM.html" title="Bayesian Model of a system, i.e. all uncertainty is modeled by probabilities.">BM</a> 
    103 <a name="l00067"></a>00067         { 
    104 <a name="l00068"></a>00068                 <span class="keyword">protected</span>: 
    105 <a name="l00070"></a><a class="code" href="classbdm_1_1Kalman.html#3fe475a1e920b20b63bb342c0e1571f7">00070</a>                         <a class="code" href="classbdm_1_1RV.html" title="Class representing variables, most often random variables.">RV</a> <a class="code" href="classbdm_1_1Kalman.html#3fe475a1e920b20b63bb342c0e1571f7" title="Indetifier of output rv.">rvy</a>; 
    106 <a name="l00072"></a><a class="code" href="classbdm_1_1Kalman.html#149e27424fd1a7cc1c998ea088618a94">00072</a>                         <a class="code" href="classbdm_1_1RV.html" title="Class representing variables, most often random variables.">RV</a> <a class="code" href="classbdm_1_1Kalman.html#149e27424fd1a7cc1c998ea088618a94" title="Indetifier of exogeneous rv.">rvu</a>; 
    107 <a name="l00074"></a><a class="code" href="classbdm_1_1Kalman.html#ba7699cdb3b1382a54d3e28b9b7517fa">00074</a>                         <span class="keywordtype">int</span> <a class="code" href="classbdm_1_1Kalman.html#ba7699cdb3b1382a54d3e28b9b7517fa" title="cache of rv.count()">dimx</a>; 
    108 <a name="l00076"></a><a class="code" href="classbdm_1_1Kalman.html#d2c36ba01760bf207b985bf321b7817f">00076</a>                         <span class="keywordtype">int</span> <a class="code" href="classbdm_1_1Kalman.html#d2c36ba01760bf207b985bf321b7817f" title="cache of rvy.count()">dimy</a>; 
    109 <a name="l00078"></a><a class="code" href="classbdm_1_1Kalman.html#c5136ef617f6ac0e426bea222755d92b">00078</a>                         <span class="keywordtype">int</span> <a class="code" href="classbdm_1_1Kalman.html#c5136ef617f6ac0e426bea222755d92b" title="cache of rvu.count()">dimu</a>; 
    110 <a name="l00080"></a><a class="code" href="classbdm_1_1Kalman.html#0a2072e2090c10fac74ad30a023a4ace">00080</a>                         mat <a class="code" href="classbdm_1_1Kalman.html#0a2072e2090c10fac74ad30a023a4ace" title="Matrix A.">A</a>; 
    111 <a name="l00082"></a><a class="code" href="classbdm_1_1Kalman.html#5977b2c81857948a35105f0e7840203c">00082</a>                         mat <a class="code" href="classbdm_1_1Kalman.html#5977b2c81857948a35105f0e7840203c" title="Matrix B.">B</a>; 
    112 <a name="l00084"></a><a class="code" href="classbdm_1_1Kalman.html#818eba63a23972786a4579ad30294177">00084</a>                         mat <a class="code" href="classbdm_1_1Kalman.html#818eba63a23972786a4579ad30294177" title="Matrix C.">C</a>; 
    113 <a name="l00086"></a><a class="code" href="classbdm_1_1Kalman.html#7b56ac423d0654b5755e4f852a870456">00086</a>                         mat <a class="code" href="classbdm_1_1Kalman.html#7b56ac423d0654b5755e4f852a870456" title="Matrix D.">D</a>; 
    114 <a name="l00088"></a><a class="code" href="classbdm_1_1Kalman.html#70f8bf19e81b532c60fd3a7a152425ee">00088</a>                         sq_T <a class="code" href="classbdm_1_1Kalman.html#70f8bf19e81b532c60fd3a7a152425ee" title="Matrix Q in square-root form.">Q</a>; 
    115 <a name="l00090"></a><a class="code" href="classbdm_1_1Kalman.html#475b088287cdfbba4dc60a3d027728b7">00090</a>                         sq_T <a class="code" href="classbdm_1_1Kalman.html#475b088287cdfbba4dc60a3d027728b7" title="Matrix R in square-root form.">R</a>; 
    116 <a name="l00091"></a>00091  
    117 <a name="l00093"></a><a class="code" href="classbdm_1_1Kalman.html#383f329ff18bbe219254c8b3b916f40d">00093</a>                         <a class="code" href="classbdm_1_1enorm.html" title="Gaussian density with positive definite (decomposed) covariance matrix.">enorm&lt;sq_T&gt;</a> <a class="code" href="classbdm_1_1Kalman.html#383f329ff18bbe219254c8b3b916f40d" title="posterior density on $x_t$">est</a>; 
    118 <a name="l00095"></a><a class="code" href="classbdm_1_1Kalman.html#ba555c394c429f6831c9bbabfa2c944c">00095</a>                         <a class="code" href="classbdm_1_1enorm.html" title="Gaussian density with positive definite (decomposed) covariance matrix.">enorm&lt;sq_T&gt;</a> <a class="code" href="classbdm_1_1Kalman.html#ba555c394c429f6831c9bbabfa2c944c" title="preditive density on $y_t$">fy</a>; 
    119 <a name="l00096"></a>00096  
    120 <a name="l00098"></a><a class="code" href="classbdm_1_1Kalman.html#bd69dfb802465f22dd84d73a180d5c92">00098</a>                         mat <a class="code" href="classbdm_1_1Kalman.html#bd69dfb802465f22dd84d73a180d5c92" title="placeholder for Kalman gain">_K</a>; 
    121 <a name="l00100"></a><a class="code" href="classbdm_1_1Kalman.html#c249d45258c8578b13858ad3e7b729b1">00100</a>                         vec&amp; <a class="code" href="classbdm_1_1Kalman.html#c249d45258c8578b13858ad3e7b729b1" title="cache of fy.mu">_yp</a>; 
    122 <a name="l00102"></a><a class="code" href="classbdm_1_1Kalman.html#2dd268f2d7fbe6382cb8825a1114192a">00102</a>                         sq_T&amp; <a class="code" href="classbdm_1_1Kalman.html#2dd268f2d7fbe6382cb8825a1114192a" title="cache of fy.R">_Ry</a>; 
    123 <a name="l00104"></a><a class="code" href="classbdm_1_1Kalman.html#fa172078091e45561343fa513dd573b0">00104</a>                         vec&amp; <a class="code" href="classbdm_1_1Kalman.html#fa172078091e45561343fa513dd573b0" title="cache of est.mu">_mu</a>; 
    124 <a name="l00106"></a><a class="code" href="classbdm_1_1Kalman.html#00c27b0bf324f0018497921ca23c71ed">00106</a>                         sq_T&amp; <a class="code" href="classbdm_1_1Kalman.html#00c27b0bf324f0018497921ca23c71ed" title="cache of est.R">_P</a>; 
    125 <a name="l00107"></a>00107  
    126 <a name="l00108"></a>00108                 <span class="keyword">public</span>: 
    127 <a name="l00110"></a>00110                         <a class="code" href="classbdm_1_1Kalman.html#025a0196cbcc2e6adb13311f9d3d52b4" title="Default constructor.">Kalman</a> ( ); 
    128 <a name="l00112"></a>00112                         <a class="code" href="classbdm_1_1Kalman.html#025a0196cbcc2e6adb13311f9d3d52b4" title="Default constructor.">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 ); 
    129 <a name="l00114"></a>00114                         <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1Kalman.html#3c7fb87fb6b87d08deb6a5a7862da957" title="Set parameters with check of relevance.">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 ); 
    130 <a name="l00116"></a><a class="code" href="classbdm_1_1Kalman.html#9264fc6b173ecb803d2684b883f32c68">00116</a>                         <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1Kalman.html#9264fc6b173ecb803d2684b883f32c68" title="Set estimate values, used e.g. in initialization.">set_est</a> ( <span class="keyword">const</span> vec &amp;mu0, <span class="keyword">const</span> sq_T &amp;P0 ) 
    131 <a name="l00117"></a>00117                         { 
    132 <a name="l00118"></a>00118                                 sq_T pom ( <a class="code" href="classbdm_1_1Kalman.html#d2c36ba01760bf207b985bf321b7817f" title="cache of rvy.count()">dimy</a> ); 
    133 <a name="l00119"></a>00119                                 <a class="code" href="classbdm_1_1Kalman.html#383f329ff18bbe219254c8b3b916f40d" title="posterior density on $x_t$">est</a>.set_parameters ( mu0,P0 ); 
    134 <a name="l00120"></a>00120                                 P0.mult_sym ( <a class="code" href="classbdm_1_1Kalman.html#818eba63a23972786a4579ad30294177" title="Matrix C.">C</a>,pom ); 
    135 <a name="l00121"></a>00121                                 <a class="code" href="classbdm_1_1Kalman.html#ba555c394c429f6831c9bbabfa2c944c" title="preditive density on $y_t$">fy</a>.set_parameters ( <a class="code" href="classbdm_1_1Kalman.html#818eba63a23972786a4579ad30294177" title="Matrix C.">C</a>*mu0, pom ); 
    136 <a name="l00122"></a>00122                         }; 
    137 <a name="l00123"></a>00123  
    138 <a name="l00125"></a>00125                         <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1Kalman.html#4a39330c14eff8d13179e868a1d1aa8c" title="Here dt = [yt;ut] of appropriate dimensions.">bayes</a> ( <span class="keyword">const</span> vec &amp;dt ); 
    139 <a name="l00127"></a><a class="code" href="classbdm_1_1Kalman.html#f75e487ff6c129d7012d702030f8c890">00127</a>                         <span class="keyword">const</span> <a class="code" href="classbdm_1_1epdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a>&amp; <a class="code" href="classbdm_1_1Kalman.html#f75e487ff6c129d7012d702030f8c890" title="access function">posterior</a>()<span class="keyword"> const </span>{<span class="keywordflow">return</span> <a class="code" href="classbdm_1_1Kalman.html#383f329ff18bbe219254c8b3b916f40d" title="posterior density on $x_t$">est</a>;} 
    140 <a name="l00128"></a>00128                         <span class="keyword">const</span> <a class="code" href="classbdm_1_1enorm.html" title="Gaussian density with positive definite (decomposed) covariance matrix.">enorm&lt;sq_T&gt;</a>* _e()<span class="keyword"> const </span>{<span class="keywordflow">return</span> &amp;<a class="code" href="classbdm_1_1Kalman.html#383f329ff18bbe219254c8b3b916f40d" title="posterior density on $x_t$">est</a>;} 
    141 <a name="l00130"></a><a class="code" href="classbdm_1_1Kalman.html#c788ec6e6c6f5f5861ae8a56d8ede277">00130</a>                         mat&amp; <a class="code" href="classbdm_1_1Kalman.html#c788ec6e6c6f5f5861ae8a56d8ede277" title="access function">__K</a>() {<span class="keywordflow">return</span> <a class="code" href="classbdm_1_1Kalman.html#bd69dfb802465f22dd84d73a180d5c92" title="placeholder for Kalman gain">_K</a>;} 
    142 <a name="l00132"></a><a class="code" href="classbdm_1_1Kalman.html#a250d1dbe7bba861dba2a324520cfa48">00132</a>                         vec <a class="code" href="classbdm_1_1Kalman.html#a250d1dbe7bba861dba2a324520cfa48" title="access function">_dP</a>() {<span class="keywordflow">return</span> <a class="code" href="classbdm_1_1Kalman.html#00c27b0bf324f0018497921ca23c71ed" title="cache of est.R">_P</a>-&gt;getD();} 
    143 <a name="l00133"></a>00133         }; 
    144 <a name="l00134"></a>00134  
    145 <a name="l00141"></a><a class="code" href="classbdm_1_1KalmanCh.html">00141</a>         <span class="keyword">class </span><a class="code" href="classbdm_1_1KalmanCh.html" title="Kalman filter in square root form.">KalmanCh</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;chmat&gt; 
    146 <a name="l00142"></a>00142         { 
    147 <a name="l00143"></a>00143                 <span class="keyword">protected</span>: 
    148 <a name="l00145"></a><a class="code" href="classbdm_1_1KalmanCh.html#48611c8582706cfa62e832be0972e75d">00145</a>                         mat <a class="code" href="classbdm_1_1KalmanCh.html#48611c8582706cfa62e832be0972e75d" title="pre array (triangular matrix)">preA</a>; 
    149 <a name="l00147"></a><a class="code" href="classbdm_1_1KalmanCh.html#bcbd68f51d4b57246e7784ca5900171f">00147</a>                         mat <a class="code" href="classbdm_1_1KalmanCh.html#bcbd68f51d4b57246e7784ca5900171f" title="post array (triangular matrix)">postA</a>; 
    150 <a name="l00148"></a>00148  
    151 <a name="l00149"></a>00149                 <span class="keyword">public</span>: 
    152 <a name="l00151"></a><a class="code" href="classbdm_1_1KalmanCh.html#24ce65bdaa538d4d5153d709a929b996">00151</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>* <a class="code" href="classbdm_1_1KalmanCh.html#24ce65bdaa538d4d5153d709a929b996" title="copy constructor">_copy_</a>()<span class="keyword"> const</span> 
    153 <a name="l00152"></a>00152 <span class="keyword">                        </span>{ 
    154 <a name="l00153"></a>00153                                 <a class="code" href="classbdm_1_1KalmanCh.html" title="Kalman filter in square root form.">KalmanCh</a>* K=<span class="keyword">new</span> <a class="code" href="classbdm_1_1KalmanCh.html" title="Kalman filter in square root form.">KalmanCh</a>; 
    155 <a name="l00154"></a>00154                                 K-&gt;<a class="code" href="classbdm_1_1KalmanCh.html#20a4d4c664e8ac8a3f1bb7b0d11c6d87" title="Set parameters with check of relevance.">set_parameters</a> ( <a class="code" href="classbdm_1_1Kalman.html#0a2072e2090c10fac74ad30a023a4ace" title="Matrix A.">A</a>,<a class="code" href="classbdm_1_1Kalman.html#5977b2c81857948a35105f0e7840203c" title="Matrix B.">B</a>,<a class="code" href="classbdm_1_1Kalman.html#818eba63a23972786a4579ad30294177" title="Matrix C.">C</a>,<a class="code" href="classbdm_1_1Kalman.html#7b56ac423d0654b5755e4f852a870456" title="Matrix D.">D</a>,<a class="code" href="classbdm_1_1Kalman.html#70f8bf19e81b532c60fd3a7a152425ee" title="Matrix Q in square-root form.">Q</a>,<a class="code" href="classbdm_1_1Kalman.html#475b088287cdfbba4dc60a3d027728b7" title="Matrix R in square-root form.">R</a> ); 
    156 <a name="l00155"></a>00155                                 K-&gt;<a class="code" href="classbdm_1_1KalmanCh.html#6e169272657ed101f3d128b49c59b890">set_statistics</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#00c27b0bf324f0018497921ca23c71ed" title="cache of est.R">_P</a> ); 
    157 <a name="l00156"></a>00156                                 <span class="keywordflow">return</span> K; 
    158 <a name="l00157"></a>00157                         } 
    159 <a name="l00159"></a>00159                         <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1KalmanCh.html#20a4d4c664e8ac8a3f1bb7b0d11c6d87" title="Set parameters with check of relevance.">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> <a class="code" href="classchmat.html" title="Symmetric matrix stored in square root decomposition using upper cholesky.">chmat</a> &amp;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> &amp;R0 ); 
    160 <a name="l00160"></a>00160                         <span class="keywordtype">void</span> set_statistics ( <span class="keyword">const</span> vec &amp;mu0, <span class="keyword">const</span> <a class="code" href="classchmat.html" title="Symmetric matrix stored in square root decomposition using upper cholesky.">chmat</a> &amp;P0 ) 
