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64	<h1>exp_family.h</h1><a href="exp__family_8h.html">Go to the documentation of this file.</a><div class="fragment"><pre class="fragment"><a name="l00001"></a>00001
65	<a name="l00013"></a>00013 <span class="preprocessor">#ifndef EF_H</span>
66	<a name="l00014"></a>00014 <span class="preprocessor"></span><span class="preprocessor">#define EF_H</span>
67	<a name="l00015"></a>00015 <span class="preprocessor"></span>
68	<a name="l00016"></a>00016
69	<a name="l00017"></a>00017 <span class="preprocessor">#include "../shared_ptr.h"</span>
70	<a name="l00018"></a>00018 <span class="preprocessor">#include "../base/bdmbase.h"</span>
71	<a name="l00019"></a>00019 <span class="preprocessor">#include "../math/chmat.h"</span>
72	<a name="l00020"></a>00020
73	<a name="l00021"></a>00021 <span class="keyword">namespace </span>bdm
74	<a name="l00022"></a>00022 {
75	<a name="l00023"></a>00023
76	<a name="l00024"></a>00024
77	<a name="l00026"></a>00026 <span class="keyword">extern</span> Uniform_RNG UniRNG;
78	<a name="l00028"></a>00028 <span class="keyword">extern</span> Normal_RNG NorRNG;
79	<a name="l00030"></a>00030 <span class="keyword">extern</span> <a class="code" href="classitpp_1_1Gamma__RNG.html" title="Gamma distribution.">Gamma_RNG</a> GamRNG;
80	<a name="l00031"></a>00031
81	<a name="l00038"></a><a class="code" href="classbdm_1_1eEF.html">00038</a> <span class="keyword">class </span><a class="code" href="classbdm_1_1eEF.html" title="General conjugate exponential family posterior density.">eEF</a> : <span class="keyword">public</span> <a class="code" href="classbdm_1_1epdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a>
82	<a name="l00039"></a>00039 {
83	<a name="l00040"></a>00040 <span class="keyword">public</span>:
84	<a name="l00041"></a>00041 <span class="comment">// eEF() :epdf() {};</span>
85	<a name="l00043"></a><a class="code" href="classbdm_1_1eEF.html#d5459d472d0feca7cf1fb5f65c4b9ef4">00043</a> <span class="comment"></span> <a class="code" href="classbdm_1_1eEF.html#d5459d472d0feca7cf1fb5f65c4b9ef4" title="default constructor">eEF</a> ( ) :<a class="code" href="classbdm_1_1epdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a> ( ) {};
86	<a name="l00045"></a>00045 <span class="keyword">virtual</span> <span class="keywordtype">double</span> <a class="code" href="classbdm_1_1eEF.html#cd678fc9b02007a4b8d6692e746f1bf8" title="logarithm of the normalizing constant, ">lognc</a>() <span class="keyword">const</span> =0;
87	<a name="l00047"></a><a class="code" href="classbdm_1_1eEF.html#deef7d6273ba4d5a5cf0bbd91ec7277a">00047</a> <span class="keyword">virtual</span> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1eEF.html#deef7d6273ba4d5a5cf0bbd91ec7277a" title="TODO decide if it is really needed.">dupdate</a> ( mat &v ) {it_error ( <span class="stringliteral">"Not implemented"</span> );};
88	<a name="l00049"></a><a class="code" href="classbdm_1_1eEF.html#a4135778ecd9ab774762936c82a097c6">00049</a> <span class="keyword">virtual</span> <span class="keywordtype">double</span> <a class="code" href="classbdm_1_1eEF.html#a4135778ecd9ab774762936c82a097c6" title="Evaluate normalized log-probability.">evallog_nn</a> ( <span class="keyword">const</span> vec &val )<span class="keyword"> const</span>{it_error ( <span class="stringliteral">"Not implemented"</span> );<span class="keywordflow">return</span> 0.0;};
89	<a name="l00051"></a><a class="code" href="classbdm_1_1eEF.html#a36d06ecdd6f4c79dc122510eaccc692">00051</a> <span class="keyword">virtual</span> <span class="keywordtype">double</span> <a class="code" href="classbdm_1_1eEF.html#a36d06ecdd6f4c79dc122510eaccc692" title="Evaluate normalized log-probability.">evallog</a> ( <span class="keyword">const</span> vec &val )<span class="keyword"> const </span>{
90	<a name="l00052"></a>00052 <span class="keywordtype">double</span> tmp;
91	<a name="l00053"></a>00053 tmp= <a class="code" href="classbdm_1_1eEF.html#a4135778ecd9ab774762936c82a097c6" title="Evaluate normalized log-probability.">evallog_nn</a> ( val )-<a class="code" href="classbdm_1_1eEF.html#cd678fc9b02007a4b8d6692e746f1bf8" title="logarithm of the normalizing constant, ">lognc</a>();
92	<a name="l00054"></a>00054 <span class="comment">// it_assert_debug ( std::isfinite ( tmp ),"Infinite value" ); </span>
93	<a name="l00055"></a>00055 <span class="keywordflow">return</span> tmp;}
94	<a name="l00057"></a><a class="code" href="classbdm_1_1eEF.html#79a7c8ea8c02e45d410bd1d7ffd72b41">00057</a> <span class="keyword">virtual</span> vec <a class="code" href="classbdm_1_1eEF.html#a36d06ecdd6f4c79dc122510eaccc692" title="Evaluate normalized log-probability.">evallog</a> ( <span class="keyword">const</span> mat &Val )<span class="keyword"> const</span>
95	<a name="l00058"></a>00058 <span class="keyword"> </span>{
96	<a name="l00059"></a>00059 vec x ( Val.cols() );
