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67<h1>arx.h</h1><a href="arx_8h.html">Go to the documentation of this file.</a><div class="fragment"><pre class="fragment"><a name="l00001"></a>00001
68<a name="l00013"></a>00013 <span class="preprocessor">#ifndef AR_H</span>
69<a name="l00014"></a>00014 <span class="preprocessor"></span><span class="preprocessor">#define AR_H</span>
70<a name="l00015"></a>00015 <span class="preprocessor"></span>
71<a name="l00016"></a>00016 <span class="preprocessor">#include &quot;../math/functions.h&quot;</span>
72<a name="l00017"></a>00017 <span class="preprocessor">#include &quot;../stat/exp_family.h&quot;</span>
73<a name="l00018"></a>00018 <span class="preprocessor">#include &quot;../base/user_info.h&quot;</span>
74<a name="l00019"></a>00019 <span class="comment">//#include &quot;../estim/kalman.h&quot;</span>
75<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>
76<a name="l00021"></a>00021
77<a name="l00022"></a>00022 <span class="keyword">namespace </span>bdm {
78<a name="l00023"></a>00023
79<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> {
80<a name="l00044"></a>00044 <span class="keyword">protected</span>:
81<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>;
82<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>;
83<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>;
84<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>;
85<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>;
86<a name="l00056"></a>00056 <span class="keyword">public</span>:
87<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() ) {};
88<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() ) {
89<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> );
90<a name="l00062"></a>00062                 set_parameters ( A0.<a class="code" href="classbdm_1_1BMEF.html#a1331865e10fb1ccef65bb4c47fa3be64" title="forgetting factor">frg</a> );
91<a name="l00063"></a>00063         };
92<a name="l00064"></a>00064         ARX* <a class="code" href="classbdm_1_1ARX.html#aca0b54c0997cfd567f49377af5def106">_copy_</a>() <span class="keyword">const</span>;
93<a name="l00065"></a>00065         <span class="keywordtype">void</span> set_parameters ( <span class="keywordtype">double</span> frg0 ) {
94<a name="l00066"></a>00066                 <a class="code" href="classbdm_1_1BMEF.html#a1331865e10fb1ccef65bb4c47fa3be64" title="forgetting factor">frg</a> = frg0;
95<a name="l00067"></a>00067         }
96<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 ) {
97<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 );
98<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();
99<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;
100<a name="l00072"></a>00072         }
101<a name="l00074"></a>00074
102<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>
103<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>
104<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 );
105<a name="l00079"></a>00079 <span class="comment">//      //! Returns sufficient statistics</span>
106<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>
107<a name="l00083"></a>00083 <span class="comment"></span>
108<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 );
109<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 ) {
110<a name="l00087"></a>00087                 <a class="code" href="classbdm_1_1ARX.html#a17e7fe14654ab3c449846c3f43e66169" title="Weighted Bayes .">bayes</a> ( dt, 1.0 );
111<a name="l00088"></a>00088         };
112<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>;
113<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 ) {
114<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 );
115<a name="l00092"></a>00092                 <span class="comment">// nu should be equal to B.nu</span>
116<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> );
117<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> ) {
118<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>();
119<a name="l00096"></a>00096                 }
120<a name="l00097"></a>00097         }
121<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>;
122<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>{
123<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> );
124<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 ) );
125<a name="l00104"></a>00104         }
126<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>;
127<a name="l00107"></a>00107         <a class="code" href="classbdm_1_1mlstudent.html">mlstudent</a>* predictor_student() <span class="keyword">const</span>;
128<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 );
129<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 );
130<a name="l00113"></a>00113
131<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>{
132<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>;
133<a name="l00118"></a>00118         }
134<a name="l00120"></a>00120
135<a name="l00123"></a>00123         <span class="keywordtype">void</span> set_drv ( <span class="keyword">const</span> RV &amp;drv0 ) {
136<a name="l00124"></a>00124                 <a class="code" href="classbdm_1_1BM.html#ac400357e37d27a4834b2b1d9211009ed" title="Random variable of the data (optional).">drv</a> = drv0;
137<a name="l00125"></a>00125         }
138<a name="l00126"></a>00126
139<a name="l00127"></a>00127         RV&amp; get_yrv() {
140<a name="l00128"></a>00128                 <span class="comment">//if yrv is not ready create it</span>
141<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> ) {
142<a name="l00130"></a>00130                         <span class="keywordtype">int</span> i = 0;
143<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> ) {
144<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 ) ) );
145<a name="l00133"></a>00133                                 i++;
146<a name="l00134"></a>00134                         }
147<a name="l00135"></a>00135                 }
148<a name="l00136"></a>00136                 <span class="comment">//yrv should be ready by now</span>
149<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> );
150<a name="l00138"></a>00138                 <span class="keywordflow">return</span> <a class="code" href="classbdm_1_1ARX.html#a363aaa55b2ab3eec602510cdf53e84ef">_yrv</a>;
151<a name="l00139"></a>00139         }
152<a name="l00141"></a>00141
153<a name="l00142"></a>00142         <span class="comment">// TODO dokumentace - aktualizovat</span>
154<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> );
155<a name="l00164"></a>00164
156<a name="l00165"></a>00165 };
157<a name="l00166"></a>00166
158<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 );
159<a name="l00168"></a>00168 SHAREDPTR ( ARX );
160<a name="l00169"></a>00169
161<a name="l00170"></a>00170 }
162<a name="l00171"></a>00171
163<a name="l00172"></a>00172 <span class="preprocessor">#endif // AR_H</span>
164<a name="l00173"></a>00173 <span class="preprocessor"></span>
165<a name="l00174"></a>00174
166</pre></div></div>
167<hr size="1"/><address style="text-align: right;"><small>Generated on Tue Sep 15 23:42:47 2009 for mixpp by&nbsp;
168<a href="http://www.doxygen.org/index.html">
169<img class="footer" src="doxygen.png" alt="doxygen"/></a> 1.6.1 </small></address>
170</body>
171</html>
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