    161 <a name="l00161"></a>00161                         { 
    162 <a name="l00162"></a>00162                                 <a class="code" href="classbdm_1_1Kalman.html#383f329ff18bbe219254c8b3b916f40d" title="posterior density on $x_t$">est</a>.<a class="code" href="classbdm_1_1enorm.html#b8322f2c11560871dd922c660f4771bb">set_parameters</a> ( mu0,P0 ); 
    163 <a name="l00163"></a>00163                         }; 
    164 <a name="l00164"></a>00164  
     100<a name="l00057"></a>00057  
     101<a name="l00065"></a>00065         <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt; 
     102<a name="l00066"></a>00066  
     103<a name="l00067"></a><a class="code" href="classbdm_1_1Kalman.html">00067</a>         <span class="keyword">class </span><a class="code" href="classbdm_1_1Kalman.html" title="Kalman filter with covariance matrices in square root form.">Kalman</a> : <span class="keyword">public</span> <a class="code" href="classbdm_1_1BM.html" title="Bayesian Model of a system, i.e. all uncertainty is modeled by probabilities.">BM</a> 
     104<a name="l00068"></a>00068         { 
     105<a name="l00069"></a>00069                 <span class="keyword">protected</span>: 
     106<a name="l00071"></a><a class="code" href="classbdm_1_1Kalman.html#3fe475a1e920b20b63bb342c0e1571f7">00071</a>                         <a class="code" href="classbdm_1_1RV.html" title="Class representing variables, most often random variables.">RV</a> <a class="code" href="classbdm_1_1Kalman.html#3fe475a1e920b20b63bb342c0e1571f7" title="Indetifier of output rv.">rvy</a>; 
     107<a name="l00073"></a><a class="code" href="classbdm_1_1Kalman.html#149e27424fd1a7cc1c998ea088618a94">00073</a>                         <a class="code" href="classbdm_1_1RV.html" title="Class representing variables, most often random variables.">RV</a> <a class="code" href="classbdm_1_1Kalman.html#149e27424fd1a7cc1c998ea088618a94" title="Indetifier of exogeneous rv.">rvu</a>; 
     108<a name="l00075"></a><a class="code" href="classbdm_1_1Kalman.html#ba7699cdb3b1382a54d3e28b9b7517fa">00075</a>                         <span class="keywordtype">int</span> <a class="code" href="classbdm_1_1Kalman.html#ba7699cdb3b1382a54d3e28b9b7517fa" title="cache of rv.count()">dimx</a>; 
     109<a name="l00077"></a><a class="code" href="classbdm_1_1Kalman.html#d2c36ba01760bf207b985bf321b7817f">00077</a>                         <span class="keywordtype">int</span> <a class="code" href="classbdm_1_1Kalman.html#d2c36ba01760bf207b985bf321b7817f" title="cache of rvy.count()">dimy</a>; 
     110<a name="l00079"></a><a class="code" href="classbdm_1_1Kalman.html#c5136ef617f6ac0e426bea222755d92b">00079</a>                         <span class="keywordtype">int</span> <a class="code" href="classbdm_1_1Kalman.html#c5136ef617f6ac0e426bea222755d92b" title="cache of rvu.count()">dimu</a>; 
     111<a name="l00081"></a><a class="code" href="classbdm_1_1Kalman.html#0a2072e2090c10fac74ad30a023a4ace">00081</a>                         mat <a class="code" href="classbdm_1_1Kalman.html#0a2072e2090c10fac74ad30a023a4ace" title="Matrix A.">A</a>; 
     112<a name="l00083"></a><a class="code" href="classbdm_1_1Kalman.html#5977b2c81857948a35105f0e7840203c">00083</a>                         mat <a class="code" href="classbdm_1_1Kalman.html#5977b2c81857948a35105f0e7840203c" title="Matrix B.">B</a>; 
     113<a name="l00085"></a><a class="code" href="classbdm_1_1Kalman.html#818eba63a23972786a4579ad30294177">00085</a>                         mat <a class="code" href="classbdm_1_1Kalman.html#818eba63a23972786a4579ad30294177" title="Matrix C.">C</a>; 
     114<a name="l00087"></a><a class="code" href="classbdm_1_1Kalman.html#7b56ac423d0654b5755e4f852a870456">00087</a>                         mat <a class="code" href="classbdm_1_1Kalman.html#7b56ac423d0654b5755e4f852a870456" title="Matrix D.">D</a>; 
     115<a name="l00089"></a><a class="code" href="classbdm_1_1Kalman.html#70f8bf19e81b532c60fd3a7a152425ee">00089</a>                         sq_T <a class="code" href="classbdm_1_1Kalman.html#70f8bf19e81b532c60fd3a7a152425ee" title="Matrix Q in square-root form.">Q</a>; 
     116<a name="l00091"></a><a class="code" href="classbdm_1_1Kalman.html#475b088287cdfbba4dc60a3d027728b7">00091</a>                         sq_T <a class="code" href="classbdm_1_1Kalman.html#475b088287cdfbba4dc60a3d027728b7" title="Matrix R in square-root form.">R</a>; 
     117<a name="l00092"></a>00092  
     118<a name="l00094"></a><a class="code" href="classbdm_1_1Kalman.html#383f329ff18bbe219254c8b3b916f40d">00094</a>                         <a class="code" href="classbdm_1_1enorm.html" title="Gaussian density with positive definite (decomposed) covariance matrix.">enorm&lt;sq_T&gt;</a> <a class="code" href="classbdm_1_1Kalman.html#383f329ff18bbe219254c8b3b916f40d" title="posterior density on $x_t$">est</a>; 
     119<a name="l00096"></a><a class="code" href="classbdm_1_1Kalman.html#ba555c394c429f6831c9bbabfa2c944c">00096</a>                         <a class="code" href="classbdm_1_1enorm.html" title="Gaussian density with positive definite (decomposed) covariance matrix.">enorm&lt;sq_T&gt;</a> <a class="code" href="classbdm_1_1Kalman.html#ba555c394c429f6831c9bbabfa2c944c" title="preditive density on $y_t$">fy</a>; 
     120<a name="l00097"></a>00097  
     121<a name="l00099"></a><a class="code" href="classbdm_1_1Kalman.html#bd69dfb802465f22dd84d73a180d5c92">00099</a>                         mat <a class="code" href="classbdm_1_1Kalman.html#bd69dfb802465f22dd84d73a180d5c92" title="placeholder for Kalman gain">_K</a>; 
     122<a name="l00101"></a><a class="code" href="classbdm_1_1Kalman.html#c249d45258c8578b13858ad3e7b729b1">00101</a>                         vec&amp; <a class="code" href="classbdm_1_1Kalman.html#c249d45258c8578b13858ad3e7b729b1" title="cache of fy.mu">_yp</a>; 
     123<a name="l00103"></a><a class="code" href="classbdm_1_1Kalman.html#2dd268f2d7fbe6382cb8825a1114192a">00103</a>                         sq_T&amp; <a class="code" href="classbdm_1_1Kalman.html#2dd268f2d7fbe6382cb8825a1114192a" title="cache of fy.R">_Ry</a>; 
     124<a name="l00105"></a><a class="code" href="classbdm_1_1Kalman.html#fa172078091e45561343fa513dd573b0">00105</a>                         vec&amp; <a class="code" href="classbdm_1_1Kalman.html#fa172078091e45561343fa513dd573b0" title="cache of est.mu">_mu</a>; 
     125<a name="l00107"></a><a class="code" href="classbdm_1_1Kalman.html#00c27b0bf324f0018497921ca23c71ed">00107</a>                         sq_T&amp; <a class="code" href="classbdm_1_1Kalman.html#00c27b0bf324f0018497921ca23c71ed" title="cache of est.R">_P</a>; 
     126<a name="l00108"></a>00108  
     127<a name="l00109"></a>00109                 <span class="keyword">public</span>: 
     128<a name="l00111"></a>00111                         <a class="code" href="classbdm_1_1Kalman.html#025a0196cbcc2e6adb13311f9d3d52b4" title="Default constructor.">Kalman</a> ( ); 
     129<a name="l00113"></a>00113                         <a class="code" href="classbdm_1_1Kalman.html#025a0196cbcc2e6adb13311f9d3d52b4" title="Default constructor.">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 ); 
     130<a name="l00115"></a>00115                         <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1Kalman.html#3c7fb87fb6b87d08deb6a5a7862da957" title="Set parameters with check of relevance.">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 ); 
     131<a name="l00117"></a><a class="code" href="classbdm_1_1Kalman.html#9264fc6b173ecb803d2684b883f32c68">00117</a>                         <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1Kalman.html#9264fc6b173ecb803d2684b883f32c68" title="Set estimate values, used e.g. in initialization.">set_est</a> ( <span class="keyword">const</span> vec &amp;mu0, <span class="keyword">const</span> sq_T &amp;P0 ) 
     132<a name="l00118"></a>00118                         { 
     133<a name="l00119"></a>00119                                 sq_T pom ( <a class="code" href="classbdm_1_1Kalman.html#d2c36ba01760bf207b985bf321b7817f" title="cache of rvy.count()">dimy</a> ); 
     134<a name="l00120"></a>00120                                 <a class="code" href="classbdm_1_1Kalman.html#383f329ff18bbe219254c8b3b916f40d" title="posterior density on $x_t$">est</a>.set_parameters ( mu0,P0 ); 
     135<a name="l00121"></a>00121                                 P0.mult_sym ( <a class="code" href="classbdm_1_1Kalman.html#818eba63a23972786a4579ad30294177" title="Matrix C.">C</a>,pom ); 
     136<a name="l00122"></a>00122                                 <a class="code" href="classbdm_1_1Kalman.html#ba555c394c429f6831c9bbabfa2c944c" title="preditive density on $y_t$">fy</a>.set_parameters ( <a class="code" href="classbdm_1_1Kalman.html#818eba63a23972786a4579ad30294177" title="Matrix C.">C</a>*mu0, pom ); 
     137<a name="l00123"></a>00123                         }; 
     138<a name="l00124"></a>00124  
     139<a name="l00126"></a>00126                         <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1Kalman.html#4a39330c14eff8d13179e868a1d1aa8c" title="Here dt = [yt;ut] of appropriate dimensions.">bayes</a> ( <span class="keyword">const</span> vec &amp;dt ); 
     140<a name="l00128"></a><a class="code" href="classbdm_1_1Kalman.html#f75e487ff6c129d7012d702030f8c890">00128</a>                         <span class="keyword">const</span> <a class="code" href="classbdm_1_1epdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a>&amp; <a class="code" href="classbdm_1_1Kalman.html#f75e487ff6c129d7012d702030f8c890" title="access function">posterior</a>()<span class="keyword"> const </span>{<span class="keywordflow">return</span> <a class="code" href="classbdm_1_1Kalman.html#383f329ff18bbe219254c8b3b916f40d" title="posterior density on $x_t$">est</a>;} 
     141<a name="l00129"></a>00129                         <span class="keyword">const</span> <a class="code" href="classbdm_1_1enorm.html" title="Gaussian density with positive definite (decomposed) covariance matrix.">enorm&lt;sq_T&gt;</a>* _e()<span class="keyword"> const </span>{<span class="keywordflow">return</span> &amp;<a class="code" href="classbdm_1_1Kalman.html#383f329ff18bbe219254c8b3b916f40d" title="posterior density on $x_t$">est</a>;} 
     142<a name="l00131"></a><a class="code" href="classbdm_1_1Kalman.html#c788ec6e6c6f5f5861ae8a56d8ede277">00131</a>                         mat&amp; <a class="code" href="classbdm_1_1Kalman.html#c788ec6e6c6f5f5861ae8a56d8ede277" title="access function">__K</a>() {<span class="keywordflow">return</span> <a class="code" href="classbdm_1_1Kalman.html#bd69dfb802465f22dd84d73a180d5c92" title="placeholder for Kalman gain">_K</a>;} 
     143<a name="l00133"></a><a class="code" href="classbdm_1_1Kalman.html#a250d1dbe7bba861dba2a324520cfa48">00133</a>                         vec <a class="code" href="classbdm_1_1Kalman.html#a250d1dbe7bba861dba2a324520cfa48" title="access function">_dP</a>() {<span class="keywordflow">return</span> <a class="code" href="classbdm_1_1Kalman.html#00c27b0bf324f0018497921ca23c71ed" title="cache of est.R">_P</a>-&gt;getD();} 
     144<a name="l00134"></a>00134         }; 
     145<a name="l00135"></a>00135  
     146<a name="l00142"></a><a class="code" href="classbdm_1_1KalmanCh.html">00142</a>         <span class="keyword">class </span><a class="code" href="classbdm_1_1KalmanCh.html" title="Kalman filter in square root form.">KalmanCh</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;chmat&gt; 
     147<a name="l00143"></a>00143         { 
     148<a name="l00144"></a>00144                 <span class="keyword">protected</span>: 
     149<a name="l00146"></a><a class="code" href="classbdm_1_1KalmanCh.html#48611c8582706cfa62e832be0972e75d">00146</a>                         mat <a class="code" href="classbdm_1_1KalmanCh.html#48611c8582706cfa62e832be0972e75d" title="pre array (triangular matrix)">preA</a>; 
     150<a name="l00148"></a><a class="code" href="classbdm_1_1KalmanCh.html#bcbd68f51d4b57246e7784ca5900171f">00148</a>                         mat <a class="code" href="classbdm_1_1KalmanCh.html#bcbd68f51d4b57246e7784ca5900171f" title="post array (triangular matrix)">postA</a>; 
     151<a name="l00149"></a>00149  
     152<a name="l00150"></a>00150                 <span class="keyword">public</span>: 
     153<a name="l00152"></a><a class="code" href="classbdm_1_1KalmanCh.html#24ce65bdaa538d4d5153d709a929b996">00152</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>* <a class="code" href="classbdm_1_1KalmanCh.html#24ce65bdaa538d4d5153d709a929b996" title="copy constructor">_copy_</a>()<span class="keyword"> const</span> 
     154<a name="l00153"></a>00153 <span class="keyword">                        </span>{ 
     155<a name="l00154"></a>00154                                 <a class="code" href="classbdm_1_1KalmanCh.html" title="Kalman filter in square root form.">KalmanCh</a>* K=<span class="keyword">new</span> <a class="code" href="classbdm_1_1KalmanCh.html" title="Kalman filter in square root form.">KalmanCh</a>; 
     156<a name="l00155"></a>00155                                 K-&gt;<a class="code" href="classbdm_1_1KalmanCh.html#20a4d4c664e8ac8a3f1bb7b0d11c6d87" title="Set parameters with check of relevance.">set_parameters</a> ( <a class="code" href="classbdm_1_1Kalman.html#0a2072e2090c10fac74ad30a023a4ace" title="Matrix A.">A</a>,<a class="code" href="classbdm_1_1Kalman.html#5977b2c81857948a35105f0e7840203c" title="Matrix B.">B</a>,<a class="code" href="classbdm_1_1Kalman.html#818eba63a23972786a4579ad30294177" title="Matrix C.">C</a>,<a class="code" href="classbdm_1_1Kalman.html#7b56ac423d0654b5755e4f852a870456" title="Matrix D.">D</a>,<a class="code" href="classbdm_1_1Kalman.html#70f8bf19e81b532c60fd3a7a152425ee" title="Matrix Q in square-root form.">Q</a>,<a class="code" href="classbdm_1_1Kalman.html#475b088287cdfbba4dc60a3d027728b7" title="Matrix R in square-root form.">R</a> ); 
     157<a name="l00156"></a>00156                                 K-&gt;<a class="code" href="classbdm_1_1KalmanCh.html#6e169272657ed101f3d128b49c59b890">set_statistics</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#00c27b0bf324f0018497921ca23c71ed" title="cache of est.R">_P</a> ); 
     158<a name="l00157"></a>00157                                 <span class="keywordflow">return</span> K; 