97	<a name="l00060"></a>00060 <span class="keywordflow">for</span> ( <span class="keywordtype">int</span> i=0;i<Val.cols();i++ ) {x ( i ) =<a class="code" href="classbdm_1_1eEF.html#a4135778ecd9ab774762936c82a097c6" title="Evaluate normalized log-probability.">evallog_nn</a> ( Val.get_col ( i ) ) ;}
98	<a name="l00061"></a>00061 <span class="keywordflow">return</span> x-<a class="code" href="classbdm_1_1eEF.html#cd678fc9b02007a4b8d6692e746f1bf8" title="logarithm of the normalizing constant, ">lognc</a>();
99	<a name="l00062"></a>00062 }
100	<a name="l00064"></a><a class="code" href="classbdm_1_1eEF.html#cf38af29e8e3d650c640509a52396053">00064</a> <span class="keyword">virtual</span> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1eEF.html#cf38af29e8e3d650c640509a52396053" title="Power of the density, used e.g. to flatten the density.">pow</a> ( <span class="keywordtype">double</span> p ) {it_error ( <span class="stringliteral">"Not implemented"</span> );};
101	<a name="l00065"></a>00065 };
102	<a name="l00066"></a>00066
103	<a name="l00073"></a><a class="code" href="classbdm_1_1mEF.html">00073</a> <span class="keyword">class </span><a class="code" href="classbdm_1_1mEF.html" title="Exponential family model.">mEF</a> : <span class="keyword">public</span> <a class="code" href="classbdm_1_1mpdf.html" title="Conditional probability density, e.g. modeling some dependencies.">mpdf</a>
104	<a name="l00074"></a>00074 {
105	<a name="l00075"></a>00075
106	<a name="l00076"></a>00076 <span class="keyword">public</span>:
107	<a name="l00078"></a><a class="code" href="classbdm_1_1mEF.html#dd7caad7026b778af66e34480eec6f9e">00078</a> <a class="code" href="classbdm_1_1mEF.html#dd7caad7026b778af66e34480eec6f9e" title="Default constructor.">mEF</a> ( ) :<a class="code" href="classbdm_1_1mpdf.html" title="Conditional probability density, e.g. modeling some dependencies.">mpdf</a> ( ) {};
108	<a name="l00079"></a>00079 };
109	<a name="l00080"></a>00080
110	<a name="l00082"></a><a class="code" href="classbdm_1_1BMEF.html">00082</a> <span class="keyword">class </span><a class="code" href="classbdm_1_1BMEF.html" title="Estimator for Exponential family.">BMEF</a> : <span class="keyword">public</span> <a class="code" href="classbdm_1_1BM.html" title="Bayesian Model of a system, i.e. all uncertainty is modeled by probabilities.">BM</a>
111	<a name="l00083"></a>00083 {
112	<a name="l00084"></a>00084 <span class="keyword">protected</span>:
113	<a name="l00086"></a><a class="code" href="classbdm_1_1BMEF.html#1331865e10fb1ccef65bb4c47fa3be64">00086</a> <span class="keywordtype">double</span> <a class="code" href="classbdm_1_1BMEF.html#1331865e10fb1ccef65bb4c47fa3be64" title="forgetting factor">frg</a>;
114	<a name="l00088"></a><a class="code" href="classbdm_1_1BMEF.html#06e7b3ac03e10017d4288c76888e2865">00088</a> <span class="keywordtype">double</span> <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>;
115	<a name="l00089"></a>00089 <span class="keyword">public</span>:
116	<a name="l00091"></a><a class="code" href="classbdm_1_1BMEF.html#2def512872ed8a4fc3b702371ec0be55">00091</a> <a class="code" href="classbdm_1_1BMEF.html#2def512872ed8a4fc3b702371ec0be55" title="Default constructor (=empty constructor).">BMEF</a> ( <span class="keywordtype">double</span> frg0=1.0 ) :<a class="code" href="classbdm_1_1BM.html" title="Bayesian Model of a system, i.e. all uncertainty is modeled by probabilities.">BM</a> ( ), <a class="code" href="classbdm_1_1BMEF.html#1331865e10fb1ccef65bb4c47fa3be64" title="forgetting factor">frg</a> ( frg0 ) {}
117	<a name="l00093"></a><a class="code" href="classbdm_1_1BMEF.html#9662379513101405e159e76717104e62">00093</a> <a class="code" href="classbdm_1_1BMEF.html#9662379513101405e159e76717104e62" title="Copy constructor.">BMEF</a> ( <span class="keyword">const</span> <a class="code" href="classbdm_1_1BMEF.html" title="Estimator for Exponential family.">BMEF</a> &B ) :<a class="code" href="classbdm_1_1BM.html" title="Bayesian Model of a system, i.e. all uncertainty is modeled by probabilities.">BM</a> ( B ), <a class="code" href="classbdm_1_1BMEF.html#1331865e10fb1ccef65bb4c47fa3be64" title="forgetting factor">frg</a> ( B.<a class="code" href="classbdm_1_1BMEF.html#1331865e10fb1ccef65bb4c47fa3be64" title="forgetting factor">frg</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> ( B.<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> ) {}
118	<a name="l00095"></a><a class="code" href="classbdm_1_1BMEF.html#d2b528b7a41ca67163152142f5404051">00095</a> <span class="keyword">virtual</span> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1BMEF.html#d2b528b7a41ca67163152142f5404051" title="get statistics from another model">set_statistics</a> ( <span class="keyword">const</span> <a class="code" href="classbdm_1_1BMEF.html" title="Estimator for Exponential family.">BMEF</a>* BM0 ) {it_error ( <span class="stringliteral">"Not implemented"</span> );};
