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@@ -66,82 +69,103 @@
 <a name="l00014"></a>00014 <span class="preprocessor"></span><span class="preprocessor">#define AR_H</span>
 <a name="l00015"></a>00015 <span class="preprocessor"></span>
-<a name="l00016"></a>00016 <span class="preprocessor">#include "../math/functions.h"</span>
-<a name="l00017"></a>00017 <span class="preprocessor">#include "../stat/exp_family.h"</span>
-<a name="l00018"></a>00018 <span class="preprocessor">#include "../base/user_info.h"</span>
-<a name="l00019"></a>00019 
-<a name="l00020"></a>00020 <span class="keyword">namespace </span>bdm {
+<a name="l00016"></a>00016 <span class="preprocessor">#include &quot;../math/functions.h&quot;</span>
+<a name="l00017"></a>00017 <span class="preprocessor">#include &quot;../stat/exp_family.h&quot;</span>
+<a name="l00018"></a>00018 <span class="preprocessor">#include &quot;../base/user_info.h&quot;</span>
+<a name="l00019"></a>00019 <span class="comment">//#include &quot;../estim/kalman.h&quot;</span>
+<a name="l00020"></a>00020 <span class="preprocessor">#include &quot;<a class="code" href="arx__straux_8h.html" title="Bayesian Filtering for generalized autoregressive (ARX) model.">arx_straux.h</a>&quot;</span>
 <a name="l00021"></a>00021 
-<a name="l00041"></a><a class="code" href="classbdm_1_1ARX.html">00041</a> <span class="keyword">class </span><a class="code" href="classbdm_1_1ARX.html" title="Linear Autoregressive model with Gaussian noise.">ARX</a>: <span class="keyword">public</span> <a class="code" href="classbdm_1_1BMEF.html" title="Estimator for Exponential family.">BMEF</a> {
-<a name="l00042"></a>00042 <span class="keyword">protected</span>:
-<a name="l00044"></a><a class="code" href="classbdm_1_1ARX.html#8e68db2a218d54b09304cad6c0a897d9">00044</a>         <span class="keywordtype">int</span> <a class="code" href="classbdm_1_1ARX.html#8e68db2a218d54b09304cad6c0a897d9" title="size of output variable (needed in regressors)">dimx</a>;
-<a name="l00047"></a><a class="code" href="classbdm_1_1ARX.html#363aaa55b2ab3eec602510cdf53e84ef">00047</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_1ARX.html#363aaa55b2ab3eec602510cdf53e84ef">_yrv</a>;
-<a name="l00049"></a><a class="code" href="classbdm_1_1ARX.html#11474a627367f81b76830cb8477cf026">00049</a>         <a class="code" href="classbdm_1_1egiw.html" title="Gauss-inverse-Wishart density stored in LD form.">egiw</a> <a class="code" href="classbdm_1_1ARX.html#11474a627367f81b76830cb8477cf026" title="Posterior estimate of  in the form of Normal-inverse Wishart density.">est</a>;
-<a name="l00051"></a><a class="code" href="classbdm_1_1ARX.html#de5b7d83ff5d3f5af2f80068db0abdfd">00051</a>         <a class="code" href="classldmat.html" title="Matrix stored in LD form, (commonly known as UD).">ldmat</a> &amp;<a class="code" href="classbdm_1_1ARX.html#de5b7d83ff5d3f5af2f80068db0abdfd" title="cached value of est.V">V</a>;
-<a name="l00053"></a><a class="code" href="classbdm_1_1ARX.html#740b0582f180ba13cae91d66e9bdb67f">00053</a>         <span class="keywordtype">double</span> &amp;<a class="code" href="classbdm_1_1ARX.html#740b0582f180ba13cae91d66e9bdb67f" title="cached value of est.nu">nu</a>;
-<a name="l00054"></a>00054 <span class="keyword">public</span>:
-<a name="l00057"></a>00057         <a class="code" href="classbdm_1_1ARX.html" title="Linear Autoregressive model with Gaussian noise.">ARX</a> ( <span class="keyword">const</span> <span class="keywordtype">double</span> frg0=1.0 ) : <a class="code" href="classbdm_1_1BMEF.html" title="Estimator for Exponential family.">BMEF</a> ( frg0 ),<a class="code" href="classbdm_1_1ARX.html#11474a627367f81b76830cb8477cf026" title="Posterior estimate of  in the form of Normal-inverse Wishart density.">est</a> (), <a class="code" href="classbdm_1_1ARX.html#de5b7d83ff5d3f5af2f80068db0abdfd" title="cached value of est.V">V</a> ( <a class="code" href="classbdm_1_1ARX.html#11474a627367f81b76830cb8477cf026" title="Posterior estimate of  in the form of Normal-inverse Wishart density.">est</a>._V() ), <a class="code" href="classbdm_1_1ARX.html#740b0582f180ba13cae91d66e9bdb67f" title="cached value of est.nu">nu</a> ( <a class="code" href="classbdm_1_1ARX.html#11474a627367f81b76830cb8477cf026" title="Posterior estimate of  in the form of Normal-inverse Wishart density.">est</a>._nu() ) {};