     159<a name="l00158"></a>00158                         } 
     160<a name="l00160"></a>00160                         <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1KalmanCh.html#20a4d4c664e8ac8a3f1bb7b0d11c6d87" title="Set parameters with check of relevance.">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> <a class="code" href="classchmat.html" title="Symmetric matrix stored in square root decomposition using upper cholesky.">chmat</a> &amp;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> &amp;R0 ); 
     161<a name="l00161"></a>00161                         <span class="keywordtype">void</span> set_statistics ( <span class="keyword">const</span> vec &amp;mu0, <span class="keyword">const</span> <a class="code" href="classchmat.html" title="Symmetric matrix stored in square root decomposition using upper cholesky.">chmat</a> &amp;P0 ) 
     162<a name="l00162"></a>00162                         { 
     163<a name="l00163"></a>00163                                 <a class="code" href="classbdm_1_1Kalman.html#383f329ff18bbe219254c8b3b916f40d" title="posterior density on $x_t$">est</a>.<a class="code" href="classbdm_1_1enorm.html#b8322f2c11560871dd922c660f4771bb">set_parameters</a> ( mu0,P0 ); 
     164<a name="l00164"></a>00164                         }; 
    165165<a name="l00165"></a>00165  
    166 <a name="l00179"></a>00179                         <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1KalmanCh.html#b41fe5540548100b08e1684c3be767b6" title="Here dt = [yt;ut] of appropriate dimensions.">bayes</a> ( <span class="keyword">const</span> vec &amp;dt ); 
    167 <a name="l00180"></a>00180         }; 
    168 <a name="l00181"></a>00181  
    169 <a name="l00187"></a><a class="code" href="classbdm_1_1EKFfull.html">00187</a>         <span class="keyword">class </span><a class="code" href="classbdm_1_1EKFfull.html" title="Extended Kalman Filter in full matrices.">EKFfull</a> : <span class="keyword">public</span> <a class="code" href="classbdm_1_1KalmanFull.html" title="Basic Kalman filter with full matrices (education purpose only)! Will be deleted...">KalmanFull</a>, <span class="keyword">public</span> <a class="code" href="classbdm_1_1BM.html" title="Bayesian Model of a system, i.e. all uncertainty is modeled by probabilities.">BM</a> 
    170 <a name="l00188"></a>00188         { 
    171 <a name="l00189"></a>00189                 <span class="keyword">protected</span>: 
    172 <a name="l00191"></a><a class="code" href="classbdm_1_1EKFfull.html#016d3ec108a430b1e70cf7d78bb963f4">00191</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_1EKFfull.html#016d3ec108a430b1e70cf7d78bb963f4" title="Internal Model f(x,u).">pfxu</a>; 
    173 <a name="l00193"></a><a class="code" href="classbdm_1_1EKFfull.html#f7cdf9cf74284630b4578a2cb8ba92c7">00193</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_1EKFfull.html#f7cdf9cf74284630b4578a2cb8ba92c7" title="Observation Model h(x,u).">phxu</a>; 
    174 <a name="l00194"></a>00194  
    175 <a name="l00195"></a>00195                         <a class="code" href="classbdm_1_1enorm.html">enorm&lt;fsqmat&gt;</a> E; 
    176 <a name="l00196"></a>00196                 <span class="keyword">public</span>: 
    177 <a name="l00198"></a>00198                         <a class="code" href="classbdm_1_1EKFfull.html#6939c345389abb8b2481457b4cfe1165" title="Default constructor.">EKFfull</a> ( ); 
    178 <a name="l00200"></a>00200                         <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1EKFfull.html#78748da361ba61fef162b0d8956d1743" 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_1EKFfull.html#016d3ec108a430b1e70cf7d78bb963f4" 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_1EKFfull.html#f7cdf9cf74284630b4578a2cb8ba92c7" title="Observation Model h(x,u).">phxu</a>, <span class="keyword">const</span> mat Q0, <span class="keyword">const</span> mat R0 ); 
    179 <a name="l00202"></a>00202                         <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1EKFfull.html#f149ae8e9ce14d9931a7bb2850736699" title="Here dt = [yt;ut] of appropriate dimensions.">bayes</a> ( <span class="keyword">const</span> vec &amp;dt ); 
    180 <a name="l00204"></a><a class="code" href="classbdm_1_1EKFfull.html#1949a9b1496a855cc7c24e619bc52365">00204</a>                         <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1EKFfull.html#1949a9b1496a855cc7c24e619bc52365" title="set estimates">set_statistics</a> ( vec mu0, mat P0 ) {<a class="code" href="classbdm_1_1KalmanFull.html#2defb75e58892615c5f95fd844f3a666" title="Mean value of the posterior density.">mu</a>=mu0;<a class="code" href="classbdm_1_1KalmanFull.html#acacd228e100c3e937de575ad2d7cd9c" title="Variance of the posterior density.">P</a>=P0;}; 
    181 <a name="l00206"></a><a class="code" href="classbdm_1_1EKFfull.html#7e9a69f36a0a0615c9abb806772ef36d">00206</a>                         <span class="keyword">const</span> <a class="code" href="classbdm_1_1epdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a>&amp; <a class="code" href="classbdm_1_1EKFfull.html#7e9a69f36a0a0615c9abb806772ef36d" title="dummy!">posterior</a>()<span class="keyword"> const</span>{<span class="keywordflow">return</span> E;}; 
    182 <a name="l00207"></a>00207                         <span class="keyword">const</span> <a class="code" href="classbdm_1_1enorm.html">enorm&lt;fsqmat&gt;</a>* _e()<span class="keyword"> const</span>{<span class="keywordflow">return</span> &amp;E;}; 
    183 <a name="l00208"></a>00208                         <span class="keyword">const</span> mat _R() {<span class="keywordflow">return</span> <a class="code" href="classbdm_1_1KalmanFull.html#acacd228e100c3e937de575ad2d7cd9c" title="Variance of the posterior density.">P</a>;} 
    184 <a name="l00209"></a>00209         }; 
    185 <a name="l00210"></a>00210  
    186 <a name="l00216"></a>00216         <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt; 
    187 <a name="l00217"></a><a class="code" href="classbdm_1_1EKF.html">00217</a>         <span class="keyword">class </span><a class="code" href="classbdm_1_1EKF.html" title="Extended Kalman Filter.">EKF</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;fsqmat&gt; 
    188 <a name="l00218"></a>00218         { 
    189 <a name="l00220"></a>00220                         <a class="code" href="classbdm_1_1diffbifn.html" title="Class representing a differentiable function of two variables .">diffbifn</a>* pfxu; 
    190 <a name="l00222"></a>00222                         <a class="code" href="classbdm_1_1diffbifn.html" title="Class representing a differentiable function of two variables .">diffbifn</a>* phxu; 
    191 <a name="l00223"></a>00223                 <span class="keyword">public</span>: 
    192 <a name="l00225"></a>00225                         <a class="code" href="classbdm_1_1EKF.html#d087a8bb408d26ac4f5c542746b81059" title="Default constructor.">EKF</a> ( <a class="code" href="classbdm_1_1RV.html" title="Class representing variables, most often random variables.">RV</a> rvx, <a class="code" href="classbdm_1_1RV.html" title="Class representing variables, most often random variables.">RV</a> <a class="code" href="classbdm_1_1Kalman.html#3fe475a1e920b20b63bb342c0e1571f7" title="Indetifier of output rv.">rvy</a>, <a class="code" href="classbdm_1_1RV.html" title="Class representing variables, most often random variables.">RV</a> <a class="code" href="classbdm_1_1Kalman.html#149e27424fd1a7cc1c998ea088618a94" title="Indetifier of exogeneous rv.">rvu</a> ); 
    193 <a name="l00227"></a><a class="code" href="classbdm_1_1EKF.html#fe9b2e227255ad32dc73df316b7318f4">00227</a>                         <a class="code" href="classbdm_1_1EKF.html" title="Extended Kalman Filter.">EKF&lt;sq_T&gt;</a>* <a class="code" href="classbdm_1_1EKF.html#fe9b2e227255ad32dc73df316b7318f4" title="copy constructor">_copy_</a>()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> <span class="keyword">new</span> <a class="code" href="classbdm_1_1EKF.html" title="Extended Kalman Filter.">EKF&lt;sq_T&gt;</a> ( this ); } 
    194 <a name="l00229"></a>00229                         <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1EKF.html#00fec1a0a6a467eb83fb36c65eba7bcb" 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>* pfxu, <a class="code" href="classbdm_1_1diffbifn.html" title="Class representing a differentiable function of two variables .">diffbifn</a>* phxu, <span class="keyword">const</span> sq_T Q0, <span class="keyword">const</span> sq_T R0 ); 
    195 <a name="l00231"></a>00231                         <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1EKF.html#3fb182ecc29b10ca1163cecbf3bcccfa" title="Here dt = [yt;ut] of appropriate dimensions.">bayes</a> ( <span class="keyword">const</span> vec &amp;dt ); 
    196 <a name="l00232"></a>00232         }; 
    197 <a name="l00233"></a>00233  
    198 <a name="l00240"></a><a class="code" href="classbdm_1_1EKFCh.html">00240</a>         <span class="keyword">class </span><a class="code" href="classbdm_1_1EKFCh.html" title="Extended Kalman Filter in Square root.">EKFCh</a> : <span class="keyword">public</span> <a class="code" href="classbdm_1_1KalmanCh.html" title="Kalman filter in square root form.">KalmanCh</a> 
    199 <a name="l00241"></a>00241         { 
    200 <a name="l00242"></a>00242                 <span class="keyword">protected</span>: 
    201 <a name="l00244"></a><a class="code" href="classbdm_1_1EKFCh.html#e1e895f994398a55bc425551fc275ba3">00244</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>; 
    202 <a name="l00246"></a><a class="code" href="classbdm_1_1EKFCh.html#6b34c69641826322467b704e8252f317">00246</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>; 
    203 <a name="l00247"></a>00247                 <span class="keyword">public</span>: 
    204 <a name="l00249"></a><a class="code" href="classbdm_1_1EKFCh.html#1d1d91400e3f177de9fe7962ea17adc4">00249</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>* <a class="code" href="classbdm_1_1EKFCh.html#1d1d91400e3f177de9fe7962ea17adc4" title="copy constructor duplicated - calls different set_parameters">_copy_</a>()<span class="keyword"> const</span> 
    205 <a name="l00250"></a>00250 <span class="keyword">                        </span>{ 
    206 <a name="l00251"></a>00251                                 <a class="code" href="classbdm_1_1EKFCh.html" title="Extended Kalman Filter in Square root.">EKFCh</a>* E=<span class="keyword">new</span> <a class="code" href="classbdm_1_1EKFCh.html" title="Extended Kalman Filter in Square root.">EKFCh</a>; 
    207 <a name="l00252"></a>00252                                 E-&gt;<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_1EKFCh.html#e1e895f994398a55bc425551fc275ba3" title="Internal Model f(x,u).">pfxu</a>,<a class="code" href="classbdm_1_1EKFCh.html#6b34c69641826322467b704e8252f317" title="Observation Model h(x,u).">phxu</a>,<a class="code" href="classbdm_1_1Kalman.html#70f8bf19e81b532c60fd3a7a152425ee" title="Matrix Q in square-root form.">Q</a>,<a class="code" href="classbdm_1_1Kalman.html#475b088287cdfbba4dc60a3d027728b7" title="Matrix R in square-root form.">R</a> ); 
    208 <a name="l00253"></a>00253                                 E-&gt;<a class="code" href="classbdm_1_1KalmanCh.html#6e169272657ed101f3d128b49c59b890">set_statistics</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#00c27b0bf324f0018497921ca23c71ed" title="cache of est.R">_P</a> ); 
    209 <a name="l00254"></a>00254                                 <span class="keywordflow">return</span> E; 
    210 <a name="l00255"></a>00255                         } 
    211 <a name="l00257"></a>00257                         <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 ); 
    212 <a name="l00259"></a>00259                         <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 ); 
    213 <a name="l00260"></a>00260         }; 
     166<a name="l00166"></a>00166  
     167<a name="l00180"></a>00180                         <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1KalmanCh.html#b41fe5540548100b08e1684c3be767b6" title="Here dt = [yt;ut] of appropriate dimensions.">bayes</a> ( <span class="keyword">const</span> vec &amp;dt ); 
     168<a name="l00181"></a>00181         }; 
     169<a name="l00182"></a>00182  
     170<a name="l00188"></a><a class="code" href="classbdm_1_1EKFfull.html">00188</a>         <span class="keyword">class </span><a class="code" href="classbdm_1_1EKFfull.html" title="Extended Kalman Filter in full matrices.">EKFfull</a> : <span class="keyword">public</span> <a class="code" href="classbdm_1_1KalmanFull.html" title="Basic Kalman filter with full matrices (education purpose only)! Will be deleted...">KalmanFull</a>, <span class="keyword">public</span> <a class="code" href="classbdm_1_1BM.html" title="Bayesian Model of a system, i.e. all uncertainty is modeled by probabilities.">BM</a> 
     171<a name="l00189"></a>00189         { 
     172<a name="l00190"></a>00190                 <span class="keyword">protected</span>: 
     173<a name="l00192"></a><a class="code" href="classbdm_1_1EKFfull.html#016d3ec108a430b1e70cf7d78bb963f4">00192</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_1EKFfull.html#016d3ec108a430b1e70cf7d78bb963f4" title="Internal Model f(x,u).">pfxu</a>; 
     174<a name="l00194"></a><a class="code" href="classbdm_1_1EKFfull.html#f7cdf9cf74284630b4578a2cb8ba92c7">00194</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_1EKFfull.html#f7cdf9cf74284630b4578a2cb8ba92c7" title="Observation Model h(x,u).">phxu</a>; 
     175<a name="l00195"></a>00195  
     176<a name="l00196"></a>00196                         <a class="code" href="classbdm_1_1enorm.html">enorm&lt;fsqmat&gt;</a> E; 
     177<a name="l00197"></a>00197                 <span class="keyword">public</span>: 
     178<a name="l00199"></a>00199                         <a class="code" href="classbdm_1_1EKFfull.html#6939c345389abb8b2481457b4cfe1165" title="Default constructor.">EKFfull</a> ( ); 