119	<a name="l00097"></a><a class="code" href="classbdm_1_1BMEF.html#bf58deb99af2a6cc674f13ff90300de6">00097</a> <span class="keyword">virtual</span> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1BMEF.html#bf58deb99af2a6cc674f13ff90300de6" title="Weighted update of sufficient statistics (Bayes rule).">bayes</a> ( <span class="keyword">const</span> vec &data, <span class="keyword">const</span> <span class="keywordtype">double</span> w ) {};
120	<a name="l00098"></a>00098 <span class="comment">//original Bayes</span>
121	<a name="l00099"></a>00099 <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1BMEF.html#bf58deb99af2a6cc674f13ff90300de6" title="Weighted update of sufficient statistics (Bayes rule).">bayes</a> ( <span class="keyword">const</span> vec &dt );
122	<a name="l00101"></a><a class="code" href="classbdm_1_1BMEF.html#b2916a2e71a958665054473124d5e749">00101</a> <span class="keyword">virtual</span> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1BMEF.html#b2916a2e71a958665054473124d5e749" 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 ) {it_error ( <span class="stringliteral">"Not implemented"</span> );}
123	<a name="l00103"></a>00103 <span class="comment">// virtual void flatten ( double nu0 ) {it_error ( "Not implemented" );}</span>
124	<a name="l00104"></a>00104
125	<a name="l00105"></a><a class="code" href="classbdm_1_1BMEF.html#62d2e4691bed41a1efa6b9c2e35e5c67">00105</a> <a class="code" href="classbdm_1_1BMEF.html" title="Estimator for Exponential family.">BMEF</a>* <a class="code" href="classbdm_1_1BMEF.html#62d2e4691bed41a1efa6b9c2e35e5c67" title="Flatten the posterior as if to keep nu0 data.">_copy_</a> ()<span class="keyword"> const </span>{it_error ( <span class="stringliteral">"function _copy_ not implemented for this BM"</span> ); <span class="keywordflow">return</span> NULL;};
126	<a name="l00106"></a>00106 };
127	<a name="l00107"></a>00107
128	<a name="l00108"></a>00108 <span class="keyword">template</span><<span class="keyword">class</span> sq_T>
129	<a name="l00109"></a>00109 <span class="keyword">class </span>mlnorm;
130	<a name="l00110"></a>00110
131	<a name="l00116"></a>00116 <span class="keyword">template</span><<span class="keyword">class</span> sq_T>
132	<a name="l00117"></a><a class="code" href="classbdm_1_1enorm.html">00117</a> <span class="keyword">class </span><a class="code" href="classbdm_1_1enorm.html" title="Gaussian density with positive definite (decomposed) covariance matrix.">enorm</a> : <span class="keyword">public</span> <a class="code" href="classbdm_1_1eEF.html" title="General conjugate exponential family posterior density.">eEF</a>
133	<a name="l00118"></a>00118 {
134	<a name="l00119"></a>00119 <span class="keyword">protected</span>:
135	<a name="l00121"></a><a class="code" href="classbdm_1_1enorm.html#c702a194720853570d08b65482f842c7">00121</a> vec <a class="code" href="classbdm_1_1enorm.html#c702a194720853570d08b65482f842c7" title="mean value">mu</a>;
136	<a name="l00123"></a><a class="code" href="classbdm_1_1enorm.html#2d92dde696b2a7a5b10ddef5d22ba2c2">00123</a> sq_T <a class="code" href="classbdm_1_1enorm.html#2d92dde696b2a7a5b10ddef5d22ba2c2" title="Covariance matrix in decomposed form.">R</a>;
137	<a name="l00124"></a>00124 <span class="keyword">public</span>:
138	<a name="l00127"></a>00127
139	<a name="l00128"></a>00128 <a class="code" href="classbdm_1_1enorm.html" title="Gaussian density with positive definite (decomposed) covariance matrix.">enorm</a> ( ) :<a class="code" href="classbdm_1_1eEF.html" title="General conjugate exponential family posterior density.">eEF</a> ( ), <a class="code" href="classbdm_1_1enorm.html#c702a194720853570d08b65482f842c7" title="mean value">mu</a> ( ),<a class="code" href="classbdm_1_1enorm.html#2d92dde696b2a7a5b10ddef5d22ba2c2" title="Covariance matrix in decomposed form.">R</a> ( ) {};
140	<a name="l00129"></a>00129 <a class="code" href="classbdm_1_1enorm.html" title="Gaussian density with positive definite (decomposed) covariance matrix.">enorm</a> ( <span class="keyword">const</span> vec &<a class="code" href="classbdm_1_1enorm.html#c702a194720853570d08b65482f842c7" title="mean value">mu</a>,<span class="keyword">const</span> sq_T &<a class="code" href="classbdm_1_1enorm.html#2d92dde696b2a7a5b10ddef5d22ba2c2" title="Covariance matrix in decomposed form.">R</a> ) {set_parameters ( mu,R );}
141	<a name="l00130"></a>00130 <span class="keywordtype">void</span> set_parameters ( <span class="keyword">const</span> vec &<a class="code" href="classbdm_1_1enorm.html#c702a194720853570d08b65482f842c7" title="mean value">mu</a>,<span class="keyword">const</span> sq_T &<a class="code" href="classbdm_1_1enorm.html#2d92dde696b2a7a5b10ddef5d22ba2c2" title="Covariance matrix in decomposed form.">R</a> );
142	<a name="l00131"></a>00131 <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1enorm.html#61bd470764020bea6e1ed35000f259e6">from_setting</a>(<span class="keyword">const</span> Setting &root);
143	<a name="l00132"></a><a class="code" href="classbdm_1_1enorm.html#38eb17ecb75d94a50b6782fcf735cfea">00132</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1enorm.html#38eb17ecb75d94a50b6782fcf735cfea" title="This method TODO.">validate</a>() {