-<a name="l00058"></a>00058         <a class="code" href="classbdm_1_1ARX.html" title="Linear Autoregressive model with Gaussian noise.">ARX</a> ( <span class="keyword">const</span> <a class="code" href="classbdm_1_1ARX.html" title="Linear Autoregressive model with Gaussian noise.">ARX</a> &amp;A0 ) : <a class="code" href="classbdm_1_1BMEF.html" title="Estimator for Exponential family.">BMEF</a> (),<a class="code" href="classbdm_1_1ARX.html#11474a627367f81b76830cb8477cf026" title="Posterior estimate of  in the form of Normal-inverse Wishart density.">est</a> (), <a class="code" href="classbdm_1_1ARX.html#de5b7d83ff5d3f5af2f80068db0abdfd" title="cached value of est.V">V</a> ( <a class="code" href="classbdm_1_1ARX.html#11474a627367f81b76830cb8477cf026" title="Posterior estimate of  in the form of Normal-inverse Wishart density.">est</a>._V() ), <a class="code" href="classbdm_1_1ARX.html#740b0582f180ba13cae91d66e9bdb67f" title="cached value of est.nu">nu</a> ( <a class="code" href="classbdm_1_1ARX.html#11474a627367f81b76830cb8477cf026" title="Posterior estimate of  in the form of Normal-inverse Wishart density.">est</a>._nu() ) {
-<a name="l00059"></a>00059                 set_statistics ( A0.<a class="code" href="classbdm_1_1ARX.html#8e68db2a218d54b09304cad6c0a897d9" title="size of output variable (needed in regressors)">dimx</a>,A0.<a class="code" href="classbdm_1_1ARX.html#de5b7d83ff5d3f5af2f80068db0abdfd" title="cached value of est.V">V</a>,A0.<a class="code" href="classbdm_1_1ARX.html#740b0582f180ba13cae91d66e9bdb67f" title="cached value of est.nu">nu</a> );
-<a name="l00060"></a>00060                 set_parameters(A0.<a class="code" href="classbdm_1_1BMEF.html#1331865e10fb1ccef65bb4c47fa3be64" title="forgetting factor">frg</a>);
-<a name="l00061"></a>00061         };
-<a name="l00062"></a>00062         ARX* <a class="code" href="classbdm_1_1ARX.html#ca0b54c0997cfd567f49377af5def106" title="Flatten the posterior as if to keep nu0 data.">_copy_</a>() <span class="keyword">const</span>;
-<a name="l00063"></a>00063         <span class="keywordtype">void</span> set_parameters ( <span class="keywordtype">double</span> frg0 ) {<a class="code" href="classbdm_1_1BMEF.html#1331865e10fb1ccef65bb4c47fa3be64" title="forgetting factor">frg</a>=frg0;}
-<a name="l00064"></a>00064         <span class="keywordtype">void</span> set_statistics ( <span class="keywordtype">int</span> dimx0, <span class="keyword">const</span> <a class="code" href="classldmat.html" title="Matrix stored in LD form, (commonly known as UD).">ldmat</a> V0, <span class="keywordtype">double</span> nu0=-1.0 ) {<a class="code" href="classbdm_1_1ARX.html#11474a627367f81b76830cb8477cf026" title="Posterior estimate of  in the form of Normal-inverse Wishart density.">est</a>.set_parameters ( dimx0,V0,nu0 );<a class="code" href="classbdm_1_1BMEF.html#06e7b3ac03e10017d4288c76888e2865" title="cached value of lognc() in the previous step (used in evaluation of ll )">last_lognc</a>=<a class="code" href="classbdm_1_1ARX.html#11474a627367f81b76830cb8477cf026" title="Posterior estimate of  in the form of Normal-inverse Wishart density.">est</a>.lognc();<a class="code" href="classbdm_1_1ARX.html#8e68db2a218d54b09304cad6c0a897d9" title="size of output variable (needed in regressors)">dimx</a>=dimx0;}
-<a name="l00066"></a>00066 
-<a name="l00067"></a>00067 <span class="comment">//      //! Set parameters given by moments, \c mu (mean of theta), \c R (mean of R) and \c C (variance of theta)</span>
-<a name="l00068"></a>00068 <span class="comment">//      void set_parameters ( const vec &amp;mu, const mat &amp;R, const mat &amp;C, double dfm){};</span>
-<a name="l00070"></a>00070 <span class="comment"></span>        <span class="keywordtype">void</span> set_statistics ( <span class="keyword">const</span> <a class="code" href="classbdm_1_1BMEF.html#2def512872ed8a4fc3b702371ec0be55" title="Default constructor (=empty constructor).">BMEF</a>* BM0 );
-<a name="l00071"></a>00071 <span class="comment">//      //! Returns sufficient statistics</span>
-<a name="l00072"></a>00072 <span class="comment">//      void get_parameters ( mat &amp;V0, double &amp;nu0 ) {V0=est._V().to_mat(); nu0=est._nu();}</span>
-<a name="l00075"></a>00075 <span class="comment"></span>
-<a name="l00077"></a>00077         <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1ARX.html#17e7fe14654ab3c449846c3f43e66169" title="Weighted Bayes .">bayes</a> ( <span class="keyword">const</span> vec &amp;dt, <span class="keyword">const</span> <span class="keywordtype">double</span> w );