     179<a name="l00201"></a>00201                         <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1EKFfull.html#78748da361ba61fef162b0d8956d1743" 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_1EKFfull.html#016d3ec108a430b1e70cf7d78bb963f4" 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_1EKFfull.html#f7cdf9cf74284630b4578a2cb8ba92c7" title="Observation Model h(x,u).">phxu</a>, <span class="keyword">const</span> mat Q0, <span class="keyword">const</span> mat R0 ); 
     180<a name="l00203"></a>00203                         <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1EKFfull.html#f149ae8e9ce14d9931a7bb2850736699" title="Here dt = [yt;ut] of appropriate dimensions.">bayes</a> ( <span class="keyword">const</span> vec &amp;dt ); 
     181<a name="l00205"></a><a class="code" href="classbdm_1_1EKFfull.html#1949a9b1496a855cc7c24e619bc52365">00205</a>                         <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1EKFfull.html#1949a9b1496a855cc7c24e619bc52365" title="set estimates">set_statistics</a> ( vec mu0, mat P0 ) {<a class="code" href="classbdm_1_1KalmanFull.html#2defb75e58892615c5f95fd844f3a666" title="Mean value of the posterior density.">mu</a>=mu0;<a class="code" href="classbdm_1_1KalmanFull.html#acacd228e100c3e937de575ad2d7cd9c" title="Variance of the posterior density.">P</a>=P0;}; 
     182<a name="l00207"></a><a class="code" href="classbdm_1_1EKFfull.html#7e9a69f36a0a0615c9abb806772ef36d">00207</a>                         <span class="keyword">const</span> <a class="code" href="classbdm_1_1epdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a>&amp; <a class="code" href="classbdm_1_1EKFfull.html#7e9a69f36a0a0615c9abb806772ef36d" title="dummy!">posterior</a>()<span class="keyword"> const</span>{<span class="keywordflow">return</span> E;}; 
     183<a name="l00208"></a>00208                         <span class="keyword">const</span> <a class="code" href="classbdm_1_1enorm.html">enorm&lt;fsqmat&gt;</a>* _e()<span class="keyword"> const</span>{<span class="keywordflow">return</span> &amp;E;}; 
     184<a name="l00209"></a>00209                         <span class="keyword">const</span> mat _R() {<span class="keywordflow">return</span> <a class="code" href="classbdm_1_1KalmanFull.html#acacd228e100c3e937de575ad2d7cd9c" title="Variance of the posterior density.">P</a>;} 
     185<a name="l00210"></a>00210         }; 
     186<a name="l00211"></a>00211  
     187<a name="l00217"></a>00217         <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt; 
     188<a name="l00218"></a><a class="code" href="classbdm_1_1EKF.html">00218</a>         <span class="keyword">class </span><a class="code" href="classbdm_1_1EKF.html" title="Extended Kalman Filter.">EKF</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;fsqmat&gt; 
     189<a name="l00219"></a>00219         { 
     190<a name="l00221"></a>00221                         <a class="code" href="classbdm_1_1diffbifn.html" title="Class representing a differentiable function of two variables .">diffbifn</a>* pfxu; 
     191<a name="l00223"></a>00223                         <a class="code" href="classbdm_1_1diffbifn.html" title="Class representing a differentiable function of two variables .">diffbifn</a>* phxu; 
     192<a name="l00224"></a>00224                 <span class="keyword">public</span>: 
     193<a name="l00226"></a>00226                         <a class="code" href="classbdm_1_1EKF.html#d087a8bb408d26ac4f5c542746b81059" title="Default constructor.">EKF</a> ( <a class="code" href="classbdm_1_1RV.html" title="Class representing variables, most often random variables.">RV</a> rvx, <a class="code" href="classbdm_1_1RV.html" title="Class representing variables, most often random variables.">RV</a> <a class="code" href="classbdm_1_1Kalman.html#3fe475a1e920b20b63bb342c0e1571f7" title="Indetifier of output rv.">rvy</a>, <a class="code" href="classbdm_1_1RV.html" title="Class representing variables, most often random variables.">RV</a> <a class="code" href="classbdm_1_1Kalman.html#149e27424fd1a7cc1c998ea088618a94" title="Indetifier of exogeneous rv.">rvu</a> ); 
     194<a name="l00228"></a><a class="code" href="classbdm_1_1EKF.html#fe9b2e227255ad32dc73df316b7318f4">00228</a>                         <a class="code" href="classbdm_1_1EKF.html" title="Extended Kalman Filter.">EKF&lt;sq_T&gt;</a>* <a class="code" href="classbdm_1_1EKF.html#fe9b2e227255ad32dc73df316b7318f4" title="copy constructor">_copy_</a>()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> <span class="keyword">new</span> <a class="code" href="classbdm_1_1EKF.html" title="Extended Kalman Filter.">EKF&lt;sq_T&gt;</a> ( this ); } 
     195<a name="l00230"></a>00230                         <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1EKF.html#00fec1a0a6a467eb83fb36c65eba7bcb" 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>* pfxu, <a class="code" href="classbdm_1_1diffbifn.html" title="Class representing a differentiable function of two variables .">diffbifn</a>* phxu, <span class="keyword">const</span> sq_T Q0, <span class="keyword">const</span> sq_T R0 ); 
     196<a name="l00232"></a>00232                         <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1EKF.html#3fb182ecc29b10ca1163cecbf3bcccfa" title="Here dt = [yt;ut] of appropriate dimensions.">bayes</a> ( <span class="keyword">const</span> vec &amp;dt ); 
     197<a name="l00233"></a>00233         }; 
     198<a name="l00234"></a>00234  
     199<a name="l00241"></a><a class="code" href="classbdm_1_1EKFCh.html">00241</a>         <span class="keyword">class </span><a class="code" href="classbdm_1_1EKFCh.html" title="Extended Kalman Filter in Square root.">EKFCh</a> : <span class="keyword">public</span> <a class="code" href="classbdm_1_1KalmanCh.html" title="Kalman filter in square root form.">KalmanCh</a> 
     200<a name="l00242"></a>00242         { 
     201<a name="l00243"></a>00243                 <span class="keyword">protected</span>: 
     202<a name="l00245"></a><a class="code" href="classbdm_1_1EKFCh.html#e1e895f994398a55bc425551fc275ba3">00245</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>; 
     203<a name="l00247"></a><a class="code" href="classbdm_1_1EKFCh.html#6b34c69641826322467b704e8252f317">00247</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>; 
     204<a name="l00248"></a>00248                 <span class="keyword">public</span>: 
     205<a name="l00250"></a><a class="code" href="classbdm_1_1EKFCh.html#1d1d91400e3f177de9fe7962ea17adc4">00250</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>* <a class="code" href="classbdm_1_1EKFCh.html#1d1d91400e3f177de9fe7962ea17adc4" title="copy constructor duplicated - calls different set_parameters">_copy_</a>()<span class="keyword"> const</span> 
     206<a name="l00251"></a>00251 <span class="keyword">                        </span>{ 
     207<a name="l00252"></a>00252                                 <a class="code" href="classbdm_1_1EKFCh.html" title="Extended Kalman Filter in Square root.">EKFCh</a>* E=<span class="keyword">new</span> <a class="code" href="classbdm_1_1EKFCh.html" title="Extended Kalman Filter in Square root.">EKFCh</a>; 
     208<a name="l00253"></a>00253                                 E-&gt;<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_1EKFCh.html#e1e895f994398a55bc425551fc275ba3" title="Internal Model f(x,u).">pfxu</a>,<a class="code" href="classbdm_1_1EKFCh.html#6b34c69641826322467b704e8252f317" title="Observation Model h(x,u).">phxu</a>,<a class="code" href="classbdm_1_1Kalman.html#70f8bf19e81b532c60fd3a7a152425ee" title="Matrix Q in square-root form.">Q</a>,<a class="code" href="classbdm_1_1Kalman.html#475b088287cdfbba4dc60a3d027728b7" title="Matrix R in square-root form.">R</a> ); 
     209<a name="l00254"></a>00254                                 E-&gt;<a class="code" href="classbdm_1_1KalmanCh.html#6e169272657ed101f3d128b49c59b890">set_statistics</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#00c27b0bf324f0018497921ca23c71ed" title="cache of est.R">_P</a> ); 
     210<a name="l00255"></a>00255                                 <span class="keywordflow">return</span> E; 
     211<a name="l00256"></a>00256                         } 
     212<a name="l00258"></a>00258                         <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 ); 
     213<a name="l00260"></a>00260                         <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 ); 
    214214<a name="l00261"></a>00261  
    215 <a name="l00266"></a><a class="code" href="classbdm_1_1KFcondQR.html">00266</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; 
    216 <a name="l00267"></a>00267         { 
    217 <a name="l00268"></a>00268 <span class="comment">//protected:</span> 
    218 <a name="l00269"></a>00269                 <span class="keyword">public</span>: 
    219 <a name="l00270"></a><a class="code" href="classbdm_1_1KFcondQR.html#31bc31087ee7ed6c0bfb92d626321b91">00270</a>                         <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1KFcondQR.html#31bc31087ee7ed6c0bfb92d626321b91" title="Substitute val for rvc.">condition</a> ( <span class="keyword">const</span> vec &amp;QR ) 
    220 <a name="l00271"></a>00271                         { 
    221 <a name="l00272"></a>00272                                 it_assert_debug ( QR.length() == ( <a class="code" href="classbdm_1_1Kalman.html#ba7699cdb3b1382a54d3e28b9b7517fa" title="cache of rv.count()">dimx</a>+<a class="code" href="classbdm_1_1Kalman.html#d2c36ba01760bf207b985bf321b7817f" title="cache of rvy.count()">dimy</a> ),<span class="stringliteral">"KFcondRQ: conditioning by incompatible vector"</span> ); 
    222 <a name="l00273"></a>00273  
    223 <a name="l00274"></a>00274                                 <a class="code" href="classbdm_1_1Kalman.html#70f8bf19e81b532c60fd3a7a152425ee" title="Matrix Q in square-root form.">Q</a>.<a class="code" href="classldmat.html#0884a613b94fde61bfc84288e73ce57f" title="Access functions.">setD</a> ( QR ( 0, <a class="code" href="classbdm_1_1Kalman.html#ba7699cdb3b1382a54d3e28b9b7517fa" title="cache of rv.count()">dimx</a>-1 ) ); 
    224 <a name="l00275"></a>00275                                 <a class="code" href="classbdm_1_1Kalman.html#475b088287cdfbba4dc60a3d027728b7" title="Matrix R in square-root form.">R</a>.<a class="code" href="classldmat.html#0884a613b94fde61bfc84288e73ce57f" title="Access functions.">setD</a> ( QR ( <a class="code" href="classbdm_1_1Kalman.html#ba7699cdb3b1382a54d3e28b9b7517fa" title="cache of rv.count()">dimx</a>, -1 ) ); 
    225 <a name="l00276"></a>00276                         }; 
    226 <a name="l00277"></a>00277         }; 
    227 <a name="l00278"></a>00278  
    228 <a name="l00283"></a><a class="code" href="classbdm_1_1KFcondR.html">00283</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; 
    229 <a name="l00284"></a>00284         { 
    230 <a name="l00285"></a>00285 <span class="comment">//protected:</span> 
    231 <a name="l00286"></a>00286                 <span class="keyword">public</span>: 
    232 <a name="l00288"></a><a class="code" href="classbdm_1_1KFcondR.html#f11639d79f10b1e7dad16a0d8233450d">00288</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; ( ) {}; 
    233 <a name="l00289"></a>00289  
    234 <a name="l00290"></a><a class="code" href="classbdm_1_1KFcondR.html#7d42a421acbdcf9b610a5682ee5fb9a8">00290</a>                         <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1KFcondR.html#7d42a421acbdcf9b610a5682ee5fb9a8" title="Substitute val for rvc.">condition</a> ( <span class="keyword">const</span> vec &amp;R0 ) 
    235 <a name="l00291"></a>00291                         { 
    236 <a name="l00292"></a>00292                                 it_assert_debug ( R0.length() == ( <a class="code" href="classbdm_1_1Kalman.html#d2c36ba01760bf207b985bf321b7817f" title="cache of rvy.count()">dimy</a> ),<span class="stringliteral">"KFcondR: conditioning by incompatible vector"</span> ); 
    237 <a name="l00293"></a>00293  
    238 <a name="l00294"></a>00294                                 <a class="code" href="classbdm_1_1Kalman.html#475b088287cdfbba4dc60a3d027728b7" title="Matrix R in square-root form.">R</a>.<a class="code" href="classldmat.html#0884a613b94fde61bfc84288e73ce57f" title="Access functions.">setD</a> ( R0 ); 
    239 <a name="l00295"></a>00295                         }; 
    240 <a name="l00296"></a>00296  
    241 <a name="l00297"></a>00297         }; 
     215<a name="l00262"></a>00262                         <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1EKFCh.html#0c2d3a9d57f23b998c53d7c12fa2a724" title="This method arrange instance properties according the data stored in the Setting...">from_setting</a>( <span class="keyword">const</span> Setting &amp;root ); 
     216<a name="l00263"></a>00263  
     217<a name="l00264"></a>00264                         <span class="comment">// TODO dodelat void to_setting( Setting &amp;root ) const;</span> 
     218<a name="l00265"></a>00265  
     219<a name="l00266"></a>00266         }; 
     220<a name="l00267"></a>00267  
     221<a name="l00268"></a>00268         UIREGISTER(EKFCh); 
     222<a name="l00269"></a>00269  
     223<a name="l00270"></a>00270  
     224<a name="l00275"></a><a class="code" href="classbdm_1_1KFcondQR.html">00275</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; 
     225<a name="l00276"></a>00276         { 
     226<a name="l00277"></a>00277 <span class="comment">//protected:</span> 
     227<a name="l00278"></a>00278                 <span class="keyword">public</span>: 
     228<a name="l00279"></a><a class="code" href="classbdm_1_1KFcondQR.html#31bc31087ee7ed6c0bfb92d626321b91">00279</a>                         <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1KFcondQR.html#31bc31087ee7ed6c0bfb92d626321b91" title="Substitute val for rvc.">condition</a> ( <span class="keyword">const</span> vec &amp;QR ) 
     229<a name="l00280"></a>00280                         { 
     230<a name="l00281"></a>00281                                 it_assert_debug ( QR.length() == ( <a class="code" href="classbdm_1_1Kalman.html#ba7699cdb3b1382a54d3e28b9b7517fa" title="cache of rv.count()">dimx</a>+<a class="code" href="classbdm_1_1Kalman.html#d2c36ba01760bf207b985bf321b7817f" title="cache of rvy.count()">dimy</a> ),<span class="stringliteral">"KFcondRQ: conditioning by incompatible vector"</span> ); 
     231<a name="l00282"></a>00282  