144	<a name="l00133"></a>00133 it_assert(<a class="code" href="classbdm_1_1enorm.html#c702a194720853570d08b65482f842c7" title="mean value">mu</a>.length()==<a class="code" href="classbdm_1_1enorm.html#2d92dde696b2a7a5b10ddef5d22ba2c2" title="Covariance matrix in decomposed form.">R</a>.rows(),<span class="stringliteral">"parameters mismatch"</span>);
145	<a name="l00134"></a>00134 <a class="code" href="classbdm_1_1epdf.html#16adac20ec7fe07e1ea0b27d917788ce" title="dimension of the random variable">dim</a> = <a class="code" href="classbdm_1_1enorm.html#c702a194720853570d08b65482f842c7" title="mean value">mu</a>.length();
146	<a name="l00135"></a>00135 }
147	<a name="l00137"></a>00137
148	<a name="l00140"></a>00140
149	<a name="l00142"></a>00142 <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1enorm.html#d2e0d3a1e30ab3ab04df2d0c43ae74a2" title="dupdate in exponential form (not really handy)">dupdate</a> ( mat &v,<span class="keywordtype">double</span> nu=1.0 );
150	<a name="l00143"></a>00143
151	<a name="l00144"></a>00144 vec <a class="code" href="classbdm_1_1enorm.html#e1a48f52351ec3a349bd443b713b1766" title="Returns a sample, from density .">sample</a>() <span class="keyword">const</span>;
152	<a name="l00145"></a>00145
153	<a name="l00146"></a>00146 <span class="keywordtype">double</span> <a class="code" href="classbdm_1_1enorm.html#e13aeed5b543b2179bacdc4fa2ae47a3" title="Evaluate normalized log-probability.">evallog_nn</a> ( <span class="keyword">const</span> vec &val ) <span class="keyword">const</span>;
154	<a name="l00147"></a>00147 <span class="keywordtype">double</span> <a class="code" href="classbdm_1_1enorm.html#25785343aff102cc5df1cab08ba16d32" title="logarithm of the normalizing constant, ">lognc</a> () <span class="keyword">const</span>;
155	<a name="l00148"></a><a class="code" href="classbdm_1_1enorm.html#b2fa2915c35366392fe9bb022ca1a600">00148</a> vec <a class="code" href="classbdm_1_1enorm.html#b2fa2915c35366392fe9bb022ca1a600" title="return expected value">mean</a>()<span class="keyword"> const </span>{<span class="keywordflow">return</span> <a class="code" href="classbdm_1_1enorm.html#c702a194720853570d08b65482f842c7" title="mean value">mu</a>;}
156	<a name="l00149"></a><a class="code" href="classbdm_1_1enorm.html#729c75ef0fa8abae03d58ad1f81e6773">00149</a> vec <a class="code" href="classbdm_1_1enorm.html#729c75ef0fa8abae03d58ad1f81e6773" title="return expected variance (not covariance!)">variance</a>()<span class="keyword"> const </span>{<span class="keywordflow">return</span> diag ( <a class="code" href="classbdm_1_1enorm.html#2d92dde696b2a7a5b10ddef5d22ba2c2" title="Covariance matrix in decomposed form.">R</a>.to_mat() );}
157	<a name="l00150"></a>00150 <span class="comment">// mlnorm<sq_T>* condition ( const RV &rvn ) const ; <=========== fails to cmpile. Why?</span>
158	<a name="l00151"></a>00151 <a class="code" href="classbdm_1_1mpdf.html" title="Conditional probability density, e.g. modeling some dependencies.">mpdf</a>* <a class="code" href="classbdm_1_1enorm.html#baea4d49c657342b58297d68cda16d26" title="Return conditional density on the given RV, the remaining rvs will be in conditioning...">condition</a> ( <span class="keyword">const</span> <a class="code" href="classbdm_1_1RV.html" title="Class representing variables, most often random variables.">RV</a> &rvn ) <span class="keyword">const</span> ;
159	<a name="l00152"></a>00152 <a class="code" href="classbdm_1_1enorm.html" title="Gaussian density with positive definite (decomposed) covariance matrix.">enorm<sq_T></a>* <a class="code" href="classbdm_1_1enorm.html#c2996bdaffad38fbe0fc776db54c9d80" title="Return marginal density on the given RV, the remainig rvs are intergrated out.">marginal</a> ( <span class="keyword">const</span> <a class="code" href="classbdm_1_1RV.html" title="Class representing variables, most often random variables.">RV</a> &<a class="code" href="classbdm_1_1epdf.html#62c5b8ff71d9ebe6cd58d3c342eb1dc8" title="Description of the random variable.">rv</a> ) <span class="keyword">const</span>;
160	<a name="l00153"></a>00153 <span class="comment">// epdf* marginal ( const RV &rv ) const;</span>
161	<a name="l00155"></a>00155 <span class="comment"></span>
162	<a name="l00158"></a>00158
163	<a name="l00159"></a>00159 vec& _mu() {<span class="keywordflow">return</span> <a class="code" href="classbdm_1_1enorm.html#c702a194720853570d08b65482f842c7" title="mean value">mu</a>;}
164	<a name="l00160"></a>00160 <span class="keywordtype">void</span> set_mu ( <span class="keyword">const</span> vec mu0 ) { <a class="code" href="classbdm_1_1enorm.html#c702a194720853570d08b65482f842c7" title="mean value">mu</a>=mu0;}
165	<a name="l00161"></a>00161 sq_T& _R() {<span class="keywordflow">return</span> <a class="code" href="classbdm_1_1enorm.html#2d92dde696b2a7a5b10ddef5d22ba2c2" title="Covariance matrix in decomposed form.">R</a>;}
