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> &<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> &<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> &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 &mu, const mat &R, const mat &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 &V0, double &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 &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 &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 &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<</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">></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-><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<ldmat>* <a class="code" href="classbdm_1_1ARX.html#a4cdf5e2a7d3480ec31f6247ed4289b15" title="Predictor for empty regressor.">epredictor</a> ( <span class="keyword">const</span> vec &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<ldmat></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">"Regressor is not only 1"</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<ldmat></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>& 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 &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& 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() < <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">"incompatible drv"</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 &<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> |
| 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> &<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> &<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="l00062"></a>00062 <span class="keyword">public</span>: |
| 90 | <a name="l00065"></a>00065 <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() ) {}; |
| 91 | <a name="l00066"></a>00066 <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> &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() ) { |
| 92 | <a name="l00067"></a>00067 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> ); |
| 93 | <a name="l00068"></a>00068 set_parameters ( A0.<a class="code" href="classbdm_1_1BMEF.html#a1331865e10fb1ccef65bb4c47fa3be64" title="forgetting factor">frg</a> ); |
| 94 | <a name="l00069"></a>00069 }; |
| 95 | <a name="l00070"></a>00070 ARX* <a class="code" href="classbdm_1_1ARX.html#aca0b54c0997cfd567f49377af5def106">_copy_</a>() <span class="keyword">const</span>; |
| 96 | <a name="l00071"></a>00071 <span class="keywordtype">void</span> set_parameters ( <span class="keywordtype">double</span> frg0 ) { |
| 97 | <a name="l00072"></a>00072 <a class="code" href="classbdm_1_1BMEF.html#a1331865e10fb1ccef65bb4c47fa3be64" title="forgetting factor">frg</a> = frg0; |
| 98 | <a name="l00073"></a>00073 } |
| 99 | <a name="l00074"></a>00074 <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 ) { |
| 100 | <a name="l00075"></a>00075 <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 ); |
| 101 | <a name="l00076"></a>00076 <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(); |
| 102 | <a name="l00077"></a>00077 <a class="code" href="classbdm_1_1ARX.html#a8e68db2a218d54b09304cad6c0a897d9" title="size of output variable (needed in regressors)">dimx</a> = dimx0; |
| 103 | <a name="l00078"></a>00078 } |
| 104 | <a name="l00080"></a>00080 |
| 105 | <a name="l00082"></a>00082 <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 ); |
| 106 | <a name="l00083"></a>00083 |
| 107 | <a name="l00086"></a>00086 |
| 108 | <a name="l00088"></a>00088 <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 &dt, <span class="keyword">const</span> <span class="keywordtype">double</span> w ); |
| 109 | <a name="l00089"></a><a class="code" href="classbdm_1_1ARX.html#a8bdf2974052e8ce74eb0d4f3791c58a3">00089</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 &dt ) { |
| 110 | <a name="l00090"></a>00090 <a class="code" href="classbdm_1_1ARX.html#a17e7fe14654ab3c449846c3f43e66169" title="Weighted Bayes .">bayes</a> ( dt, 1.0 ); |
| 111 | <a name="l00091"></a>00091 }; |
| 112 | <a name="l00092"></a>00092 <span class="keywordtype">double</span> <a class="code" href="classbdm_1_1ARX.html#a080a7e531e3aa06694112863b15bc6a4">logpred</a> ( <span class="keyword">const</span> vec &dt ) <span class="keyword">const</span>; |
| 113 | <a name="l00093"></a>00093 <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="l00094"></a>00094 <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<</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">></span> ( B ); |
| 115 | <a name="l00095"></a>00095 <span class="comment">// nu should be equal to B.nu</span> |