-<a name="l00078"></a><a class="code" href="classbdm_1_1ARX.html#8bdf2974052e8ce74eb0d4f3791c58a3">00078</a>         <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1ARX.html#8bdf2974052e8ce74eb0d4f3791c58a3" title="Incremental Bayes rule.">bayes</a> ( <span class="keyword">const</span> vec &amp;dt ) {<a class="code" href="classbdm_1_1ARX.html#8bdf2974052e8ce74eb0d4f3791c58a3" title="Incremental Bayes rule.">bayes</a> ( dt,1.0 );};
-<a name="l00079"></a>00079         <span class="keywordtype">double</span> <a class="code" href="classbdm_1_1ARX.html#080a7e531e3aa06694112863b15bc6a4">logpred</a> ( <span class="keyword">const</span> vec &amp;dt ) <span class="keyword">const</span>;
-<a name="l00080"></a><a class="code" href="classbdm_1_1ARX.html#e86ab499b116b837d3163ec852961eca">00080</a>         <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1ARX.html#e86ab499b116b837d3163ec852961eca" title="Flatten the posterior according to the given BMEF (of the same type!).">flatten</a> ( <span class="keyword">const</span> <a class="code" href="classbdm_1_1BMEF.html" title="Estimator for Exponential family.">BMEF</a>* B ) {
-<a name="l00081"></a>00081                 <span class="keyword">const</span> <a class="code" href="classbdm_1_1ARX.html" title="Linear Autoregressive model with Gaussian noise.">ARX</a>* A=<span class="keyword">dynamic_cast&lt;</span><span class="keyword">const </span><a class="code" href="classbdm_1_1ARX.html" title="Linear Autoregressive model with Gaussian noise.">ARX</a>*<span class="keyword">&gt;</span> ( B );
-<a name="l00082"></a>00082                 <span class="comment">// nu should be equal to B.nu</span>
-<a name="l00083"></a>00083                 <a class="code" href="classbdm_1_1ARX.html#11474a627367f81b76830cb8477cf026" title="Posterior estimate of  in the form of Normal-inverse Wishart density.">est</a>.<a class="code" href="classbdm_1_1egiw.html#8e610e95401a11baf34f65e16ecd87be" title="Power of the density, used e.g. to flatten the density.">pow</a> ( A-&gt;<a class="code" href="classbdm_1_1ARX.html#740b0582f180ba13cae91d66e9bdb67f" title="cached value of est.nu">nu</a>/<a class="code" href="classbdm_1_1ARX.html#740b0582f180ba13cae91d66e9bdb67f" title="cached value of est.nu">nu</a> );
-<a name="l00084"></a>00084                 <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> ) {<a class="code" href="classbdm_1_1BMEF.html#06e7b3ac03e10017d4288c76888e2865" title="cached value of lognc() in the previous step (used in evaluation of ll )">last_lognc</a>=<a class="code" href="classbdm_1_1ARX.html#11474a627367f81b76830cb8477cf026" title="Posterior estimate of  in the form of Normal-inverse Wishart density.">est</a>.<a class="code" href="classbdm_1_1egiw.html#41d72ba7b2abc8a9a4209ffa98ed5633" title="logarithm of the normalizing constant, ">lognc</a>();}
-<a name="l00085"></a>00085         }
-<a name="l00087"></a>00087         <a class="code" href="classbdm_1_1enorm.html">enorm&lt;ldmat&gt;</a>* <a class="code" href="classbdm_1_1ARX.html#4cdf5e2a7d3480ec31f6247ed4289b15" title="Predictor for empty regressor.">epredictor</a> ( <span class="keyword">const</span> vec &amp;rgr ) <span class="keyword">const</span>;
-<a name="l00089"></a><a class="code" href="classbdm_1_1ARX.html#4cdf5e2a7d3480ec31f6247ed4289b15">00089</a>         <a class="code" href="classbdm_1_1enorm.html">enorm&lt;ldmat&gt;</a>* <a class="code" href="classbdm_1_1ARX.html#4cdf5e2a7d3480ec31f6247ed4289b15" title="Predictor for empty regressor.">epredictor</a>()<span class="keyword"> const </span>{
-<a name="l00090"></a>00090                 it_assert_debug ( <a class="code" href="classbdm_1_1ARX.html#8e68db2a218d54b09304cad6c0a897d9" title="size of output variable (needed in regressors)">dimx</a>==<a class="code" href="classbdm_1_1ARX.html#de5b7d83ff5d3f5af2f80068db0abdfd" title="cached value of est.V">V</a>.<a class="code" href="classsqmat.html#071e80ced9cc3b8cbb360fa7462eb646" title="Reimplementing common functions of mat: rows().">rows</a>()-1,<span class="stringliteral">"Regressor is not only 1"</span> );
-<a name="l00091"></a>00091                 <span class="keywordflow">return</span> <a class="code" href="classbdm_1_1ARX.html#4cdf5e2a7d3480ec31f6247ed4289b15" title="Predictor for empty regressor.">epredictor</a> ( vec_1 ( 1.0 ) );
-<a name="l00092"></a>00092         }
-<a name="l00094"></a>00094         <a class="code" href="classbdm_1_1mlnorm.html">mlnorm&lt;ldmat&gt;</a>* <a class="code" href="classbdm_1_1ARX.html#74fe8ae2d88bee8639510fd0eaf73513" title="conditional version of the predictor">predictor</a>() <span class="keyword">const</span>;