166	<a name="l00162"></a>00162 <span class="keyword">const</span> sq_T& _R()<span class="keyword"> const </span>{<span class="keywordflow">return</span> <a class="code" href="classbdm_1_1enorm.html#2d92dde696b2a7a5b10ddef5d22ba2c2" title="Covariance matrix in decomposed form.">R</a>;}
167	<a name="l00164"></a>00164
168	<a name="l00165"></a>00165 };
169	<a name="l00166"></a>00166 <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>(enorm<chmat>);
170	<a name="l00167"></a>00167 <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>(enorm<ldmat>);
171	<a name="l00168"></a>00168 <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>(enorm<fsqmat>);
172	<a name="l00169"></a>00169
173	<a name="l00170"></a>00170
174	<a name="l00177"></a><a class="code" href="classbdm_1_1egiw.html">00177</a> <span class="keyword">class </span><a class="code" href="classbdm_1_1egiw.html" title="Gauss-inverse-Wishart density stored in LD form.">egiw</a> : <span class="keyword">public</span> <a class="code" href="classbdm_1_1eEF.html" title="General conjugate exponential family posterior density.">eEF</a>
175	<a name="l00178"></a>00178 {
176	<a name="l00179"></a>00179 <span class="keyword">protected</span>:
177	<a name="l00181"></a><a class="code" href="classbdm_1_1egiw.html#ae56852845c6af176fd9017dbebbbd52">00181</a> <a class="code" href="classldmat.html" title="Matrix stored in LD form, (commonly known as UD).">ldmat</a> <a class="code" href="classbdm_1_1egiw.html#ae56852845c6af176fd9017dbebbbd52" title="Extended information matrix of sufficient statistics.">V</a>;
178	<a name="l00183"></a><a class="code" href="classbdm_1_1egiw.html#447eacf19d4f4083872686f044814dc4">00183</a> <span class="keywordtype">double</span> <a class="code" href="classbdm_1_1egiw.html#447eacf19d4f4083872686f044814dc4" title="Number of data records (degrees of freedom) of sufficient statistics.">nu</a>;
179	<a name="l00185"></a><a class="code" href="classbdm_1_1egiw.html#23e4d78bea7e98840f3da30e76a2b57a">00185</a> <span class="keywordtype">int</span> <a class="code" href="classbdm_1_1egiw.html#23e4d78bea7e98840f3da30e76a2b57a" title="Dimension of the output.">dimx</a>;
180	<a name="l00187"></a><a class="code" href="classbdm_1_1egiw.html#322414c32d9a21a006a5aab0311f64fd">00187</a> <span class="keywordtype">int</span> <a class="code" href="classbdm_1_1egiw.html#322414c32d9a21a006a5aab0311f64fd" title="Dimension of the regressor.">nPsi</a>;
181	<a name="l00188"></a>00188 <span class="keyword">public</span>:
182	<a name="l00191"></a>00191 <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_1eEF.html" title="General conjugate exponential family posterior density.">eEF</a>() {};
183	<a name="l00192"></a>00192 <a class="code" href="classbdm_1_1egiw.html" title="Gauss-inverse-Wishart density stored in LD form.">egiw</a> ( <span class="keywordtype">int</span> dimx0, <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_1eEF.html" title="General conjugate exponential family posterior density.">eEF</a>() {set_parameters ( dimx0,V0, nu0 );};
184	<a name="l00193"></a>00193
185	<a name="l00194"></a>00194 <span class="keywordtype">void</span> set_parameters ( <span class="keywordtype">int</span> dimx0, <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 )
186	<a name="l00195"></a>00195 {
187	<a name="l00196"></a>00196 <a class="code" href="classbdm_1_1egiw.html#23e4d78bea7e98840f3da30e76a2b57a" title="Dimension of the output.">dimx</a>=dimx0;
188	<a name="l00197"></a>00197 <a class="code" href="classbdm_1_1egiw.html#322414c32d9a21a006a5aab0311f64fd" title="Dimension of the regressor.">nPsi</a> = V0.<a class="code" href="classsqmat.html#071e80ced9cc3b8cbb360fa7462eb646" title="Reimplementing common functions of mat: rows().">rows</a>()-<a class="code" href="classbdm_1_1egiw.html#23e4d78bea7e98840f3da30e76a2b57a" title="Dimension of the output.">dimx</a>;
189	<a name="l00198"></a>00198 <a class="code" href="classbdm_1_1epdf.html#16adac20ec7fe07e1ea0b27d917788ce" title="dimension of the random variable">dim</a> = <a class="code" href="classbdm_1_1egiw.html#23e4d78bea7e98840f3da30e76a2b57a" title="Dimension of the output.">dimx</a>* ( <a class="code" href="classbdm_1_1egiw.html#23e4d78bea7e98840f3da30e76a2b57a" title="Dimension of the output.">dimx</a>+<a class="code" href="classbdm_1_1egiw.html#322414c32d9a21a006a5aab0311f64fd" title="Dimension of the regressor.">nPsi</a> ); <span class="comment">// size(R) + size(Theta)</span>
190	<a name="l00199"></a>00199
191	<a name="l00200"></a>00200 <a class="code" href="classbdm_1_1egiw.html#ae56852845c6af176fd9017dbebbbd52" title="Extended information matrix of sufficient statistics.">V</a>=V0;
192	<a name="l00201"></a>00201 <span class="keywordflow">if</span> ( nu0<0 )
193	<a name="l00202"></a>00202 {
194	<a name="l00203"></a>00203 <a class="code" href="classbdm_1_1egiw.html#447eacf19d4f4083872686f044814dc4" title="Number of data records (degrees of freedom) of sufficient statistics.">nu</a> = 0.1 +<a class="code" href="classbdm_1_1egiw.html#322414c32d9a21a006a5aab0311f64fd" title="Dimension of the regressor.">nPsi</a> +2*<a class="code" href="classbdm_1_1egiw.html#23e4d78bea7e98840f3da30e76a2b57a" title="Dimension of the output.">dimx</a> +2; <span class="comment">// +2 assures finite expected value of R</span>