| 116 | <a name="l00096"></a>00096 <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-><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="l00097"></a>00097 <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="l00098"></a>00098 <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="l00099"></a>00099 } |
| 120 | <a name="l00100"></a>00100 } |
| 121 | <a name="l00102"></a>00102 enorm<ldmat>* <a class="code" href="classbdm_1_1ARX.html#a4cdf5e2a7d3480ec31f6247ed4289b15" title="Predictor for empty regressor.">epredictor</a> ( <span class="keyword">const</span> vec &rgr ) <span class="keyword">const</span>; |
| 122 | <a name="l00104"></a><a class="code" href="classbdm_1_1ARX.html#a4cdf5e2a7d3480ec31f6247ed4289b15">00104</a> <a class="code" href="classbdm_1_1enorm.html">enorm<ldmat></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="l00105"></a>00105 <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">"Regressor is not only 1"</span> ); |
| 124 | <a name="l00106"></a>00106 <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="l00107"></a>00107 } |
| 126 | <a name="l00109"></a>00109 <a class="code" href="classbdm_1_1mlnorm.html" title="Normal distributed linear function with linear function of mean value;.">mlnorm<ldmat></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="l00110"></a>00110 <a class="code" href="classbdm_1_1mlstudent.html">mlstudent</a>* predictor_student() <span class="keyword">const</span>; |
| 128 | <a name="l00112"></a>00112 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="l00114"></a>00114 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="l00116"></a>00116 |
| 131 | <a name="l00119"></a>00119 <span class="keyword">const</span> <a class="code" href="classbdm_1_1egiw.html" title="Gauss-inverse-Wishart density stored in LD form.">egiw</a>& posterior()<span class="keyword"> const </span>{ |
| 132 | <a name="l00120"></a>00120 <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="l00121"></a>00121 } |
| 134 | <a name="l00123"></a>00123 |
| 135 | <a name="l00126"></a>00126 <span class="keywordtype">void</span> set_rv ( <span class="keyword">const</span> RV &yrv0 , <span class="keyword">const</span> RV &rgrrv0 ) { |
| 136 | <a name="l00127"></a>00127 <a class="code" href="classbdm_1_1ARX.html#a363aaa55b2ab3eec602510cdf53e84ef">_yrv</a> = yrv0; |
| 137 | <a name="l00128"></a>00128 <a class="code" href="classbdm_1_1ARX.html#a320ac7b3b511bc4b26e8f8823026a453" title="rv of regressor">rgrrv</a>=rgrrv0; |
| 138 | <a name="l00129"></a>00129 set_drv(concat(yrv0, <a class="code" href="classbdm_1_1ARX.html#a320ac7b3b511bc4b26e8f8823026a453" title="rv of regressor">rgrrv</a>)); |
| 139 | <a name="l00130"></a>00130 } |
| 140 | <a name="l00131"></a>00131 |
| 141 | <a name="l00132"></a>00132 RV& get_yrv() { |
| 142 | <a name="l00133"></a>00133 <span class="comment">//if yrv is not ready create it</span> |
| 143 | <a name="l00134"></a>00134 <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> ) { |
| 144 | <a name="l00135"></a>00135 <span class="keywordtype">int</span> i = 0; |
| 145 | <a name="l00136"></a>00136 <span class="keywordflow">while</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> ) { |
| 146 | <a name="l00137"></a>00137 <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 ) ) ); |
| 147 | <a name="l00138"></a>00138 i++; |
| 148 | <a name="l00139"></a>00139 } |
| 149 | <a name="l00140"></a>00140 } |
| 150 | <a name="l00141"></a>00141 <span class="comment">//yrv should be ready by now</span> |
| 151 | <a name="l00142"></a>00142 <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">"incompatible drv"</span> ); |
| 152 | <a name="l00143"></a>00143 <span class="keywordflow">return</span> <a class="code" href="classbdm_1_1ARX.html#a363aaa55b2ab3eec602510cdf53e84ef">_yrv</a>; |
| 153 | <a name="l00144"></a>00144 } |
| 154 | <a name="l00146"></a>00146 |
| 155 | <a name="l00167"></a>00167 <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1ARX.html#a9637412df898048bafaefee9dc7e9f6c">from_setting</a> ( <span class="keyword">const</span> Setting &<span class="keyword">set</span> ); |
| 156 | <a name="l00168"></a>00168 |
| 157 | <a name="l00169"></a><a class="code" href="classbdm_1_1ARX.html#a5b4ae27fa320a1b6e09777239210566d">00169</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1ARX.html#a5b4ae27fa320a1b6e09777239210566d" title="This method TODO.">validate</a>() { |
| 158 | <a name="l00170"></a>00170 <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">"RVs of parameters and regressor do not match"</span>); |
| 159 | <a name="l00171"></a>00171 |
| 160 | <a name="l00172"></a>00172 } |
| 161 | <a name="l00173"></a>00173 }; |