-<a name="l00095"></a>00095         <a class="code" href="classbdm_1_1mlstudent.html">mlstudent</a>* predictor_student() <span class="keyword">const</span>;
-<a name="l00097"></a>00097         ivec <a class="code" href="classbdm_1_1ARX.html#16b02ae03316751664c22d59d90c1e34" title="Brute force structure estimation.">structure_est</a> ( <a class="code" href="classbdm_1_1egiw.html" title="Gauss-inverse-Wishart density stored in LD form.">egiw</a> Eg0 );
-<a name="l00099"></a>00099 
-<a name="l00102"></a>00102         <span class="keyword">const</span> <a class="code" href="classbdm_1_1egiw.html" title="Gauss-inverse-Wishart density stored in LD form.">egiw</a>* _e()<span class="keyword"> const </span>{<span class="keywordflow">return</span> &amp;<a class="code" href="classbdm_1_1ARX.html#11474a627367f81b76830cb8477cf026" title="Posterior estimate of  in the form of Normal-inverse Wishart density.">est</a> ;};
-<a name="l00103"></a>00103         <span class="keyword">const</span> egiw&amp; posterior()<span class="keyword"> const </span>{<span class="keywordflow">return</span> <a class="code" href="classbdm_1_1ARX.html#11474a627367f81b76830cb8477cf026" title="Posterior estimate of  in the form of Normal-inverse Wishart density.">est</a>;}
-<a name="l00105"></a>00105 
-<a name="l00108"></a>00108         <span class="keywordtype">void</span> set_drv ( <span class="keyword">const</span> RV &amp;drv0 ) {<a class="code" href="classbdm_1_1BM.html#c400357e37d27a4834b2b1d9211009ed" title="Random variable of the data (optional).">drv</a>=drv0;}
-<a name="l00109"></a>00109         RV&amp; get_yrv() {
-<a name="l00110"></a>00110                 <span class="comment">//if yrv is not ready create it</span>
-<a name="l00111"></a>00111                 <span class="keywordflow">if</span> ( <a class="code" href="classbdm_1_1ARX.html#363aaa55b2ab3eec602510cdf53e84ef">_yrv</a>._dsize() !=<a class="code" href="classbdm_1_1ARX.html#8e68db2a218d54b09304cad6c0a897d9" title="size of output variable (needed in regressors)">dimx</a> ) {
-<a name="l00112"></a>00112                         <span class="keywordtype">int</span> i=0;
-<a name="l00113"></a>00113                         <span class="keywordflow">while</span> ( <a class="code" href="classbdm_1_1ARX.html#363aaa55b2ab3eec602510cdf53e84ef">_yrv</a>._dsize() &lt;<a class="code" href="classbdm_1_1ARX.html#8e68db2a218d54b09304cad6c0a897d9" title="size of output variable (needed in regressors)">dimx</a> ) {<a class="code" href="classbdm_1_1ARX.html#363aaa55b2ab3eec602510cdf53e84ef">_yrv</a>.add ( <a class="code" href="classbdm_1_1BM.html#c400357e37d27a4834b2b1d9211009ed" title="Random variable of the data (optional).">drv</a> ( vec_1 ( i ) ) );i++;}
-<a name="l00114"></a>00114                 }
-<a name="l00115"></a>00115                 <span class="comment">//yrv should be ready by now</span>
-<a name="l00116"></a>00116                 it_assert_debug ( <a class="code" href="classbdm_1_1ARX.html#363aaa55b2ab3eec602510cdf53e84ef">_yrv</a>._dsize() ==<a class="code" href="classbdm_1_1ARX.html#8e68db2a218d54b09304cad6c0a897d9" title="size of output variable (needed in regressors)">dimx</a>,<span class="stringliteral">"incompatible drv"</span> );
-<a name="l00117"></a>00117                 <span class="keywordflow">return</span> <a class="code" href="classbdm_1_1ARX.html#363aaa55b2ab3eec602510cdf53e84ef">_yrv</a>;
+<a name="l00022"></a>00022 <span class="keyword">namespace </span>bdm {
+<a name="l00023"></a>00023 
+<a name="l00043"></a><a class="code" href="classbdm_1_1ARX.html">00043</a> <span class="keyword">class </span><a class="code" href="classbdm_1_1ARX.html" title="Linear Autoregressive model with Gaussian noise.">ARX</a>: <span class="keyword">public</span> <a class="code" href="classbdm_1_1BMEF.html" title="Estimator for Exponential family.">BMEF</a> {
+<a name="l00044"></a>00044 <span class="keyword">protected</span>:
+<a name="l00046"></a><a class="code" href="classbdm_1_1ARX.html#a8e68db2a218d54b09304cad6c0a897d9">00046</a>         <span class="keywordtype">int</span> <a class="code" href="classbdm_1_1ARX.html#a8e68db2a218d54b09304cad6c0a897d9" title="size of output variable (needed in regressors)">dimx</a>;
+<a name="l00049"></a><a class="code" href="classbdm_1_1ARX.html#a363aaa55b2ab3eec602510cdf53e84ef">00049</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_1ARX.html#a363aaa55b2ab3eec602510cdf53e84ef">_yrv</a>;