195	<a name="l00204"></a>00204 <span class="comment">// terms before that are sufficient for finite normalization</span>
196	<a name="l00205"></a>00205 }
197	<a name="l00206"></a>00206 <span class="keywordflow">else</span>
198	<a name="l00207"></a>00207 {
199	<a name="l00208"></a>00208 <a class="code" href="classbdm_1_1egiw.html#447eacf19d4f4083872686f044814dc4" title="Number of data records (degrees of freedom) of sufficient statistics.">nu</a>=nu0;
200	<a name="l00209"></a>00209 }
201	<a name="l00210"></a>00210 }
202	<a name="l00212"></a>00212
203	<a name="l00213"></a>00213 vec <a class="code" href="classbdm_1_1egiw.html#920f21548b7a3723923dd108fe514c61" title="Returns a sample, from density .">sample</a>() <span class="keyword">const</span>;
204	<a name="l00214"></a>00214 vec <a class="code" href="classbdm_1_1egiw.html#df70c05f918c3a6f86d60f10c1fd6ba2" title="return expected value">mean</a>() <span class="keyword">const</span>;
205	<a name="l00215"></a>00215 vec <a class="code" href="classbdm_1_1egiw.html#c1ecc406613cc2341225dc10c3d3b46a" title="return expected variance (not covariance!)">variance</a>() <span class="keyword">const</span>;
206	<a name="l00216"></a>00216
207	<a name="l00218"></a>00218 vec <a class="code" href="classbdm_1_1egiw.html#66d2ba9295c306012b309efcc9e516f0" title="LS estimate of .">est_theta</a>() <span class="keyword">const</span>;
208	<a name="l00219"></a>00219
209	<a name="l00221"></a>00221 <a class="code" href="classldmat.html" title="Matrix stored in LD form, (commonly known as UD).">ldmat</a> <a class="code" href="classbdm_1_1egiw.html#88c321a2051d1afdbb31a098896a717b" title="Covariance of the LS estimate.">est_theta_cov</a>() <span class="keyword">const</span>;
210	<a name="l00222"></a>00222
211	<a name="l00223"></a>00223 <span class="keywordtype">void</span> mean_mat ( mat &M, mat&R ) <span class="keyword">const</span>;
212	<a name="l00225"></a>00225 <span class="keywordtype">double</span> <a class="code" href="classbdm_1_1egiw.html#bfb8e7c619b34ad804a73bff71742b5e" title="In this instance, val= [theta, r]. For multivariate instances, it is stored columnwise...">evallog_nn</a> ( <span class="keyword">const</span> vec &val ) <span class="keyword">const</span>;
213	<a name="l00226"></a>00226 <span class="keywordtype">double</span> <a class="code" href="classbdm_1_1egiw.html#41d72ba7b2abc8a9a4209ffa98ed5633" title="logarithm of the normalizing constant, ">lognc</a> () <span class="keyword">const</span>;
214	<a name="l00227"></a><a class="code" href="classbdm_1_1egiw.html#8e610e95401a11baf34f65e16ecd87be">00227</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1egiw.html#8e610e95401a11baf34f65e16ecd87be" title="Power of the density, used e.g. to flatten the density.">pow</a> ( <span class="keywordtype">double</span> p ) {V=p;<a class="code" href="classbdm_1_1egiw.html#447eacf19d4f4083872686f044814dc4" title="Number of data records (degrees of freedom) of sufficient statistics.">nu</a>=p;};
215	<a name="l00228"></a>00228
216	<a name="l00231"></a>00231
217	<a name="l00232"></a>00232 <a class="code" href="classldmat.html" title="Matrix stored in LD form, (commonly known as UD).">ldmat</a>& _V() {<span class="keywordflow">return</span> V;}
218	<a name="l00233"></a>00233 <span class="keyword">const</span> <a class="code" href="classldmat.html" title="Matrix stored in LD form, (commonly known as UD).">ldmat</a>& _V()<span class="keyword"> const </span>{<span class="keywordflow">return</span> V;}
219	<a name="l00234"></a>00234 <span class="keywordtype">double</span>& _nu() {<span class="keywordflow">return</span> <a class="code" href="classbdm_1_1egiw.html#447eacf19d4f4083872686f044814dc4" title="Number of data records (degrees of freedom) of sufficient statistics.">nu</a>;}
220	<a name="l00235"></a>00235 <span class="keyword">const</span> <span class="keywordtype">double</span>& _nu()<span class="keyword"> const </span>{<span class="keywordflow">return</span> <a class="code" href="classbdm_1_1egiw.html#447eacf19d4f4083872686f044814dc4" title="Number of data records (degrees of freedom) of sufficient statistics.">nu</a>;}
221	<a name="l00236"></a><a class="code" href="classbdm_1_1egiw.html#55b76ec75bd2df5ef9cab3be20a33bbb">00236</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1egiw.html#55b76ec75bd2df5ef9cab3be20a33bbb">from_setting</a>(<span class="keyword">const</span> Setting &<span class="keyword">set</span>){
222	<a name="l00237"></a>00237 <a class="code" href="classbdm_1_1UI.html#cd1667e6fec99ec64dabcb3ca2ff922d">UI::get</a>(<a class="code" href="classbdm_1_1egiw.html#447eacf19d4f4083872686f044814dc4" title="Number of data records (degrees of freedom) of sufficient statistics.">nu</a>,<span class="keyword">set</span>,<span class="stringliteral">"nu"</span>);
