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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#a320ac7b3b511bc4b26e8f8823026a453">00051</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#a320ac7b3b511bc4b26e8f8823026a453" title="rv of regressor">rgrrv</a>;
84<a name="l00053"></a><a class="code" href="classbdm_1_1ARX.html#a11474a627367f81b76830cb8477cf026">00053</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>;
85<a name="l00055"></a><a class="code" href="classbdm_1_1ARX.html#ade5b7d83ff5d3f5af2f80068db0abdfd">00055</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>;
86<a name="l00057"></a><a class="code" href="classbdm_1_1ARX.html#a740b0582f180ba13cae91d66e9bdb67f">00057</a>         <span class="keywordtype">double</span> &amp;<a class="code" href="classbdm_1_1ARX.html#a740b0582f180ba13cae91d66e9bdb67f" title="cached value of est.nu">nu</a>;
87<a name="l00059"></a><a class="code" href="classbdm_1_1ARX.html#a6dcf8458bdc25d831542c6da89961fbc">00059</a>         <span class="keywordtype">bool</span> <a class="code" href="classbdm_1_1ARX.html#a6dcf8458bdc25d831542c6da89961fbc" title="switch if constant is modelled or not">have_constant</a>;
88<a name="l00061"></a><a class="code" href="classbdm_1_1ARX.html#a8f87c2958e5690610fed2992d6ffe5c0">00061</a>         vec <a class="code" href="classbdm_1_1ARX.html#a8f87c2958e5690610fed2992d6ffe5c0" title="cached value of data vector for have_constant =true">_dt</a>;
89<a name="l00063"></a><a class="code" href="classbdm_1_1ARX.html#aa6b50507d9e7a56b38e549710ffb466d">00063</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#aa6b50507d9e7a56b38e549710ffb466d" title="Alternative estimate of parameters, used in stabilized forgetting, see [Kulhavy]...">alter_est</a>;
90<a name="l00064"></a>00064 <span class="keyword">public</span>:
91<a name="l00067"></a>00067         <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 class="code" href="classbdm_1_1ARX.html#a6dcf8458bdc25d831542c6da89961fbc" title="switch if constant is modelled or not">have_constant</a>(true), <a class="code" href="classbdm_1_1ARX.html#a8f87c2958e5690610fed2992d6ffe5c0" title="cached value of data vector for have_constant =true">_dt</a>() {};
92<a name="l00068"></a>00068         <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> (A0.<a class="code" href="classbdm_1_1BMEF.html#a1331865e10fb1ccef65bb4c47fa3be64" title="forgetting factor">frg</a>), <a class="code" href="classbdm_1_1ARX.html#a11474a627367f81b76830cb8477cf026" title="Posterior estimate of  in the form of Normal-inverse Wishart density.">est</a> (A0.<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 class="code" href="classbdm_1_1ARX.html#a6dcf8458bdc25d831542c6da89961fbc" title="switch if constant is modelled or not">have_constant</a>(A0.<a class="code" href="classbdm_1_1ARX.html#a6dcf8458bdc25d831542c6da89961fbc" title="switch if constant is modelled or not">have_constant</a>), <a class="code" href="classbdm_1_1ARX.html#a8f87c2958e5690610fed2992d6ffe5c0" title="cached value of data vector for have_constant =true">_dt</a>(A0.<a class="code" href="classbdm_1_1ARX.html#a8f87c2958e5690610fed2992d6ffe5c0" title="cached value of data vector for have_constant =true">_dt</a>) {
93<a name="l00069"></a>00069                 <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#a8e68db2a218d54b09304cad6c0a897d9" title="size of output variable (needed in regressors)">dimx</a>;
94<a name="l00070"></a>00070                 <a class="code" href="classbdm_1_1ARX.html#a363aaa55b2ab3eec602510cdf53e84ef">_yrv</a> = A0.<a class="code" href="classbdm_1_1ARX.html#a363aaa55b2ab3eec602510cdf53e84ef">_yrv</a>;
95<a name="l00071"></a>00071                 <a class="code" href="classbdm_1_1ARX.html#a320ac7b3b511bc4b26e8f8823026a453" title="rv of regressor">rgrrv</a> = A0.<a class="code" href="classbdm_1_1ARX.html#a320ac7b3b511bc4b26e8f8823026a453" title="rv of regressor">rgrrv</a>;
96<a name="l00072"></a>00072                 <a class="code" href="classbdm_1_1BM.html#af135ae6dce7e9f30c9f88229c7930b96" title="access function">set_drv</a>(A0._drv());
97<a name="l00073"></a>00073         };
98<a name="l00074"></a>00074         ARX* <a class="code" href="classbdm_1_1ARX.html#aca0b54c0997cfd567f49377af5def106" title="Copy function required in vectors, Arrays of BM etc. Have to be DELETED manually!...">_copy_</a>() <span class="keyword">const</span>;
99<a name="l00075"></a>00075         <span class="keywordtype">void</span> set_parameters ( <span class="keywordtype">double</span> frg0 ) {
100<a name="l00076"></a>00076                 <a class="code" href="classbdm_1_1BMEF.html#a1331865e10fb1ccef65bb4c47fa3be64" title="forgetting factor">frg</a> = frg0;
101<a name="l00077"></a>00077         }
102<a name="l00078"></a>00078         <span class="keywordtype">void</span> set_constant ( <span class="keywordtype">bool</span> const0 ) {
103<a name="l00079"></a>00079                 <a class="code" href="classbdm_1_1ARX.html#a6dcf8458bdc25d831542c6da89961fbc" title="switch if constant is modelled or not">have_constant</a>=const0;