+<a name="l00051"></a><a class="code" href="classbdm_1_1ARX.html#a11474a627367f81b76830cb8477cf026">00051</a>         <a class="code" href="classbdm_1_1egiw.html" title="Gauss-inverse-Wishart density stored in LD form.">egiw</a> <a class="code" href="classbdm_1_1ARX.html#a11474a627367f81b76830cb8477cf026" title="Posterior estimate of  in the form of Normal-inverse Wishart density.">est</a>;
+<a name="l00053"></a><a class="code" href="classbdm_1_1ARX.html#ade5b7d83ff5d3f5af2f80068db0abdfd">00053</a>         <a class="code" href="classbdm_1_1ldmat.html" title="Matrix stored in LD form, (commonly known as UD).">ldmat</a> &amp;<a class="code" href="classbdm_1_1ARX.html#ade5b7d83ff5d3f5af2f80068db0abdfd" title="cached value of est.V">V</a>;
+<a name="l00055"></a><a class="code" href="classbdm_1_1ARX.html#a740b0582f180ba13cae91d66e9bdb67f">00055</a>         <span class="keywordtype">double</span> &amp;<a class="code" href="classbdm_1_1ARX.html#a740b0582f180ba13cae91d66e9bdb67f" title="cached value of est.nu">nu</a>;
+<a name="l00056"></a>00056 <span class="keyword">public</span>:
+<a name="l00059"></a>00059         <a class="code" href="classbdm_1_1ARX.html" title="Linear Autoregressive model with Gaussian noise.">ARX</a> ( <span class="keyword">const</span> <span class="keywordtype">double</span> frg0 = 1.0 ) : <a class="code" href="classbdm_1_1BMEF.html" title="Estimator for Exponential family.">BMEF</a> ( frg0 ), <a class="code" href="classbdm_1_1ARX.html#a11474a627367f81b76830cb8477cf026" title="Posterior estimate of  in the form of Normal-inverse Wishart density.">est</a> (), <a class="code" href="classbdm_1_1ARX.html#ade5b7d83ff5d3f5af2f80068db0abdfd" title="cached value of est.V">V</a> ( <a class="code" href="classbdm_1_1ARX.html#a11474a627367f81b76830cb8477cf026" title="Posterior estimate of  in the form of Normal-inverse Wishart density.">est</a>._V() ), <a class="code" href="classbdm_1_1ARX.html#a740b0582f180ba13cae91d66e9bdb67f" title="cached value of est.nu">nu</a> ( <a class="code" href="classbdm_1_1ARX.html#a11474a627367f81b76830cb8477cf026" title="Posterior estimate of  in the form of Normal-inverse Wishart density.">est</a>._nu() ) {};
+<a name="l00060"></a>00060         <a class="code" href="classbdm_1_1ARX.html" title="Linear Autoregressive model with Gaussian noise.">ARX</a> ( <span class="keyword">const</span> <a class="code" href="classbdm_1_1ARX.html" title="Linear Autoregressive model with Gaussian noise.">ARX</a> &amp;A0 ) : <a class="code" href="classbdm_1_1BMEF.html" title="Estimator for Exponential family.">BMEF</a> (), <a class="code" href="classbdm_1_1ARX.html#a11474a627367f81b76830cb8477cf026" title="Posterior estimate of  in the form of Normal-inverse Wishart density.">est</a> (), <a class="code" href="classbdm_1_1ARX.html#ade5b7d83ff5d3f5af2f80068db0abdfd" title="cached value of est.V">V</a> ( <a class="code" href="classbdm_1_1ARX.html#a11474a627367f81b76830cb8477cf026" title="Posterior estimate of  in the form of Normal-inverse Wishart density.">est</a>._V() ), <a class="code" href="classbdm_1_1ARX.html#a740b0582f180ba13cae91d66e9bdb67f" title="cached value of est.nu">nu</a> ( <a class="code" href="classbdm_1_1ARX.html#a11474a627367f81b76830cb8477cf026" title="Posterior estimate of  in the form of Normal-inverse Wishart density.">est</a>._nu() ) {
+<a name="l00061"></a>00061                 set_statistics ( A0.<a class="code" href="classbdm_1_1ARX.html#a8e68db2a218d54b09304cad6c0a897d9" title="size of output variable (needed in regressors)">dimx</a>, A0.<a class="code" href="classbdm_1_1ARX.html#ade5b7d83ff5d3f5af2f80068db0abdfd" title="cached value of est.V">V</a>, A0.<a class="code" href="classbdm_1_1ARX.html#a740b0582f180ba13cae91d66e9bdb67f" title="cached value of est.nu">nu</a> );
+<a name="l00062"></a>00062                 set_parameters ( A0.<a class="code" href="classbdm_1_1BMEF.html#a1331865e10fb1ccef65bb4c47fa3be64" title="forgetting factor">frg</a> );
+<a name="l00063"></a>00063         };
+<a name="l00064"></a>00064         ARX* <a class="code" href="classbdm_1_1ARX.html#aca0b54c0997cfd567f49377af5def106">_copy_</a>() <span class="keyword">const</span>;
+<a name="l00065"></a>00065         <span class="keywordtype">void</span> set_parameters ( <span class="keywordtype">double</span> frg0 ) {
+<a name="l00066"></a>00066                 <a class="code" href="classbdm_1_1BMEF.html#a1331865e10fb1ccef65bb4c47fa3be64" title="forgetting factor">frg</a> = frg0;
+<a name="l00067"></a>00067         }
+<a name="l00068"></a>00068         <span class="keywordtype">void</span> set_statistics ( <span class="keywordtype">int</span> dimx0, <span class="keyword">const</span> ldmat V0, <span class="keywordtype">double</span> nu0 = -1.0 ) {