223	<a name="l00238"></a>00238 <a class="code" href="classbdm_1_1UI.html#cd1667e6fec99ec64dabcb3ca2ff922d">UI::get</a>(<a class="code" href="classbdm_1_1egiw.html#23e4d78bea7e98840f3da30e76a2b57a" title="Dimension of the output.">dimx</a>,<span class="keyword">set</span>,<span class="stringliteral">"dimx"</span>);
224	<a name="l00239"></a>00239 <span class="keyword">set</span>.lookupValue(<span class="stringliteral">"nu"</span>,<a class="code" href="classbdm_1_1egiw.html#447eacf19d4f4083872686f044814dc4" title="Number of data records (degrees of freedom) of sufficient statistics.">nu</a>);
225	<a name="l00240"></a>00240 <span class="keyword">set</span>.lookupValue(<span class="stringliteral">"dimx"</span>,<a class="code" href="classbdm_1_1egiw.html#23e4d78bea7e98840f3da30e76a2b57a" title="Dimension of the output.">dimx</a>);
226	<a name="l00241"></a>00241 mat V;
227	<a name="l00242"></a>00242 <a class="code" href="classbdm_1_1UI.html#cd1667e6fec99ec64dabcb3ca2ff922d">UI::get</a>(V,<span class="keyword">set</span>,<span class="stringliteral">"V"</span>, UI::compulsory);
228	<a name="l00243"></a>00243 set_parameters(<a class="code" href="classbdm_1_1egiw.html#23e4d78bea7e98840f3da30e76a2b57a" title="Dimension of the output.">dimx</a>, V, <a class="code" href="classbdm_1_1egiw.html#447eacf19d4f4083872686f044814dc4" title="Number of data records (degrees of freedom) of sufficient statistics.">nu</a>);
229	<a name="l00244"></a>00244 <a class="code" href="classbdm_1_1RV.html" title="Class representing variables, most often random variables.">RV</a>* <a class="code" href="classbdm_1_1epdf.html#62c5b8ff71d9ebe6cd58d3c342eb1dc8" title="Description of the random variable.">rv</a>=UI::build<RV>(<span class="keyword">set</span>,<span class="stringliteral">"rv"</span>, UI::compulsory);
230	<a name="l00245"></a>00245 <a class="code" href="classbdm_1_1epdf.html#f423e28448dbb69ef4905295ec8de8ff" title="Name its rv.">set_rv</a>(*rv);
231	<a name="l00246"></a>00246 <span class="keyword">delete</span> rv;
232	<a name="l00247"></a>00247 }
233	<a name="l00249"></a>00249 };
234	<a name="l00250"></a>00250 <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>(egiw);
235	<a name="l00251"></a>00251
236	<a name="l00260"></a><a class="code" href="classbdm_1_1eDirich.html">00260</a> <span class="keyword">class </span><a class="code" href="classbdm_1_1eDirich.html" title="Dirichlet posterior density.">eDirich</a>: <span class="keyword">public</span> <a class="code" href="classbdm_1_1eEF.html" title="General conjugate exponential family posterior density.">eEF</a>
237	<a name="l00261"></a>00261 {
238	<a name="l00262"></a>00262 <span class="keyword">protected</span>:
239	<a name="l00264"></a><a class="code" href="classbdm_1_1eDirich.html#f25886a49b4667af61245de81c83b5d2">00264</a> vec <a class="code" href="classbdm_1_1eDirich.html#f25886a49b4667af61245de81c83b5d2" title="sufficient statistics">beta</a>;
240	<a name="l00265"></a>00265 <span class="keyword">public</span>:
241	<a name="l00268"></a>00268
242	<a name="l00269"></a>00269 <a class="code" href="classbdm_1_1eDirich.html" title="Dirichlet posterior density.">eDirich</a> () : <a class="code" href="classbdm_1_1eEF.html" title="General conjugate exponential family posterior density.">eEF</a> ( ) {};
243	<a name="l00270"></a>00270 <a class="code" href="classbdm_1_1eDirich.html" title="Dirichlet posterior density.">eDirich</a> ( <span class="keyword">const</span> <a class="code" href="classbdm_1_1eDirich.html" title="Dirichlet posterior density.">eDirich</a> &D0 ) : <a class="code" href="classbdm_1_1eEF.html" title="General conjugate exponential family posterior density.">eEF</a> () {set_parameters ( D0.<a class="code" href="classbdm_1_1eDirich.html#f25886a49b4667af61245de81c83b5d2" title="sufficient statistics">beta</a> );};
244	<a name="l00271"></a>00271 eDirich ( <span class="keyword">const</span> vec &beta0 ) {set_parameters ( beta0 );};
245	<a name="l00272"></a>00272 <span class="keywordtype">void</span> set_parameters ( <span class="keyword">const</span> vec &beta0 )
246	<a name="l00273"></a>00273 {
247	<a name="l00274"></a>00274 <a class="code" href="classbdm_1_1eDirich.html#f25886a49b4667af61245de81c83b5d2" title="sufficient statistics">beta</a>= beta0;
248	<a name="l00275"></a>00275 <a class="code" href="classbdm_1_1epdf.html#16adac20ec7fe07e1ea0b27d917788ce" title="dimension of the random variable">dim</a> = <a class="code" href="classbdm_1_1eDirich.html#f25886a49b4667af61245de81c83b5d2" title="sufficient statistics">beta</a>.length();
249	<a name="l00276"></a>00276 }
250	<a name="l00278"></a>00278
251	<a name="l00279"></a><a class="code" href="classbdm_1_1eDirich.html#3290613d31d58daa8a45a54b003871fc">00279</a> vec <a class="code" href="classbdm_1_1eDirich.html#3290613d31d58daa8a45a54b003871fc" title="Returns a sample, from density .">sample</a>()<span class="keyword"> const </span>{it_error ( <span class="stringliteral">"Not implemented"</span> );<span class="keywordflow">return</span> vec_1 ( 0.0 );};