     232<a name="l00283"></a>00283                                 <a class="code" href="classbdm_1_1Kalman.html#70f8bf19e81b532c60fd3a7a152425ee" title="Matrix Q in square-root form.">Q</a>.<a class="code" href="classldmat.html#0884a613b94fde61bfc84288e73ce57f" title="Access functions.">setD</a> ( QR ( 0, <a class="code" href="classbdm_1_1Kalman.html#ba7699cdb3b1382a54d3e28b9b7517fa" title="cache of rv.count()">dimx</a>-1 ) ); 
     233<a name="l00284"></a>00284                                 <a class="code" href="classbdm_1_1Kalman.html#475b088287cdfbba4dc60a3d027728b7" title="Matrix R in square-root form.">R</a>.<a class="code" href="classldmat.html#0884a613b94fde61bfc84288e73ce57f" title="Access functions.">setD</a> ( QR ( <a class="code" href="classbdm_1_1Kalman.html#ba7699cdb3b1382a54d3e28b9b7517fa" title="cache of rv.count()">dimx</a>, -1 ) ); 
     234<a name="l00285"></a>00285                         }; 
     235<a name="l00286"></a>00286         }; 
     236<a name="l00287"></a>00287  
     237<a name="l00292"></a><a class="code" href="classbdm_1_1KFcondR.html">00292</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; 
     238<a name="l00293"></a>00293         { 
     239<a name="l00294"></a>00294 <span class="comment">//protected:</span> 
     240<a name="l00295"></a>00295                 <span class="keyword">public</span>: 
     241<a name="l00297"></a><a class="code" href="classbdm_1_1KFcondR.html#f11639d79f10b1e7dad16a0d8233450d">00297</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; ( ) {}; 
    242242<a name="l00298"></a>00298  
    243 <a name="l00300"></a>00300  
    244 <a name="l00301"></a>00301         <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt; 
    245 <a name="l00302"></a><a class="code" href="classbdm_1_1Kalman.html#8b22c45cffa949d70b8e5ac92ed5ce25">00302</a>         <a class="code" href="classbdm_1_1Kalman.html#025a0196cbcc2e6adb13311f9d3d52b4" title="Default constructor.">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 ), 
    246 <a name="l00303"></a>00303                         dimx ( K0.dimx ), dimy ( K0.dimy ),dimu ( K0.dimu ), 
    247 <a name="l00304"></a>00304                         A ( K0.A ), B ( K0.B ), C ( K0.C ), D ( K0.D ), 
    248 <a name="l00305"></a>00305                         Q ( K0.Q ), R ( K0.R ), 
    249 <a name="l00306"></a>00306                         est ( K0.est ), fy ( K0.fy ), _yp ( fy._mu() ),_Ry ( fy._R() ), _mu ( est._mu() ), _P ( est._R() ) 
    250 <a name="l00307"></a>00307         { 
    251 <a name="l00308"></a>00308  
    252 <a name="l00309"></a>00309 <span class="comment">// copy values in pointers</span> 
    253 <a name="l00310"></a>00310 <span class="comment">//      _mu = K0._mu;</span> 
    254 <a name="l00311"></a>00311 <span class="comment">//      _P = K0._P;</span> 
    255 <a name="l00312"></a>00312 <span class="comment">//      _yp = K0._yp;</span> 
    256 <a name="l00313"></a>00313 <span class="comment">//      _Ry = K0._Ry;</span> 
    257 <a name="l00314"></a>00314  
    258 <a name="l00315"></a>00315         } 
    259 <a name="l00316"></a>00316  
    260 <a name="l00317"></a>00317         <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt; 
    261 <a name="l00318"></a><a class="code" href="classbdm_1_1Kalman.html#025a0196cbcc2e6adb13311f9d3d52b4">00318</a>         <a class="code" href="classbdm_1_1Kalman.html#025a0196cbcc2e6adb13311f9d3d52b4" title="Default constructor.">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() ) 
    262 <a name="l00319"></a>00319         { 
    263 <a name="l00320"></a>00320         }; 
    264 <a name="l00321"></a>00321  
    265 <a name="l00322"></a>00322         <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt; 
    266 <a name="l00323"></a><a class="code" href="classbdm_1_1Kalman.html#3c7fb87fb6b87d08deb6a5a7862da957">00323</a>         <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1Kalman.html#3c7fb87fb6b87d08deb6a5a7862da957" title="Set parameters with check of relevance.">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 ) 
    267 <a name="l00324"></a>00324         { 
    268 <a name="l00325"></a>00325                 <a class="code" href="classbdm_1_1Kalman.html#ba7699cdb3b1382a54d3e28b9b7517fa" title="cache of rv.count()">dimx</a> = A0.rows(); 
    269 <a name="l00326"></a>00326                 <a class="code" href="classbdm_1_1Kalman.html#d2c36ba01760bf207b985bf321b7817f" title="cache of rvy.count()">dimy</a> = C0.rows(); 
    270 <a name="l00327"></a>00327                 <a class="code" href="classbdm_1_1Kalman.html#c5136ef617f6ac0e426bea222755d92b" title="cache of rvu.count()">dimu</a> = B0.cols(); 
    271 <a name="l00328"></a>00328  
    272 <a name="l00329"></a>00329                 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> ); 
    273 <a name="l00330"></a>00330                 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> ); 
    274 <a name="l00331"></a>00331                 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> ); 
    275 <a name="l00332"></a>00332                 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> ); 
    276 <a name="l00333"></a>00333                 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> ); 
    277 <a name="l00334"></a>00334                 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> ); 
    278 <a name="l00335"></a>00335  
    279 <a name="l00336"></a>00336                 <a class="code" href="classbdm_1_1Kalman.html#0a2072e2090c10fac74ad30a023a4ace" title="Matrix A.">A</a> = A0; 
    280 <a name="l00337"></a>00337                 <a class="code" href="classbdm_1_1Kalman.html#5977b2c81857948a35105f0e7840203c" title="Matrix B.">B</a> = B0; 
    281 <a name="l00338"></a>00338                 <a class="code" href="classbdm_1_1Kalman.html#818eba63a23972786a4579ad30294177" title="Matrix C.">C</a> = C0; 
    282 <a name="l00339"></a>00339                 <a class="code" href="classbdm_1_1Kalman.html#7b56ac423d0654b5755e4f852a870456" title="Matrix D.">D</a> = D0; 
    283 <a name="l00340"></a>00340                 <a class="code" href="classbdm_1_1Kalman.html#475b088287cdfbba4dc60a3d027728b7" title="Matrix R in square-root form.">R</a> = R0; 
    284 <a name="l00341"></a>00341                 <a class="code" href="classbdm_1_1Kalman.html#70f8bf19e81b532c60fd3a7a152425ee" title="Matrix Q in square-root form.">Q</a> = Q0; 
    285 <a name="l00342"></a>00342         } 
    286 <a name="l00343"></a>00343  
    287 <a name="l00344"></a>00344         <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt; 
    288 <a name="l00345"></a><a class="code" href="classbdm_1_1Kalman.html#4a39330c14eff8d13179e868a1d1aa8c">00345</a>         <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1Kalman.html#4a39330c14eff8d13179e868a1d1aa8c" title="Here dt = [yt;ut] of appropriate dimensions.">Kalman&lt;sq_T&gt;::bayes</a> ( <span class="keyword">const</span> vec &amp;dt ) 
    289 <a name="l00346"></a>00346         { 
    290 <a name="l00347"></a>00347                 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> ); 
    291 <a name="l00348"></a>00348  
    292 <a name="l00349"></a>00349                 sq_T iRy ( <a class="code" href="classbdm_1_1Kalman.html#d2c36ba01760bf207b985bf321b7817f" title="cache of rvy.count()">dimy</a> ); 
    293 <a name="l00350"></a>00350                 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 ); 
    294 <a name="l00351"></a>00351                 vec y = dt.get ( 0,<a class="code" href="classbdm_1_1Kalman.html#d2c36ba01760bf207b985bf321b7817f" title="cache of rvy.count()">dimy</a>-1 ); 
    295 <a name="l00352"></a>00352                 <span class="comment">//Time update</span> 
    296 <a name="l00353"></a>00353                 <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; 
    297 <a name="l00354"></a>00354                 <span class="comment">//P  = A*P*A.transpose() + Q; in sq_T</span> 
    298 <a name="l00355"></a>00355                 <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> ); 
    299 <a name="l00356"></a>00356                 <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>; 
     243<a name="l00299"></a><a class="code" href="classbdm_1_1KFcondR.html#7d42a421acbdcf9b610a5682ee5fb9a8">00299</a>                         <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1KFcondR.html#7d42a421acbdcf9b610a5682ee5fb9a8" title="Substitute val for rvc.">condition</a> ( <span class="keyword">const</span> vec &amp;R0 ) 
     244<a name="l00300"></a>00300                         { 
     245<a name="l00301"></a>00301                                 it_assert_debug ( R0.length() == ( <a class="code" href="classbdm_1_1Kalman.html#d2c36ba01760bf207b985bf321b7817f" title="cache of rvy.count()">dimy</a> ),<span class="stringliteral">"KFcondR: conditioning by incompatible vector"</span> ); 
     246<a name="l00302"></a>00302  
     247<a name="l00303"></a>00303                                 <a class="code" href="classbdm_1_1Kalman.html#475b088287cdfbba4dc60a3d027728b7" title="Matrix R in square-root form.">R</a>.<a class="code" href="classldmat.html#0884a613b94fde61bfc84288e73ce57f" title="Access functions.">setD</a> ( R0 ); 
     248<a name="l00304"></a>00304                         }; 
     249<a name="l00305"></a>00305  
     250<a name="l00306"></a>00306         }; 
     251<a name="l00307"></a>00307  
     252<a name="l00309"></a>00309  
     253<a name="l00310"></a>00310         <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt; 
     254<a name="l00311"></a><a class="code" href="classbdm_1_1Kalman.html#8b22c45cffa949d70b8e5ac92ed5ce25">00311</a>         <a class="code" href="classbdm_1_1Kalman.html#025a0196cbcc2e6adb13311f9d3d52b4" title="Default constructor.">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 ), 
     255<a name="l00312"></a>00312                         dimx ( K0.dimx ), dimy ( K0.dimy ),dimu ( K0.dimu ), 
     256<a name="l00313"></a>00313                         A ( K0.A ), B ( K0.B ), C ( K0.C ), D ( K0.D ), 
     257<a name="l00314"></a>00314                         Q ( K0.Q ), R ( K0.R ), 
     258<a name="l00315"></a>00315                         est ( K0.est ), fy ( K0.fy ), _yp ( fy._mu() ),_Ry ( fy._R() ), _mu ( est._mu() ), _P ( est._R() ) 
     259<a name="l00316"></a>00316         { 
     260<a name="l00317"></a>00317  
     261<a name="l00318"></a>00318 <span class="comment">// copy values in pointers</span> 
     262<a name="l00319"></a>00319 <span class="comment">//      _mu = K0._mu;</span> 
     263<a name="l00320"></a>00320 <span class="comment">//      _P = K0._P;</span> 
     264<a name="l00321"></a>00321 <span class="comment">//      _yp = K0._yp;</span> 
     265<a name="l00322"></a>00322 <span class="comment">//      _Ry = K0._Ry;</span> 
     266<a name="l00323"></a>00323  
     267<a name="l00324"></a>00324         } 
     268<a name="l00325"></a>00325  
     269<a name="l00326"></a>00326         <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt; 
     270<a name="l00327"></a><a class="code" href="classbdm_1_1Kalman.html#025a0196cbcc2e6adb13311f9d3d52b4">00327</a>         <a class="code" href="classbdm_1_1Kalman.html#025a0196cbcc2e6adb13311f9d3d52b4" title="Default constructor.">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() ) 
     271<a name="l00328"></a>00328         { 
     272<a name="l00329"></a>00329         }; 
     273<a name="l00330"></a>00330  
     274<a name="l00331"></a>00331         <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt; 
     275<a name="l00332"></a><a class="code" href="classbdm_1_1Kalman.html#3c7fb87fb6b87d08deb6a5a7862da957">00332</a>         <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1Kalman.html#3c7fb87fb6b87d08deb6a5a7862da957" title="Set parameters with check of relevance.">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 ) 
     276<a name="l00333"></a>00333         { 
     277<a name="l00334"></a>00334                 <a class="code" href="classbdm_1_1Kalman.html#ba7699cdb3b1382a54d3e28b9b7517fa" title="cache of rv.count()">dimx</a> = A0.rows(); 
     278<a name="l00335"></a>00335                 <a class="code" href="classbdm_1_1Kalman.html#d2c36ba01760bf207b985bf321b7817f" title="cache of rvy.count()">dimy</a> = C0.rows(); 
     279<a name="l00336"></a>00336                 <a class="code" href="classbdm_1_1Kalman.html#c5136ef617f6ac0e426bea222755d92b" title="cache of rvu.count()">dimu</a> = B0.cols(); 
     280<a name="l00337"></a>00337  
     281<a name="l00338"></a>00338                 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> ); 
     282<a name="l00339"></a>00339                 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> ); 
     283<a name="l00340"></a>00340                 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> ); 
     284<a name="l00341"></a>00341                 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> ); 
     285<a name="l00342"></a>00342                 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> ); 
     286<a name="l00343"></a>00343                 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> ); 
     287<a name="l00344"></a>00344  
     288<a name="l00345"></a>00345                 <a class="code" href="classbdm_1_1Kalman.html#0a2072e2090c10fac74ad30a023a4ace" title="Matrix A.">A</a> = A0; 
     289<a name="l00346"></a>00346                 <a class="code" href="classbdm_1_1Kalman.html#5977b2c81857948a35105f0e7840203c" title="Matrix B.">B</a> = B0; 
     290<a name="l00347"></a>00347                 <a class="code" href="classbdm_1_1Kalman.html#818eba63a23972786a4579ad30294177" title="Matrix C.">C</a> = C0; 
     291<a name="l00348"></a>00348                 <a class="code" href="classbdm_1_1Kalman.html#7b56ac423d0654b5755e4f852a870456" title="Matrix D.">D</a> = D0; 
     292<a name="l00349"></a>00349                 <a class="code" href="classbdm_1_1Kalman.html#475b088287cdfbba4dc60a3d027728b7" title="Matrix R in square-root form.">R</a> = R0; 
     293<a name="l00350"></a>00350                 <a class="code" href="classbdm_1_1Kalman.html#70f8bf19e81b532c60fd3a7a152425ee" title="Matrix Q in square-root form.">Q</a> = Q0; 
     294<a name="l00351"></a>00351         } 
     295<a name="l00352"></a>00352  