+<a name="l00069"></a>00069                 <a class="code" href="classbdm_1_1ARX.html#a11474a627367f81b76830cb8477cf026" title="Posterior estimate of  in the form of Normal-inverse Wishart density.">est</a>.set_parameters ( dimx0, V0, nu0 );
+<a name="l00070"></a>00070                 <a class="code" href="classbdm_1_1BMEF.html#a06e7b3ac03e10017d4288c76888e2865" title="cached value of lognc() in the previous step (used in evaluation of ll )">last_lognc</a> = <a class="code" href="classbdm_1_1ARX.html#a11474a627367f81b76830cb8477cf026" title="Posterior estimate of  in the form of Normal-inverse Wishart density.">est</a>.lognc();
+<a name="l00071"></a>00071                 <a class="code" href="classbdm_1_1ARX.html#a8e68db2a218d54b09304cad6c0a897d9" title="size of output variable (needed in regressors)">dimx</a> = dimx0;
+<a name="l00072"></a>00072         }
+<a name="l00074"></a>00074 
+<a name="l00075"></a>00075 <span class="comment">//      //! Set parameters given by moments, \c mu (mean of theta), \c R (mean of R) and \c C (variance of theta)</span>
+<a name="l00076"></a>00076 <span class="comment">//      void set_parameters ( const vec &amp;mu, const mat &amp;R, const mat &amp;C, double dfm){};</span>
+<a name="l00078"></a>00078 <span class="comment"></span>        <span class="keywordtype">void</span> set_statistics ( <span class="keyword">const</span> <a class="code" href="classbdm_1_1BMEF.html#a2def512872ed8a4fc3b702371ec0be55" title="Default constructor (=empty constructor).">BMEF</a>* BM0 );
+<a name="l00079"></a>00079 <span class="comment">//      //! Returns sufficient statistics</span>
+<a name="l00080"></a>00080 <span class="comment">//      void get_parameters ( mat &amp;V0, double &amp;nu0 ) {V0=est._V().to_mat(); nu0=est._nu();}</span>
+<a name="l00083"></a>00083 <span class="comment"></span>
+<a name="l00085"></a>00085         <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1ARX.html#a17e7fe14654ab3c449846c3f43e66169" title="Weighted Bayes .">bayes</a> ( <span class="keyword">const</span> vec &amp;dt, <span class="keyword">const</span> <span class="keywordtype">double</span> w );
+<a name="l00086"></a><a class="code" href="classbdm_1_1ARX.html#a8bdf2974052e8ce74eb0d4f3791c58a3">00086</a>         <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1ARX.html#a8bdf2974052e8ce74eb0d4f3791c58a3" title="Incremental Bayes rule.">bayes</a> ( <span class="keyword">const</span> vec &amp;dt ) {
+<a name="l00087"></a>00087                 <a class="code" href="classbdm_1_1ARX.html#a17e7fe14654ab3c449846c3f43e66169" title="Weighted Bayes .">bayes</a> ( dt, 1.0 );
+<a name="l00088"></a>00088         };
+<a name="l00089"></a>00089         <span class="keywordtype">double</span> <a class="code" href="classbdm_1_1ARX.html#a080a7e531e3aa06694112863b15bc6a4">logpred</a> ( <span class="keyword">const</span> vec &amp;dt ) <span class="keyword">const</span>;
+<a name="l00090"></a>00090         <span class="keywordtype">void</span> flatten ( <span class="keyword">const</span> <a class="code" href="classbdm_1_1BMEF.html" title="Estimator for Exponential family.">BMEF</a>* B ) {
+<a name="l00091"></a>00091                 <span class="keyword">const</span> <a class="code" href="classbdm_1_1ARX.html" title="Linear Autoregressive model with Gaussian noise.">ARX</a>* A = <span class="keyword">dynamic_cast&lt;</span><span class="keyword">const </span><a class="code" href="classbdm_1_1ARX.html" title="Linear Autoregressive model with Gaussian noise.">ARX</a>*<span class="keyword">&gt;</span> ( B );
+<a name="l00092"></a>00092                 <span class="comment">// nu should be equal to B.nu</span>
+<a name="l00093"></a>00093                 <a class="code" href="classbdm_1_1ARX.html#a11474a627367f81b76830cb8477cf026" title="Posterior estimate of  in the form of Normal-inverse Wishart density.">est</a>.<a class="code" href="classbdm_1_1egiw.html#a8e610e95401a11baf34f65e16ecd87be" title="Power of the density, used e.g. to flatten the density.">pow</a> ( A-&gt;<a class="code" href="classbdm_1_1ARX.html#a740b0582f180ba13cae91d66e9bdb67f" title="cached value of est.nu">nu</a> / <a class="code" href="classbdm_1_1ARX.html#a740b0582f180ba13cae91d66e9bdb67f" title="cached value of est.nu">nu</a> );
+<a name="l00094"></a>00094                 <span class="keywordflow">if</span> ( <a class="code" href="classbdm_1_1BM.html#afaff0ad12556fe7dc0e2807d4fd938ee" title="If true, the filter will compute likelihood of the data record and store it in ll...">evalll</a> ) {
