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  • library/doc/html/kalman.html

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    55<link href="doxygen.css" rel="stylesheet" type="text/css"> 
    66</head><body> 
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    8484<div class="fragment"><pre class="fragment"><span class="preprocessor">#include "<a class="code" href="kalman_8h.html" title="Bayesian Filtering for linear Gaussian models (Kalman Filter) and extensions.">estim/kalman.h</a>"</span> 
    8585<span class="keyword">using namespace </span>bdm; 
    86          
     86 
    8787<span class="comment">// estimation of AR(0) model</span> 
    8888<span class="keywordtype">int</span> main() { 
    8989        <span class="comment">//dimensions</span> 
    90         <span class="keywordtype">int</span> dx=3, dy=3, du=1; 
     90        <span class="keywordtype">int</span> dx = 3, dy = 3, du = 1; 
    9191        <span class="comment">// matrices</span> 
    92         mat A = eye(dx); 
    93         mat B = zeros(dx,du); 
    94         mat C = eye(dx); 
    95         mat D = zeros(dy,du); 
    96         mat Q = eye(dx); 
    97         mat R = 0.1*eye(dy); 
     92        mat A = eye ( dx ); 
     93        mat B = zeros ( dx, du ); 
     94        mat C = eye ( dx ); 
     95        mat D = zeros ( dy, du ); 
     96        mat Q = eye ( dx ); 
     97        mat R = 0.1 * eye ( dy ); 
    9898        <span class="comment">//prior</span> 
    99         mat P0 = 100*eye(dx); 
    100         vec mu0 = zeros(dx); 
     99        mat P0 = 100 * eye ( dx ); 
     100        vec mu0 = zeros ( dx ); 
    101101        <span class="comment">// Estimator</span> 
    102102        KalmanCh KF; 
    103         KF.set_parameters(A,B,C,D,<span class="comment">/*covariances*/</span> Q,R); 
    104         KF.set_statistics(mu0,P0); 
     103        KF.set_parameters ( A, B, C, D,<span class="comment">/*covariances*/</span> Q, R ); 
     104        KF.set_statistics ( mu0, P0 ); 
    105105        <span class="comment">// Estimation loop</span> 
    106         <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i=0;i&lt;100;i++){ 
    107                 KF.bayes(randn(dx+du)); 
     106        <span class="keywordflow">for</span> ( <span class="keywordtype">int</span> i = 0; i &lt; 100; i++ ) { 
     107                KF.bayes ( randn ( dx + du ) ); 
    108108        } 
    109109        <span class="comment">//print results</span> 
    110110        cout &lt;&lt; <span class="stringliteral">"Posterior estimate of x is: "</span>  &lt;&lt; endl; 
    111         cout &lt;&lt; <span class="stringliteral">"mean: "</span>&lt;&lt; KF.posterior().mean()&lt;&lt; endl; 
    112         cout &lt;&lt; <span class="stringliteral">"variance: "</span>&lt;&lt; KF.posterior().variance()&lt;&lt; endl; 
     111        cout &lt;&lt; <span class="stringliteral">"mean: "</span> &lt;&lt; KF.posterior().mean() &lt;&lt; endl; 
     112        cout &lt;&lt; <span class="stringliteral">"variance: "</span> &lt;&lt; KF.posterior().variance() &lt;&lt; endl; 
    113113} 
    114114</pre></div> </div> 
    115 <hr size="1"><address style="text-align: right;"><small>Generated on Wed Aug 5 00:06:51 2009 for mixpp by&nbsp; 
     115<hr size="1"><address style="text-align: right;"><small>Generated on Sun Aug 16 17:58:18 2009 for mixpp by&nbsp; 
    116116<a href="http://www.doxygen.org/index.html"> 
    117 <img src="doxygen.png" alt="doxygen" align="middle" border="0"></a> 1.5.9 </small></address> 
     117<img src="doxygen.png" alt="doxygen" align="middle" border="0"></a> 1.5.8 </small></address> 
    118118</body> 
    119119</html>