104<a name="l00080"></a>00080         }
105<a name="l00081"></a>00081         <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 ) {
106<a name="l00082"></a>00082                 <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 );
107<a name="l00083"></a>00083                 <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();
108<a name="l00084"></a>00084                 <a class="code" href="classbdm_1_1ARX.html#a8e68db2a218d54b09304cad6c0a897d9" title="size of output variable (needed in regressors)">dimx</a> = dimx0;
109<a name="l00085"></a>00085         }
110<a name="l00087"></a>00087
111<a name="l00089"></a>00089         <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 );
112<a name="l00090"></a>00090
113<a name="l00093"></a>00093
114<a name="l00095"></a>00095         <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 );
115<a name="l00096"></a><a class="code" href="classbdm_1_1ARX.html#a8bdf2974052e8ce74eb0d4f3791c58a3">00096</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 ) {
116<a name="l00097"></a>00097                 <a class="code" href="classbdm_1_1ARX.html#a17e7fe14654ab3c449846c3f43e66169" title="Weighted Bayes .">bayes</a> ( dt, 1.0 );
117<a name="l00098"></a>00098         };
118<a name="l00099"></a>00099         <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>;
119<a name="l00100"></a>00100         <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 ) {
120<a name="l00101"></a>00101                 <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 );
121<a name="l00102"></a>00102                 <span class="comment">// nu should be equal to B.nu</span>
122<a name="l00103"></a>00103                 <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> );
123<a name="l00104"></a>00104                 <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> ) {
124<a name="l00105"></a>00105                         <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>();
125<a name="l00106"></a>00106                 }
126<a name="l00107"></a>00107         }
127<a name="l00109"></a>00109         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>;
128<a name="l00111"></a><a class="code" href="classbdm_1_1ARX.html#a4cdf5e2a7d3480ec31f6247ed4289b15">00111</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>{
129<a name="l00112"></a>00112                 <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> );
130<a name="l00113"></a>00113                 <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 ) );
131<a name="l00114"></a>00114         }
132<a name="l00116"></a>00116         <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>;
133<a name="l00117"></a>00117         <a class="code" href="classbdm_1_1mlstudent.html">mlstudent</a>* predictor_student() <span class="keyword">const</span>;
134<a name="l00119"></a>00119         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 );
135<a name="l00121"></a>00121         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 );
136<a name="l00123"></a>00123
137<a name="l00127"></a><a class="code" href="classbdm_1_1ARX.html#a5a96a50d212648f049122a31d9553618">00127</a>                 <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; <a class="code" href="classbdm_1_1ARX.html#a5a96a50d212648f049122a31d9553618" title="return correctly typed posterior (covariant return)">posterior</a>()<span class="keyword"> const </span>{
138<a name="l00128"></a>00128                 <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>;
139<a name="l00129"></a>00129         }
140<a name="l00131"></a>00131
141<a name="l00134"></a>00134         <span class="keywordtype">void</span> set_rv ( <span class="keyword">const</span> <a class="code" href="classbdm_1_1RV.html" title="Class representing variables, most often random variables.">RV</a> &amp;yrv0 , <span class="keyword">const</span> <a class="code" href="classbdm_1_1RV.html" title="Class representing variables, most often random variables.">RV</a> &amp;rgrrv0 ) {
142<a name="l00135"></a>00135                 <a class="code" href="classbdm_1_1ARX.html#a363aaa55b2ab3eec602510cdf53e84ef">_yrv</a> = yrv0;
143<a name="l00136"></a>00136                 <a class="code" href="classbdm_1_1ARX.html#a320ac7b3b511bc4b26e8f8823026a453" title="rv of regressor">rgrrv</a>=rgrrv0;
144<a name="l00137"></a>00137                 <a class="code" href="classbdm_1_1BM.html#af135ae6dce7e9f30c9f88229c7930b96" title="access function">set_drv</a>(concat(yrv0, <a class="code" href="classbdm_1_1ARX.html#a320ac7b3b511bc4b26e8f8823026a453" title="rv of regressor">rgrrv</a>));
145<a name="l00138"></a>00138         }
146<a name="l00139"></a>00139
147<a name="l00140"></a>00140         RV&amp; get_yrv() {
148<a name="l00141"></a>00141                 <span class="comment">//if yrv is not ready create it</span>
149<a name="l00142"></a>00142                 <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> ) {
150<a name="l00143"></a>00143                         <span class="keywordtype">int</span> i = 0;