     296<a name="l00353"></a>00353         <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt; 
     297<a name="l00354"></a><a class="code" href="classbdm_1_1Kalman.html#4a39330c14eff8d13179e868a1d1aa8c">00354</a>         <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1Kalman.html#4a39330c14eff8d13179e868a1d1aa8c" title="Here dt = [yt;ut] of appropriate dimensions.">Kalman&lt;sq_T&gt;::bayes</a> ( <span class="keyword">const</span> vec &amp;dt ) 
     298<a name="l00355"></a>00355         { 
     299<a name="l00356"></a>00356                 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> ); 
    300300<a name="l00357"></a>00357  
    301 <a name="l00358"></a>00358                 <span class="comment">//Data update</span> 
    302 <a name="l00359"></a>00359                 <span class="comment">//_Ry = C*P*C.transpose() + R; in sq_T</span> 
    303 <a name="l00360"></a>00360                 <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> ); 
    304 <a name="l00361"></a>00361                 <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>; 
    305 <a name="l00362"></a>00362  
    306 <a name="l00363"></a>00363                 mat Pfull = <a class="code" href="classbdm_1_1Kalman.html#00c27b0bf324f0018497921ca23c71ed" title="cache of est.R">_P</a>.to_mat(); 
    307 <a name="l00364"></a>00364  
    308 <a name="l00365"></a>00365                 <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> 
    309 <a name="l00366"></a>00366                 <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() ); 
    310 <a name="l00367"></a>00367  
    311 <a name="l00368"></a>00368                 sq_T pom ( ( <span class="keywordtype">int</span> ) Pfull.rows() ); 
    312 <a name="l00369"></a>00369                 iRy.mult_sym_t ( <a class="code" href="classbdm_1_1Kalman.html#818eba63a23972786a4579ad30294177" title="Matrix C.">C</a>*Pfull,pom ); 
    313 <a name="l00370"></a>00370                 ( <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> 
    314 <a name="l00371"></a>00371                 ( <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> 
    315 <a name="l00372"></a>00372                 ( <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> ); 
     301<a name="l00358"></a>00358                 sq_T iRy ( <a class="code" href="classbdm_1_1Kalman.html#d2c36ba01760bf207b985bf321b7817f" title="cache of rvy.count()">dimy</a> ); 
     302<a name="l00359"></a>00359                 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 ); 
     303<a name="l00360"></a>00360                 vec y = dt.get ( 0,<a class="code" href="classbdm_1_1Kalman.html#d2c36ba01760bf207b985bf321b7817f" title="cache of rvy.count()">dimy</a>-1 ); 
     304<a name="l00361"></a>00361                 <span class="comment">//Time update</span> 
     305<a name="l00362"></a>00362                 <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; 
     306<a name="l00363"></a>00363                 <span class="comment">//P  = A*P*A.transpose() + Q; in sq_T</span> 
     307<a name="l00364"></a>00364                 <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> ); 
     308<a name="l00365"></a>00365                 <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>; 
     309<a name="l00366"></a>00366  
     310<a name="l00367"></a>00367                 <span class="comment">//Data update</span> 
     311<a name="l00368"></a>00368                 <span class="comment">//_Ry = C*P*C.transpose() + R; in sq_T</span> 
     312<a name="l00369"></a>00369                 <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> ); 
     313<a name="l00370"></a>00370                 <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>; 
     314<a name="l00371"></a>00371  
     315<a name="l00372"></a>00372                 mat Pfull = <a class="code" href="classbdm_1_1Kalman.html#00c27b0bf324f0018497921ca23c71ed" title="cache of est.R">_P</a>.to_mat(); 
    316316<a name="l00373"></a>00373  
    317 <a name="l00374"></a>00374  
    318 <a name="l00375"></a>00375                 <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> 
    319 <a name="l00376"></a>00376                 { 
    320 <a name="l00377"></a>00377                         <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 ); 
    321 <a name="l00378"></a>00378                 } 
    322 <a name="l00379"></a>00379  
    323 <a name="l00380"></a>00380 <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> 
    324 <a name="l00381"></a>00381  
    325 <a name="l00382"></a>00382         }; 
     317<a name="l00374"></a>00374                 <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> 
     318<a name="l00375"></a>00375                 <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() ); 
     319<a name="l00376"></a>00376  
     320<a name="l00377"></a>00377                 sq_T pom ( ( <span class="keywordtype">int</span> ) Pfull.rows() ); 
     321<a name="l00378"></a>00378                 iRy.mult_sym_t ( <a class="code" href="classbdm_1_1Kalman.html#818eba63a23972786a4579ad30294177" title="Matrix C.">C</a>*Pfull,pom ); 
     322<a name="l00379"></a>00379                 ( <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> 
     323<a name="l00380"></a>00380                 ( <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> 
     324<a name="l00381"></a>00381                 ( <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> ); 
     325<a name="l00382"></a>00382  
    326326<a name="l00383"></a>00383  
    327 <a name="l00391"></a><a class="code" href="classbdm_1_1MultiModel.html">00391</a>         <span class="keyword">class </span><a class="code" href="classbdm_1_1MultiModel.html" title="(Switching) Multiple Model The model runs several models in parallel and evaluates...">MultiModel</a>: <span class="keyword">public</span> <a class="code" href="classbdm_1_1BM.html" title="Bayesian Model of a system, i.e. all uncertainty is modeled by probabilities.">BM</a> 
    328 <a name="l00392"></a>00392         { 
    329 <a name="l00393"></a>00393                 <span class="keyword">protected</span>: 
    330 <a name="l00395"></a><a class="code" href="classbdm_1_1MultiModel.html#33de5d07ee774070632de8963b5d4c93">00395</a>                         Array&lt;EKFCh*&gt; <a class="code" href="classbdm_1_1MultiModel.html#33de5d07ee774070632de8963b5d4c93" title="List of models between which we switch.">Models</a>; 
    331 <a name="l00397"></a><a class="code" href="classbdm_1_1MultiModel.html#ef85ea61575bffa8beac8040869ee47a">00397</a>                         vec <a class="code" href="classbdm_1_1MultiModel.html#ef85ea61575bffa8beac8040869ee47a" title="vector of model weights">w</a>; 
    332 <a name="l00399"></a><a class="code" href="classbdm_1_1MultiModel.html#7b4012fc2208ce4ddd5c0d1fe69d7634">00399</a>                         vec <a class="code" href="classbdm_1_1MultiModel.html#7b4012fc2208ce4ddd5c0d1fe69d7634" title="cache of model lls">_lls</a>; 
    333 <a name="l00401"></a><a class="code" href="classbdm_1_1MultiModel.html#9b56bcde4664bd53f8995d7ee7ed415c">00401</a>                         <span class="keywordtype">int</span> <a class="code" href="classbdm_1_1MultiModel.html#9b56bcde4664bd53f8995d7ee7ed415c" title="type of switching policy [1=maximum,2=...]">policy</a>; 
    334 <a name="l00403"></a><a class="code" href="classbdm_1_1MultiModel.html#d665551d045b1a1055eeb9185558ff0b">00403</a>                         <a class="code" href="classbdm_1_1enorm.html">enorm&lt;chmat&gt;</a> <a class="code" href="classbdm_1_1MultiModel.html#d665551d045b1a1055eeb9185558ff0b" title="internal statistics">est</a>; 
    335 <a name="l00404"></a>00404                 <span class="keyword">public</span>: 
    336 <a name="l00405"></a>00405                         <span class="keywordtype">void</span> set_parameters ( Array&lt;EKFCh*&gt; A, <span class="keywordtype">int</span> pol0=1 ) 
    337 <a name="l00406"></a>00406                         { 
    338 <a name="l00407"></a>00407                                 <a class="code" href="classbdm_1_1MultiModel.html#33de5d07ee774070632de8963b5d4c93" title="List of models between which we switch.">Models</a>=A;<span class="comment">//TODO: test if evalll is set</span> 
    339 <a name="l00408"></a>00408                                 <a class="code" href="classbdm_1_1MultiModel.html#ef85ea61575bffa8beac8040869ee47a" title="vector of model weights">w</a>.set_length ( A.length() ); 
    340 <a name="l00409"></a>00409                                 <a class="code" href="classbdm_1_1MultiModel.html#7b4012fc2208ce4ddd5c0d1fe69d7634" title="cache of model lls">_lls</a>.set_length ( A.length() ); 
    341 <a name="l00410"></a>00410                                 <a class="code" href="classbdm_1_1MultiModel.html#9b56bcde4664bd53f8995d7ee7ed415c" title="type of switching policy [1=maximum,2=...]">policy</a>=pol0; 
    342 <a name="l00411"></a>00411                                  
    343 <a name="l00412"></a>00412                                 <a class="code" href="classbdm_1_1MultiModel.html#d665551d045b1a1055eeb9185558ff0b" title="internal statistics">est</a>.<a class="code" href="classbdm_1_1epdf.html#f423e28448dbb69ef4905295ec8de8ff" title="Name its rv.">set_rv</a>(<a class="code" href="classbdm_1_1RV.html" title="Class representing variables, most often random variables.">RV</a>(<span class="stringliteral">"MM"</span>,A(0)-&gt;posterior().dimension(),0)); 
    344 <a name="l00413"></a>00413                                 <a class="code" href="classbdm_1_1MultiModel.html#d665551d045b1a1055eeb9185558ff0b" title="internal statistics">est</a>.<a class="code" href="classbdm_1_1enorm.html#b8322f2c11560871dd922c660f4771bb">set_parameters</a>(A(0)-&gt;_e()-&gt;mean(), A(0)-&gt;_e()-&gt;_R()); 
    345 <a name="l00414"></a>00414                         } 
    346 <a name="l00415"></a><a class="code" href="classbdm_1_1MultiModel.html#a915deeddb0e94c337d02ebc0abe535e">00415</a>                         <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1MultiModel.html#a915deeddb0e94c337d02ebc0abe535e" title="Incremental Bayes rule.">bayes</a> ( <span class="keyword">const</span> vec &amp;dt ) 
    347 <a name="l00416"></a>00416                         { 
    348 <a name="l00417"></a>00417                                 <span class="keywordtype">int</span> n = <a class="code" href="classbdm_1_1MultiModel.html#33de5d07ee774070632de8963b5d4c93" title="List of models between which we switch.">Models</a>.length(); 
    349 <a name="l00418"></a>00418                                 <span class="keywordtype">int</span> i; 
    350 <a name="l00419"></a>00419                                 <span class="keywordflow">for</span> ( i=0;i&lt;n;i++ ) 
    351 <a name="l00420"></a>00420                                 { 
    352 <a name="l00421"></a>00421                                         <a class="code" href="classbdm_1_1MultiModel.html#33de5d07ee774070632de8963b5d4c93" title="List of models between which we switch.">Models</a> ( i )-&gt;bayes ( dt ); 
    353 <a name="l00422"></a>00422                                         <a class="code" href="classbdm_1_1MultiModel.html#7b4012fc2208ce4ddd5c0d1fe69d7634" title="cache of model lls">_lls</a> ( i ) = <a class="code" href="classbdm_1_1MultiModel.html#33de5d07ee774070632de8963b5d4c93" title="List of models between which we switch.">Models</a> ( i )-&gt;_ll(); 
    354 <a name="l00423"></a>00423                                 } 
    355 <a name="l00424"></a>00424                                 <span class="keywordtype">double</span> mlls=max ( <a class="code" href="classbdm_1_1MultiModel.html#7b4012fc2208ce4ddd5c0d1fe69d7634" title="cache of model lls">_lls</a> ); 
    356 <a name="l00425"></a>00425                                 <a class="code" href="classbdm_1_1MultiModel.html#ef85ea61575bffa8beac8040869ee47a" title="vector of model weights">w</a>=exp ( <a class="code" href="classbdm_1_1MultiModel.html#7b4012fc2208ce4ddd5c0d1fe69d7634" title="cache of model lls">_lls</a>-mlls ); 
    357 <a name="l00426"></a>00426                                 <a class="code" href="classbdm_1_1MultiModel.html#ef85ea61575bffa8beac8040869ee47a" title="vector of model weights">w</a>/=sum ( <a class="code" href="classbdm_1_1MultiModel.html#ef85ea61575bffa8beac8040869ee47a" title="vector of model weights">w</a> ); <span class="comment">//normalization</span> 
    358 <a name="l00427"></a>00427                                 <span class="comment">//set statistics</span> 
    359 <a name="l00428"></a>00428                                 <span class="keywordflow">switch</span> ( <a class="code" href="classbdm_1_1MultiModel.html#9b56bcde4664bd53f8995d7ee7ed415c" title="type of switching policy [1=maximum,2=...]">policy</a> ) 
     327<a name="l00384"></a>00384                 <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> 
     328<a name="l00385"></a>00385                 { 
     329<a name="l00386"></a>00386                         <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 ); 
     330<a name="l00387"></a>00387                 } 
     331<a name="l00388"></a>00388  
     332<a name="l00389"></a>00389 <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> 
     333<a name="l00390"></a>00390  
     334<a name="l00391"></a>00391         }; 
     335<a name="l00392"></a>00392  
     336<a name="l00400"></a><a class="code" href="classbdm_1_1MultiModel.html">00400</a>         <span class="keyword">class </span><a class="code" href="classbdm_1_1MultiModel.html" title="(Switching) Multiple Model The model runs several models in parallel and evaluates...">MultiModel</a>: <span class="keyword">public</span> <a class="code" href="classbdm_1_1BM.html" title="Bayesian Model of a system, i.e. all uncertainty is modeled by probabilities.">BM</a> 
     337<a name="l00401"></a>00401         { 
     338<a name="l00402"></a>00402                 <span class="keyword">protected</span>: 
     339<a name="l00404"></a><a class="code" href="classbdm_1_1MultiModel.html#33de5d07ee774070632de8963b5d4c93">00404</a>                         Array&lt;EKFCh*&gt; <a class="code" href="classbdm_1_1MultiModel.html#33de5d07ee774070632de8963b5d4c93" title="List of models between which we switch.">Models</a>; 