+<a name="l00095"></a>00095                         <a class="code" href="classbdm_1_1BMEF.html#a06e7b3ac03e10017d4288c76888e2865" title="cached value of lognc() in the previous step (used in evaluation of ll )">last_lognc</a> = <a class="code" href="classbdm_1_1ARX.html#a11474a627367f81b76830cb8477cf026" title="Posterior estimate of  in the form of Normal-inverse Wishart density.">est</a>.<a class="code" href="classbdm_1_1egiw.html#a41d72ba7b2abc8a9a4209ffa98ed5633" title="logarithm of the normalizing constant, ">lognc</a>();
+<a name="l00096"></a>00096                 }
+<a name="l00097"></a>00097         }
+<a name="l00099"></a>00099         enorm&lt;ldmat&gt;* <a class="code" href="classbdm_1_1ARX.html#a4cdf5e2a7d3480ec31f6247ed4289b15" title="Predictor for empty regressor.">epredictor</a> ( <span class="keyword">const</span> vec &amp;rgr ) <span class="keyword">const</span>;
+<a name="l00101"></a><a class="code" href="classbdm_1_1ARX.html#a4cdf5e2a7d3480ec31f6247ed4289b15">00101</a>         <a class="code" href="classbdm_1_1enorm.html">enorm&lt;ldmat&gt;</a>* <a class="code" href="classbdm_1_1ARX.html#a4cdf5e2a7d3480ec31f6247ed4289b15" title="Predictor for empty regressor.">epredictor</a>()<span class="keyword"> const </span>{
+<a name="l00102"></a>00102                 <a class="code" href="bdmerror_8h.html#a89a0f906b242b79c5d3d342291b2cab4" title="Throw std::runtime_exception if t is not true and NDEBUG is not defined.">bdm_assert_debug</a> ( <a class="code" href="classbdm_1_1ARX.html#a8e68db2a218d54b09304cad6c0a897d9" title="size of output variable (needed in regressors)">dimx</a> == <a class="code" href="classbdm_1_1ARX.html#ade5b7d83ff5d3f5af2f80068db0abdfd" title="cached value of est.V">V</a>.<a class="code" href="classbdm_1_1sqmat.html#a73e639221343dcce76c3305524d67590" title="Reimplementing common functions of mat: rows().">rows</a>() - 1, <span class="stringliteral">&quot;Regressor is not only 1&quot;</span> );
+<a name="l00103"></a>00103                 <span class="keywordflow">return</span> <a class="code" href="classbdm_1_1ARX.html#a4cdf5e2a7d3480ec31f6247ed4289b15" title="Predictor for empty regressor.">epredictor</a> ( vec_1 ( 1.0 ) );
+<a name="l00104"></a>00104         }
+<a name="l00106"></a>00106         <a class="code" href="classbdm_1_1mlnorm.html" title="Normal distributed linear function with linear function of mean value;.">mlnorm&lt;ldmat&gt;</a>* <a class="code" href="classbdm_1_1ARX.html#a74fe8ae2d88bee8639510fd0eaf73513" title="conditional version of the predictor">predictor</a>() <span class="keyword">const</span>;
+<a name="l00107"></a>00107         <a class="code" href="classbdm_1_1mlstudent.html">mlstudent</a>* predictor_student() <span class="keyword">const</span>;
+<a name="l00109"></a>00109         ivec <a class="code" href="classbdm_1_1ARX.html#a16b02ae03316751664c22d59d90c1e34" title="Brute force structure estimation.">structure_est</a> ( <a class="code" href="classbdm_1_1egiw.html" title="Gauss-inverse-Wishart density stored in LD form.">egiw</a> Eg0 );
+<a name="l00111"></a>00111         ivec <a class="code" href="classbdm_1_1ARX.html#a5d0f217ce270e6a8cb43a67b6c4b67fa" title="Smarter structure estimation by Ludvik Tesar.">structure_est_LT</a> ( <a class="code" href="classbdm_1_1egiw.html" title="Gauss-inverse-Wishart density stored in LD form.">egiw</a> Eg0 );
+<a name="l00113"></a>00113 
+<a name="l00116"></a>00116         <span class="keyword">const</span> <a class="code" href="classbdm_1_1egiw.html" title="Gauss-inverse-Wishart density stored in LD form.">egiw</a>&amp; posterior()<span class="keyword"> const </span>{
+<a name="l00117"></a>00117                 <span class="keywordflow">return</span> <a class="code" href="classbdm_1_1ARX.html#a11474a627367f81b76830cb8477cf026" title="Posterior estimate of  in the form of Normal-inverse Wishart density.">est</a>;
 <a name="l00118"></a>00118         }
 <a name="l00120"></a>00120 
-<a name="l00121"></a>00121         <span class="comment">// TODO dokumentace - aktualizovat</span>
-<a name="l00142"></a>00142 <span class="comment"></span>        <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1ARX.html#9637412df898048bafaefee9dc7e9f6c">from_setting</a>( <span class="keyword">const</span> Setting &amp;<span class="keyword">set</span> );
-<a name="l00143"></a>00143 
-<a name="l00144"></a>00144 };
-<a name="l00145"></a>00145 