151<a name="l00144"></a>00144                         <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> ) {
152<a name="l00145"></a>00145                                 <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 ) ) );
153<a name="l00146"></a>00146                                 i++;
154<a name="l00147"></a>00147                         }
155<a name="l00148"></a>00148                 }
156<a name="l00149"></a>00149                 <span class="comment">//yrv should be ready by now</span>
157<a name="l00150"></a>00150                 <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> );
158<a name="l00151"></a>00151                 <span class="keywordflow">return</span> <a class="code" href="classbdm_1_1ARX.html#a363aaa55b2ab3eec602510cdf53e84ef">_yrv</a>;
159<a name="l00152"></a>00152         }
160<a name="l00154"></a>00154
161<a name="l00175"></a>00175         <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> );
162<a name="l00176"></a>00176
163<a name="l00177"></a><a class="code" href="classbdm_1_1ARX.html#a5b4ae27fa320a1b6e09777239210566d">00177</a>         <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1ARX.html#a5b4ae27fa320a1b6e09777239210566d" title="This method TODO.">validate</a>() {
164<a name="l00178"></a>00178                 <a class="code" href="bdmerror_8h.html#a7a3399d182b8e3065532596e76f84849" title="Throw std::runtime_exception if t is not true.">bdm_assert</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#a363aaa55b2ab3eec602510cdf53e84ef">_yrv</a>.<a class="code" href="classbdm_1_1RV.html#ade30156104f61d86c94f758861418089" title="total size of a random variable">_dsize</a>(), <span class="stringliteral">&quot;RVs of parameters and regressor do not match&quot;</span>);
165<a name="l00179"></a>00179                 
166<a name="l00180"></a>00180         }
167<a name="l00181"></a>00181 };
168<a name="l00182"></a>00182
169<a name="l00183"></a>00183 <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 );
170<a name="l00184"></a>00184 SHAREDPTR ( ARX );
171<a name="l00185"></a>00185
172<a name="l00189"></a><a class="code" href="classbdm_1_1ARXfrg.html">00189</a> <span class="keyword">class </span><a class="code" href="classbdm_1_1ARXfrg.html">ARXfrg</a> : <span class="keyword">public</span> <a class="code" href="classbdm_1_1ARX.html" title="Linear Autoregressive model with Gaussian noise.">ARX</a>{
173<a name="l00190"></a>00190         <span class="keyword">public</span>:
174<a name="l00191"></a>00191                 <a class="code" href="classbdm_1_1ARXfrg.html">ARXfrg</a>():<a class="code" href="classbdm_1_1ARX.html" title="Linear Autoregressive model with Gaussian noise.">ARX</a>(){};
175<a name="l00193"></a><a class="code" href="classbdm_1_1ARXfrg.html#ac82a973ffbeff15346c4b16d75f7cd00">00193</a>                 <a class="code" href="classbdm_1_1ARXfrg.html#ac82a973ffbeff15346c4b16d75f7cd00" title="copy constructor">ARXfrg</a>(<span class="keyword">const</span> <a class="code" href="classbdm_1_1ARXfrg.html">ARXfrg</a> &amp;A0):<a class="code" href="classbdm_1_1ARX.html" title="Linear Autoregressive model with Gaussian noise.">ARX</a>(A0){};
176<a name="l00194"></a><a class="code" href="classbdm_1_1ARXfrg.html#a420f3f195d231723f2f2329ec900de60">00194</a>                 <a class="code" href="classbdm_1_1ARXfrg.html">ARXfrg</a>* <a class="code" href="classbdm_1_1ARXfrg.html#a420f3f195d231723f2f2329ec900de60" title="Copy function required in vectors, Arrays of BM etc. Have to be DELETED manually!...">_copy_</a>()<span class="keyword"> const </span>{<a class="code" href="classbdm_1_1ARXfrg.html">ARXfrg</a> *A = <span class="keyword">new</span> <a class="code" href="classbdm_1_1ARXfrg.html">ARXfrg</a>(*<span class="keyword">this</span>); <span class="keywordflow">return</span> A;}
177<a name="l00195"></a><a class="code" href="classbdm_1_1ARXfrg.html#a2baaf50640620cbd4c089a608e0c41bb">00195</a>         <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1ARXfrg.html#a2baaf50640620cbd4c089a608e0c41bb" title="Substitute val for rvc.">condition</a>(<span class="keyword">const</span> vec &amp;val){
178<a name="l00196"></a>00196                 <a class="code" href="classbdm_1_1BMEF.html#a1331865e10fb1ccef65bb4c47fa3be64" title="forgetting factor">frg</a> = val(0);
179<a name="l00197"></a>00197         }
180<a name="l00198"></a>00198 };
181<a name="l00199"></a>00199 <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>(ARXfrg);
182<a name="l00200"></a>00200 };
183<a name="l00201"></a>00201 <span class="preprocessor">#endif // AR_H</span>
184<a name="l00202"></a>00202 <span class="preprocessor"></span>
185<a name="l00203"></a>00203
186</pre></div></div>
187<hr size="1"/><address style="text-align: right;"><small>Generated on Thu Oct 15 00:07:48 2009 for mixpp by&nbsp;
188<a href="http://www.doxygen.org/index.html">
189<img class="footer" src="doxygen.png" alt="doxygen"/></a> 1.6.1 </small></address>
190</body>
191</html>
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