     340<a name="l00406"></a><a class="code" href="classbdm_1_1MultiModel.html#ef85ea61575bffa8beac8040869ee47a">00406</a>                         vec <a class="code" href="classbdm_1_1MultiModel.html#ef85ea61575bffa8beac8040869ee47a" title="vector of model weights">w</a>; 
     341<a name="l00408"></a><a class="code" href="classbdm_1_1MultiModel.html#7b4012fc2208ce4ddd5c0d1fe69d7634">00408</a>                         vec <a class="code" href="classbdm_1_1MultiModel.html#7b4012fc2208ce4ddd5c0d1fe69d7634" title="cache of model lls">_lls</a>; 
     342<a name="l00410"></a><a class="code" href="classbdm_1_1MultiModel.html#9b56bcde4664bd53f8995d7ee7ed415c">00410</a>                         <span class="keywordtype">int</span> <a class="code" href="classbdm_1_1MultiModel.html#9b56bcde4664bd53f8995d7ee7ed415c" title="type of switching policy [1=maximum,2=...]">policy</a>; 
     343<a name="l00412"></a><a class="code" href="classbdm_1_1MultiModel.html#d665551d045b1a1055eeb9185558ff0b">00412</a>                         <a class="code" href="classbdm_1_1enorm.html">enorm&lt;chmat&gt;</a> <a class="code" href="classbdm_1_1MultiModel.html#d665551d045b1a1055eeb9185558ff0b" title="internal statistics">est</a>; 
     344<a name="l00413"></a>00413                 <span class="keyword">public</span>: 
     345<a name="l00414"></a>00414                         <span class="keywordtype">void</span> set_parameters ( Array&lt;EKFCh*&gt; A, <span class="keywordtype">int</span> pol0=1 ) 
     346<a name="l00415"></a>00415                         { 
     347<a name="l00416"></a>00416                                 <a class="code" href="classbdm_1_1MultiModel.html#33de5d07ee774070632de8963b5d4c93" title="List of models between which we switch.">Models</a>=A;<span class="comment">//TODO: test if evalll is set</span> 
     348<a name="l00417"></a>00417                                 <a class="code" href="classbdm_1_1MultiModel.html#ef85ea61575bffa8beac8040869ee47a" title="vector of model weights">w</a>.set_length ( A.length() ); 
     349<a name="l00418"></a>00418                                 <a class="code" href="classbdm_1_1MultiModel.html#7b4012fc2208ce4ddd5c0d1fe69d7634" title="cache of model lls">_lls</a>.set_length ( A.length() ); 
     350<a name="l00419"></a>00419                                 <a class="code" href="classbdm_1_1MultiModel.html#9b56bcde4664bd53f8995d7ee7ed415c" title="type of switching policy [1=maximum,2=...]">policy</a>=pol0; 
     351<a name="l00420"></a>00420                                  
     352<a name="l00421"></a>00421                                 <a class="code" href="classbdm_1_1MultiModel.html#d665551d045b1a1055eeb9185558ff0b" title="internal statistics">est</a>.<a class="code" href="classbdm_1_1epdf.html#f423e28448dbb69ef4905295ec8de8ff" title="Name its rv.">set_rv</a>(<a class="code" href="classbdm_1_1RV.html" title="Class representing variables, most often random variables.">RV</a>(<span class="stringliteral">"MM"</span>,A(0)-&gt;posterior().dimension(),0)); 
     353<a name="l00422"></a>00422                                 <a class="code" href="classbdm_1_1MultiModel.html#d665551d045b1a1055eeb9185558ff0b" title="internal statistics">est</a>.<a class="code" href="classbdm_1_1enorm.html#b8322f2c11560871dd922c660f4771bb">set_parameters</a>(A(0)-&gt;_e()-&gt;mean(), A(0)-&gt;_e()-&gt;_R()); 
     354<a name="l00423"></a>00423                         } 
     355<a name="l00424"></a><a class="code" href="classbdm_1_1MultiModel.html#a915deeddb0e94c337d02ebc0abe535e">00424</a>                         <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1MultiModel.html#a915deeddb0e94c337d02ebc0abe535e" title="Incremental Bayes rule.">bayes</a> ( <span class="keyword">const</span> vec &amp;dt ) 
     356<a name="l00425"></a>00425                         { 
     357<a name="l00426"></a>00426                                 <span class="keywordtype">int</span> n = <a class="code" href="classbdm_1_1MultiModel.html#33de5d07ee774070632de8963b5d4c93" title="List of models between which we switch.">Models</a>.length(); 
     358<a name="l00427"></a>00427                                 <span class="keywordtype">int</span> i; 
     359<a name="l00428"></a>00428                                 <span class="keywordflow">for</span> ( i=0;i&lt;n;i++ ) 
    360360<a name="l00429"></a>00429                                 { 
    361 <a name="l00430"></a>00430                                         <span class="keywordflow">case</span> 1: 
    362 <a name="l00431"></a>00431                                         { 
    363 <a name="l00432"></a>00432                                                 <span class="keywordtype">int</span> mi=max_index ( <a class="code" href="classbdm_1_1MultiModel.html#ef85ea61575bffa8beac8040869ee47a" title="vector of model weights">w</a> ); 
    364 <a name="l00433"></a>00433                                                 <span class="keyword">const</span> <a class="code" href="classbdm_1_1enorm.html">enorm&lt;chmat&gt;</a>* st=(<a class="code" href="classbdm_1_1MultiModel.html#33de5d07ee774070632de8963b5d4c93" title="List of models between which we switch.">Models</a>(mi)-&gt;_e()); 
    365 <a name="l00434"></a>00434                                                 <a class="code" href="classbdm_1_1MultiModel.html#d665551d045b1a1055eeb9185558ff0b" title="internal statistics">est</a>.<a class="code" href="classbdm_1_1enorm.html#b8322f2c11560871dd922c660f4771bb">set_parameters</a>(st-&gt;<a class="code" href="classbdm_1_1enorm.html#b2fa2915c35366392fe9bb022ca1a600" title="return expected value">mean</a>(), st-&gt;<a class="code" href="classbdm_1_1enorm.html#81d81e35e57c9f194bde248e3affcf1f">_R</a>()); 
    366 <a name="l00435"></a>00435                                         } 
    367 <a name="l00436"></a>00436                                         <span class="keywordflow">break</span>; 
    368 <a name="l00437"></a>00437                                         <span class="keywordflow">default</span>: it_error ( <span class="stringliteral">"unknown policy"</span> ); 
    369 <a name="l00438"></a>00438                                 } 
    370 <a name="l00439"></a>00439                                 <span class="comment">// copy result to all models</span> 
    371 <a name="l00440"></a>00440                                 <span class="keywordflow">for</span> ( i=0;i&lt;n;i++ ) 
    372 <a name="l00441"></a>00441                                 { 
    373 <a name="l00442"></a>00442                                                 <a class="code" href="classbdm_1_1MultiModel.html#33de5d07ee774070632de8963b5d4c93" title="List of models between which we switch.">Models</a> ( i )-&gt;set_statistics ( <a class="code" href="classbdm_1_1MultiModel.html#d665551d045b1a1055eeb9185558ff0b" title="internal statistics">est</a>.<a class="code" href="classbdm_1_1enorm.html#b2fa2915c35366392fe9bb022ca1a600" title="return expected value">mean</a>(),<a class="code" href="classbdm_1_1MultiModel.html#d665551d045b1a1055eeb9185558ff0b" title="internal statistics">est</a>.<a class="code" href="classbdm_1_1enorm.html#81d81e35e57c9f194bde248e3affcf1f">_R</a>()); 
    374 <a name="l00443"></a>00443                                 } 
    375 <a name="l00444"></a>00444                         } 
    376 <a name="l00445"></a>00445                         <span class="comment">//all posterior densities are equal =&gt; return the first one</span> 
    377 <a name="l00446"></a>00446                         <span class="keyword">const</span> <a class="code" href="classbdm_1_1enorm.html">enorm&lt;chmat&gt;</a>* _e()<span class="keyword"> const </span>{<span class="keywordflow">return</span> &amp;<a class="code" href="classbdm_1_1MultiModel.html#d665551d045b1a1055eeb9185558ff0b" title="internal statistics">est</a>;} 
    378 <a name="l00447"></a>00447                                 <span class="comment">//all posterior densities are equal =&gt; return the first one</span> 
    379 <a name="l00448"></a>00448                         <span class="keyword">const</span> enorm&lt;chmat&gt;&amp; posterior()<span class="keyword"> const </span>{<span class="keywordflow">return</span> <a class="code" href="classbdm_1_1MultiModel.html#d665551d045b1a1055eeb9185558ff0b" title="internal statistics">est</a>;} 
    380 <a name="l00449"></a>00449         }; 
    381 <a name="l00450"></a>00450  
    382 <a name="l00451"></a>00451  
    383 <a name="l00452"></a>00452 <span class="comment">//TODO why not const pointer??</span> 
    384 <a name="l00453"></a>00453  
    385 <a name="l00454"></a>00454         <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt; 
    386 <a name="l00455"></a><a class="code" href="classbdm_1_1EKF.html#d087a8bb408d26ac4f5c542746b81059">00455</a>         <a class="code" href="classbdm_1_1EKF.html#d087a8bb408d26ac4f5c542746b81059" title="Default constructor.">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 ) {} 
    387 <a name="l00456"></a>00456  
    388 <a name="l00457"></a>00457         <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt; 
    389 <a name="l00458"></a><a class="code" href="classbdm_1_1EKF.html#00fec1a0a6a467eb83fb36c65eba7bcb">00458</a>         <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1EKF.html#00fec1a0a6a467eb83fb36c65eba7bcb" title="Set nonlinear functions for mean values and covariance matrices.">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 ) 
    390 <a name="l00459"></a>00459         { 
    391 <a name="l00460"></a>00460                 pfxu = pfxu0; 
    392 <a name="l00461"></a>00461                 phxu = phxu0; 
     361<a name="l00430"></a>00430                                         <a class="code" href="classbdm_1_1MultiModel.html#33de5d07ee774070632de8963b5d4c93" title="List of models between which we switch.">Models</a> ( i )-&gt;bayes ( dt ); 
     362<a name="l00431"></a>00431                                         <a class="code" href="classbdm_1_1MultiModel.html#7b4012fc2208ce4ddd5c0d1fe69d7634" title="cache of model lls">_lls</a> ( i ) = <a class="code" href="classbdm_1_1MultiModel.html#33de5d07ee774070632de8963b5d4c93" title="List of models between which we switch.">Models</a> ( i )-&gt;_ll(); 
     363<a name="l00432"></a>00432                                 } 
     364<a name="l00433"></a>00433                                 <span class="keywordtype">double</span> mlls=max ( <a class="code" href="classbdm_1_1MultiModel.html#7b4012fc2208ce4ddd5c0d1fe69d7634" title="cache of model lls">_lls</a> ); 
     365<a name="l00434"></a>00434                                 <a class="code" href="classbdm_1_1MultiModel.html#ef85ea61575bffa8beac8040869ee47a" title="vector of model weights">w</a>=exp ( <a class="code" href="classbdm_1_1MultiModel.html#7b4012fc2208ce4ddd5c0d1fe69d7634" title="cache of model lls">_lls</a>-mlls ); 
     366<a name="l00435"></a>00435                                 <a class="code" href="classbdm_1_1MultiModel.html#ef85ea61575bffa8beac8040869ee47a" title="vector of model weights">w</a>/=sum ( <a class="code" href="classbdm_1_1MultiModel.html#ef85ea61575bffa8beac8040869ee47a" title="vector of model weights">w</a> ); <span class="comment">//normalization</span> 
     367<a name="l00436"></a>00436                                 <span class="comment">//set statistics</span> 
     368<a name="l00437"></a>00437                                 <span class="keywordflow">switch</span> ( <a class="code" href="classbdm_1_1MultiModel.html#9b56bcde4664bd53f8995d7ee7ed415c" title="type of switching policy [1=maximum,2=...]">policy</a> ) 
     369<a name="l00438"></a>00438                                 { 
     370<a name="l00439"></a>00439                                         <span class="keywordflow">case</span> 1: 
     371<a name="l00440"></a>00440                                         { 
     372<a name="l00441"></a>00441                                                 <span class="keywordtype">int</span> mi=max_index ( <a class="code" href="classbdm_1_1MultiModel.html#ef85ea61575bffa8beac8040869ee47a" title="vector of model weights">w</a> ); 
     373<a name="l00442"></a>00442                                                 <span class="keyword">const</span> <a class="code" href="classbdm_1_1enorm.html">enorm&lt;chmat&gt;</a>* st=(<a class="code" href="classbdm_1_1MultiModel.html#33de5d07ee774070632de8963b5d4c93" title="List of models between which we switch.">Models</a>(mi)-&gt;_e()); 
     374<a name="l00443"></a>00443                                                 <a class="code" href="classbdm_1_1MultiModel.html#d665551d045b1a1055eeb9185558ff0b" title="internal statistics">est</a>.<a class="code" href="classbdm_1_1enorm.html#b8322f2c11560871dd922c660f4771bb">set_parameters</a>(st-&gt;<a class="code" href="classbdm_1_1enorm.html#b2fa2915c35366392fe9bb022ca1a600" title="return expected value">mean</a>(), st-&gt;<a class="code" href="classbdm_1_1enorm.html#81d81e35e57c9f194bde248e3affcf1f">_R</a>()); 
     375<a name="l00444"></a>00444                                         } 
     376<a name="l00445"></a>00445                                         <span class="keywordflow">break</span>; 
     377<a name="l00446"></a>00446                                         <span class="keywordflow">default</span>: it_error ( <span class="stringliteral">"unknown policy"</span> ); 
     378<a name="l00447"></a>00447                                 } 
     379<a name="l00448"></a>00448                                 <span class="comment">// copy result to all models</span> 
     380<a name="l00449"></a>00449                                 <span class="keywordflow">for</span> ( i=0;i&lt;n;i++ ) 
     381<a name="l00450"></a>00450                                 { 
     382<a name="l00451"></a>00451                                                 <a class="code" href="classbdm_1_1MultiModel.html#33de5d07ee774070632de8963b5d4c93" title="List of models between which we switch.">Models</a> ( i )-&gt;set_statistics ( <a class="code" href="classbdm_1_1MultiModel.html#d665551d045b1a1055eeb9185558ff0b" title="internal statistics">est</a>.<a class="code" href="classbdm_1_1enorm.html#b2fa2915c35366392fe9bb022ca1a600" title="return expected value">mean</a>(),<a class="code" href="classbdm_1_1MultiModel.html#d665551d045b1a1055eeb9185558ff0b" title="internal statistics">est</a>.<a class="code" href="classbdm_1_1enorm.html#81d81e35e57c9f194bde248e3affcf1f">_R</a>()); 