-<a name="l00146"></a>00146 <a class="code" href="user__info_8h.html#4f9de2f17e844047726487b99def99c6" title="Macro for registration of class into map of user-infos, registered class is scriptable...">UIREGISTER</a>(ARX);
-<a name="l00147"></a>00147 
-<a name="l00148"></a>00148 }
-<a name="l00149"></a>00149 
-<a name="l00150"></a>00150 <span class="preprocessor">#endif // AR_H</span>
-<a name="l00151"></a>00151 <span class="preprocessor"></span>
-<a name="l00152"></a>00152 
+<a name="l00123"></a>00123         <span class="keywordtype">void</span> set_drv ( <span class="keyword">const</span> RV &amp;drv0 ) {
+<a name="l00124"></a>00124                 <a class="code" href="classbdm_1_1BM.html#ac400357e37d27a4834b2b1d9211009ed" title="Random variable of the data (optional).">drv</a> = drv0;
+<a name="l00125"></a>00125         }
+<a name="l00126"></a>00126 
+<a name="l00127"></a>00127         RV&amp; get_yrv() {
+<a name="l00128"></a>00128                 <span class="comment">//if yrv is not ready create it</span>
+<a name="l00129"></a>00129                 <span class="keywordflow">if</span> ( <a class="code" href="classbdm_1_1ARX.html#a363aaa55b2ab3eec602510cdf53e84ef">_yrv</a>._dsize() != <a class="code" href="classbdm_1_1ARX.html#a8e68db2a218d54b09304cad6c0a897d9" title="size of output variable (needed in regressors)">dimx</a> ) {
+<a name="l00130"></a>00130                         <span class="keywordtype">int</span> i = 0;
+<a name="l00131"></a>00131                         <span class="keywordflow">while</span> ( <a class="code" href="classbdm_1_1ARX.html#a363aaa55b2ab3eec602510cdf53e84ef">_yrv</a>._dsize() &lt; <a class="code" href="classbdm_1_1ARX.html#a8e68db2a218d54b09304cad6c0a897d9" title="size of output variable (needed in regressors)">dimx</a> ) {
+<a name="l00132"></a>00132                                 <a class="code" href="classbdm_1_1ARX.html#a363aaa55b2ab3eec602510cdf53e84ef">_yrv</a>.add ( <a class="code" href="classbdm_1_1BM.html#ac400357e37d27a4834b2b1d9211009ed" title="Random variable of the data (optional).">drv</a> ( vec_1 ( i ) ) );
+<a name="l00133"></a>00133                                 i++;
+<a name="l00134"></a>00134                         }
+<a name="l00135"></a>00135                 }
+<a name="l00136"></a>00136                 <span class="comment">//yrv should be ready by now</span>
+<a name="l00137"></a>00137                 <a class="code" href="bdmerror_8h.html#a89a0f906b242b79c5d3d342291b2cab4" title="Throw std::runtime_exception if t is not true and NDEBUG is not defined.">bdm_assert_debug</a> ( <a class="code" href="classbdm_1_1ARX.html#a363aaa55b2ab3eec602510cdf53e84ef">_yrv</a>._dsize() == <a class="code" href="classbdm_1_1ARX.html#a8e68db2a218d54b09304cad6c0a897d9" title="size of output variable (needed in regressors)">dimx</a>, <span class="stringliteral">&quot;incompatible drv&quot;</span> );
+<a name="l00138"></a>00138                 <span class="keywordflow">return</span> <a class="code" href="classbdm_1_1ARX.html#a363aaa55b2ab3eec602510cdf53e84ef">_yrv</a>;
+<a name="l00139"></a>00139         }
+<a name="l00141"></a>00141 
+<a name="l00142"></a>00142         <span class="comment">// TODO dokumentace - aktualizovat</span>
+<a name="l00163"></a>00163 <span class="comment"></span>        <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1ARX.html#a9637412df898048bafaefee9dc7e9f6c">from_setting</a> ( <span class="keyword">const</span> Setting &amp;<span class="keyword">set</span> );
+<a name="l00164"></a>00164 
+<a name="l00165"></a>00165 };
+<a name="l00166"></a>00166 
+<a name="l00167"></a>00167 <a class="code" href="user__info_8h.html#a4f9de2f17e844047726487b99def99c6" title="Macro for registration of class into map of user-infos, registered class is scriptable...">UIREGISTER</a> ( ARX );
+<a name="l00168"></a>00168 SHAREDPTR ( ARX );
+<a name="l00169"></a>00169 
+<a name="l00170"></a>00170 }
+<a name="l00171"></a>00171 
+<a name="l00172"></a>00172 <span class="preprocessor">#endif // AR_H</span>
+<a name="l00173"></a>00173 <span class="preprocessor"></span>
+<a name="l00174"></a>00174 
 </pre></div></div>
-<hr size="1"><address style="text-align: right;"><small>Generated on Wed Aug 5 00:06:46 2009 for mixpp by&nbsp;
+<hr size="1"/><address style="text-align: right;"><small>Generated on Sun Aug 30 22:10:49 2009 for mixpp by&nbsp;
 <a href="http://www.doxygen.org/index.html">
-<img src="doxygen.png" alt="doxygen" align="middle" border="0"></a> 1.5.9 </small></address>
+<img class="footer" src="doxygen.png" alt="doxygen"/></a> 1.6.1 </small></address>
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