     383<a name="l00452"></a>00452                                 } 
     384<a name="l00453"></a>00453                         } 
     385<a name="l00454"></a>00454                         <span class="comment">//all posterior densities are equal =&gt; return the first one</span> 
     386<a name="l00455"></a>00455                         <span class="keyword">const</span> <a class="code" href="classbdm_1_1enorm.html">enorm&lt;chmat&gt;</a>* _e()<span class="keyword"> const </span>{<span class="keywordflow">return</span> &amp;<a class="code" href="classbdm_1_1MultiModel.html#d665551d045b1a1055eeb9185558ff0b" title="internal statistics">est</a>;} 
     387<a name="l00456"></a>00456                                 <span class="comment">//all posterior densities are equal =&gt; return the first one</span> 
     388<a name="l00457"></a>00457                         <span class="keyword">const</span> enorm&lt;chmat&gt;&amp; posterior()<span class="keyword"> const </span>{<span class="keywordflow">return</span> <a class="code" href="classbdm_1_1MultiModel.html#d665551d045b1a1055eeb9185558ff0b" title="internal statistics">est</a>;} 
     389<a name="l00458"></a>00458  
     390<a name="l00459"></a>00459                         <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1MultiModel.html#2357434d2ec3c9b4e44e962bdfceda4e" title="This method arrange instance properties according the data stored in the Setting...">from_setting</a>( <span class="keyword">const</span> Setting &amp;root ); 
     391<a name="l00460"></a>00460  
     392<a name="l00461"></a>00461                         <span class="comment">// TODO dodelat void to_setting( Setting &amp;root ) const;</span> 
    393393<a name="l00462"></a>00462  
    394 <a name="l00463"></a>00463                 <span class="comment">//initialize matrices A C, later, these will be only updated!</span> 
    395 <a name="l00464"></a>00464                 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> ); 
    396 <a name="l00465"></a>00465 <span class="comment">//      pfxu-&gt;dfdu_cond ( *_mu,zeros ( dimu ),B,true );</span> 
    397 <a name="l00466"></a>00466                 <a class="code" href="classbdm_1_1Kalman.html#5977b2c81857948a35105f0e7840203c" title="Matrix B.">B</a>.clear(); 
    398 <a name="l00467"></a>00467                 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> ); 
    399 <a name="l00468"></a>00468 <span class="comment">//      phxu-&gt;dfdu_cond ( *_mu,zeros ( dimu ),D,true );</span> 
    400 <a name="l00469"></a>00469                 <a class="code" href="classbdm_1_1Kalman.html#7b56ac423d0654b5755e4f852a870456" title="Matrix D.">D</a>.clear(); 
     394<a name="l00463"></a>00463         }; 
     395<a name="l00464"></a>00464  
     396<a name="l00465"></a>00465         UIREGISTER(MultiModel); 
     397<a name="l00466"></a>00466  
     398<a name="l00467"></a>00467  
     399<a name="l00468"></a>00468  
     400<a name="l00469"></a>00469 <span class="comment">//TODO why not const pointer??</span> 
    401401<a name="l00470"></a>00470  
    402 <a name="l00471"></a>00471                 <a class="code" href="classbdm_1_1Kalman.html#475b088287cdfbba4dc60a3d027728b7" title="Matrix R in square-root form.">R</a> = R0; 
    403 <a name="l00472"></a>00472                 <a class="code" href="classbdm_1_1Kalman.html#70f8bf19e81b532c60fd3a7a152425ee" title="Matrix Q in square-root form.">Q</a> = Q0; 
    404 <a name="l00473"></a>00473         } 
    405 <a name="l00474"></a>00474  
    406 <a name="l00475"></a>00475         <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt; 
    407 <a name="l00476"></a><a class="code" href="classbdm_1_1EKF.html#3fb182ecc29b10ca1163cecbf3bcccfa">00476</a>         <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1EKF.html#3fb182ecc29b10ca1163cecbf3bcccfa" title="Here dt = [yt;ut] of appropriate dimensions.">EKF&lt;sq_T&gt;::bayes</a> ( <span class="keyword">const</span> vec &amp;dt ) 
    408 <a name="l00477"></a>00477         { 
    409 <a name="l00478"></a>00478                 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> ); 
     402<a name="l00471"></a>00471         <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt; 
     403<a name="l00472"></a><a class="code" href="classbdm_1_1EKF.html#d087a8bb408d26ac4f5c542746b81059">00472</a>         <a class="code" href="classbdm_1_1EKF.html#d087a8bb408d26ac4f5c542746b81059" title="Default constructor.">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 ) {} 
     404<a name="l00473"></a>00473  
     405<a name="l00474"></a>00474         <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt; 
     406<a name="l00475"></a><a class="code" href="classbdm_1_1EKF.html#00fec1a0a6a467eb83fb36c65eba7bcb">00475</a>         <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1EKF.html#00fec1a0a6a467eb83fb36c65eba7bcb" title="Set nonlinear functions for mean values and covariance matrices.">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 ) 
     407<a name="l00476"></a>00476         { 
     408<a name="l00477"></a>00477                 pfxu = pfxu0; 
     409<a name="l00478"></a>00478                 phxu = phxu0; 
    410410<a name="l00479"></a>00479  
    411 <a name="l00480"></a>00480                 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> ); 
    412 <a name="l00481"></a>00481                 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 ); 
    413 <a name="l00482"></a>00482                 vec y = dt.get ( 0,<a class="code" href="classbdm_1_1Kalman.html#d2c36ba01760bf207b985bf321b7817f" title="cache of rvy.count()">dimy</a>-1 ); 
    414 <a name="l00483"></a>00483                 <span class="comment">//Time update</span> 
    415 <a name="l00484"></a>00484                 <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 ); 
    416 <a name="l00485"></a>00485                 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> 
    417 <a name="l00486"></a>00486  
    418 <a name="l00487"></a>00487                 <span class="comment">//P  = A*P*A.transpose() + Q; in sq_T</span> 
    419 <a name="l00488"></a>00488                 <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> ); 
    420 <a name="l00489"></a>00489                 <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>; 
    421 <a name="l00490"></a>00490  
    422 <a name="l00491"></a>00491                 <span class="comment">//Data update</span> 
    423 <a name="l00492"></a>00492                 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> 
    424 <a name="l00493"></a>00493                 <span class="comment">//_Ry = C*P*C.transpose() + R; in sq_T</span> 
    425 <a name="l00494"></a>00494                 <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> ); 
    426 <a name="l00495"></a>00495                 ( <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>; 
     411<a name="l00480"></a>00480                 <span class="comment">//initialize matrices A C, later, these will be only updated!</span> 
     412<a name="l00481"></a>00481                 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> ); 
     413<a name="l00482"></a>00482 <span class="comment">//      pfxu-&gt;dfdu_cond ( *_mu,zeros ( dimu ),B,true );</span> 
     414<a name="l00483"></a>00483                 <a class="code" href="classbdm_1_1Kalman.html#5977b2c81857948a35105f0e7840203c" title="Matrix B.">B</a>.clear(); 
     415<a name="l00484"></a>00484                 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> ); 
     416<a name="l00485"></a>00485 <span class="comment">//      phxu-&gt;dfdu_cond ( *_mu,zeros ( dimu ),D,true );</span> 
     417<a name="l00486"></a>00486                 <a class="code" href="classbdm_1_1Kalman.html#7b56ac423d0654b5755e4f852a870456" title="Matrix D.">D</a>.clear(); 
     418<a name="l00487"></a>00487  
     419<a name="l00488"></a>00488                 <a class="code" href="classbdm_1_1Kalman.html#475b088287cdfbba4dc60a3d027728b7" title="Matrix R in square-root form.">R</a> = R0; 
     420<a name="l00489"></a>00489                 <a class="code" href="classbdm_1_1Kalman.html#70f8bf19e81b532c60fd3a7a152425ee" title="Matrix Q in square-root form.">Q</a> = Q0; 
     421<a name="l00490"></a>00490         } 
     422<a name="l00491"></a>00491  
     423<a name="l00492"></a>00492         <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt; 
     424<a name="l00493"></a><a class="code" href="classbdm_1_1EKF.html#3fb182ecc29b10ca1163cecbf3bcccfa">00493</a>         <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1EKF.html#3fb182ecc29b10ca1163cecbf3bcccfa" title="Here dt = [yt;ut] of appropriate dimensions.">EKF&lt;sq_T&gt;::bayes</a> ( <span class="keyword">const</span> vec &amp;dt ) 
     425<a name="l00494"></a>00494         { 
     426<a name="l00495"></a>00495                 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> ); 
    427427<a name="l00496"></a>00496  
    428 <a name="l00497"></a>00497                 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>(); 
    429 <a name="l00498"></a>00498  
    430 <a name="l00499"></a>00499                 <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> 
    431 <a name="l00500"></a>00500                 <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() ); 
    432 <a name="l00501"></a>00501  
    433 <a name="l00502"></a>00502                 sq_T pom ( ( <span class="keywordtype">int</span> ) Pfull.rows() ); 
    434 <a name="l00503"></a>00503                 iRy.mult_sym_t ( <a class="code" href="classbdm_1_1Kalman.html#818eba63a23972786a4579ad30294177" title="Matrix C.">C</a>*Pfull,pom ); 
    435 <a name="l00504"></a>00504                 ( <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> 
    436 <a name="l00505"></a>00505                 <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> 
    437 <a name="l00506"></a>00506                 ( <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> ); 
     428<a name="l00497"></a>00497                 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> ); 
     429<a name="l00498"></a>00498                 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 ); 
     430<a name="l00499"></a>00499                 vec y = dt.get ( 0,<a class="code" href="classbdm_1_1Kalman.html#d2c36ba01760bf207b985bf321b7817f" title="cache of rvy.count()">dimy</a>-1 ); 
     431<a name="l00500"></a>00500                 <span class="comment">//Time update</span> 
     432<a name="l00501"></a>00501                 <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 ); 
     433<a name="l00502"></a>00502                 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> 
     434<a name="l00503"></a>00503  
     435<a name="l00504"></a>00504                 <span class="comment">//P  = A*P*A.transpose() + Q; in sq_T</span> 
     436<a name="l00505"></a>00505                 <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> ); 
     437<a name="l00506"></a>00506                 <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>; 
    438438<a name="l00507"></a>00507  
    439 <a name="l00508"></a>00508                 <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 );} 
    440 <a name="l00509"></a>00509         }; 
    441 <a name="l00510"></a>00510  
    442 <a name="l00511"></a>00511  
    443 <a name="l00512"></a>00512 } 
    444 <a name="l00513"></a>00513 <span class="preprocessor">#endif // KF_H</span> 
    445 <a name="l00514"></a>00514 <span class="preprocessor"></span> 
     439<a name="l00508"></a>00508                 <span class="comment">//Data update</span> 
     440<a name="l00509"></a>00509                 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> 
     441<a name="l00510"></a>00510                 <span class="comment">//_Ry = C*P*C.transpose() + R; in sq_T</span> 
     442<a name="l00511"></a>00511                 <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> ); 
     443<a name="l00512"></a>00512                 ( <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>; 
     444<a name="l00513"></a>00513  
     445<a name="l00514"></a>00514                 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>(); 
    446446<a name="l00515"></a>00515  
     447<a name="l00516"></a>00516                 <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> 
     448<a name="l00517"></a>00517                 <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() ); 
     449<a name="l00518"></a>00518  
     450<a name="l00519"></a>00519                 sq_T pom ( ( <span class="keywordtype">int</span> ) Pfull.rows() ); 
     451<a name="l00520"></a>00520                 iRy.mult_sym_t ( <a class="code" href="classbdm_1_1Kalman.html#818eba63a23972786a4579ad30294177" title="Matrix C.">C</a>*Pfull,pom ); 
     452<a name="l00521"></a>00521                 ( <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> 
     453<a name="l00522"></a>00522                 <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> 
     454<a name="l00523"></a>00523                 ( <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> ); 
     455<a name="l00524"></a>00524  
     456<a name="l00525"></a>00525                 <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 );} 
     457<a name="l00526"></a>00526         }; 
     458<a name="l00527"></a>00527  
     459<a name="l00528"></a>00528  
     460<a name="l00529"></a>00529 } 
     461<a name="l00530"></a>00530 <span class="preprocessor">#endif // KF_H</span> 
     462<a name="l00531"></a>00531 <span class="preprocessor"></span> 
     463<a name="l00532"></a>00532  
    447464</pre></div></div> 
    448 <hr size="1"><address style="text-align: right;"><small>Generated on Tue Jun 2 10:11:00 2009 for mixpp by&nbsp; 
     465<hr size="1"><address style="text-align: right;"><small>Generated on Mon Jun 8 18:02:33 2009 for mixpp by&nbsp; 
    449466<a href="http://www.doxygen.org/index.html"> 
    450467<img src="doxygen.png" alt="doxygen" align="middle" border="0"></a> 1.5.8 </small></address>