252	<a name="l00280"></a><a class="code" href="classbdm_1_1eDirich.html#cb343355ec791298bb5a3404cd482fb6">00280</a> vec <a class="code" href="classbdm_1_1eDirich.html#cb343355ec791298bb5a3404cd482fb6" title="return expected value">mean</a>()<span class="keyword"> const </span>{<span class="keywordflow">return</span> <a class="code" href="classbdm_1_1eDirich.html#f25886a49b4667af61245de81c83b5d2" title="sufficient statistics">beta</a>/sum(<a class="code" href="classbdm_1_1eDirich.html#f25886a49b4667af61245de81c83b5d2" title="sufficient statistics">beta</a>);};
253	<a name="l00281"></a><a class="code" href="classbdm_1_1eDirich.html#43c547a2507e233706f92712d8c2aacc">00281</a> vec <a class="code" href="classbdm_1_1eDirich.html#43c547a2507e233706f92712d8c2aacc" title="return expected variance (not covariance!)">variance</a>()<span class="keyword"> const </span>{<span class="keywordtype">double</span> gamma =sum(<a class="code" href="classbdm_1_1eDirich.html#f25886a49b4667af61245de81c83b5d2" title="sufficient statistics">beta</a>); <span class="keywordflow">return</span> elem_mult ( <a class="code" href="classbdm_1_1eDirich.html#f25886a49b4667af61245de81c83b5d2" title="sufficient statistics">beta</a>, ( <a class="code" href="classbdm_1_1eDirich.html#f25886a49b4667af61245de81c83b5d2" title="sufficient statistics">beta</a>+1 ) ) / ( gamma* ( gamma+1 ) );}
254	<a name="l00283"></a><a class="code" href="classbdm_1_1eDirich.html#e09a24938e80c3d94b0ee842d1552318">00283</a> <span class="keywordtype">double</span> <a class="code" href="classbdm_1_1eDirich.html#e09a24938e80c3d94b0ee842d1552318" title="In this instance, val is ...">evallog_nn</a> ( <span class="keyword">const</span> vec &val )<span class="keyword"> const</span>
255	<a name="l00284"></a>00284 <span class="keyword"> </span>{
256	<a name="l00285"></a>00285 <span class="keywordtype">double</span> tmp; tmp= ( <a class="code" href="classbdm_1_1eDirich.html#f25886a49b4667af61245de81c83b5d2" title="sufficient statistics">beta</a>-1 ) *log ( val );
257	<a name="l00286"></a>00286 <span class="comment">// it_assert_debug ( std::isfinite ( tmp ),"Infinite value" );</span>
258	<a name="l00287"></a>00287 <span class="keywordflow">return</span> tmp;
259	<a name="l00288"></a>00288 };
260	<a name="l00289"></a><a class="code" href="classbdm_1_1eDirich.html#279a99f6266c82fe2273e83841f19eb2">00289</a> <span class="keywordtype">double</span> <a class="code" href="classbdm_1_1eDirich.html#279a99f6266c82fe2273e83841f19eb2" title="logarithm of the normalizing constant, ">lognc</a> ()<span class="keyword"> const</span>
261	<a name="l00290"></a>00290 <span class="keyword"> </span>{
262	<a name="l00291"></a>00291 <span class="keywordtype">double</span> tmp;
263	<a name="l00292"></a>00292 <span class="keywordtype">double</span> gam=sum ( <a class="code" href="classbdm_1_1eDirich.html#f25886a49b4667af61245de81c83b5d2" title="sufficient statistics">beta</a> );
264	<a name="l00293"></a>00293 <span class="keywordtype">double</span> lgb=0.0;
265	<a name="l00294"></a>00294 <span class="keywordflow">for</span> ( <span class="keywordtype">int</span> i=0;i<<a class="code" href="classbdm_1_1eDirich.html#f25886a49b4667af61245de81c83b5d2" title="sufficient statistics">beta</a>.length();i++ ) {lgb+=lgamma ( <a class="code" href="classbdm_1_1eDirich.html#f25886a49b4667af61245de81c83b5d2" title="sufficient statistics">beta</a> ( i ) );}
266	<a name="l00295"></a>00295 tmp= lgb-lgamma ( gam );
267	<a name="l00296"></a>00296 <span class="comment">// it_assert_debug ( std::isfinite ( tmp ),"Infinite value" );</span>
268	<a name="l00297"></a>00297 <span class="keywordflow">return</span> tmp;
269	<a name="l00298"></a>00298 };
270	<a name="l00300"></a><a class="code" href="classbdm_1_1eDirich.html#175e0add26d2105c28d8121eefb9e324">00300</a> vec& <a class="code" href="classbdm_1_1eDirich.html#175e0add26d2105c28d8121eefb9e324" title="access function">_beta</a>() {<span class="keywordflow">return</span> <a class="code" href="classbdm_1_1eDirich.html#f25886a49b4667af61245de81c83b5d2" title="sufficient statistics">beta</a>;}
271	<a name="l00302"></a>00302 };
272	<a name="l00303"></a>00303
273	<a name="l00305"></a><a class="code" href="classbdm_1_1multiBM.html">00305</a> <span class="keyword">class </span><a class="code" href="classbdm_1_1multiBM.html" title="Estimator for Multinomial density.">multiBM</a> : <span class="keyword">public</span> <a class="code" href="classbdm_1_1BMEF.html" title="Estimator for Exponential family.">BMEF</a>
274	<a name="l00306"></a>00306 {
275	<a name="l00307"></a>00307 <span class="keyword">protected</span>:
276	<a name="l00309"></a><a class="code" href="classbdm_1_1multiBM.html#9ecc6878abbd20eb8d8e43b6ab3f941a">00309</a> <a class="code" href="classbdm_1_1eDirich.html" title="Dirichlet posterior density.">eDirich</a> <a class="code" href="classbdm_1_1multiBM.html#9ecc6878abbd20eb8d8e43b6ab3f941a" title="Conjugate prior and posterior.">est</a>;
277	<a name="l00311"></a><a class="code" href="classbdm_1_1multiBM.html#044263356944c92209eecd39a5187d25">00311</a> vec &<a class="code" href="classbdm_1_1multiBM.html#044263356944c92209eecd39a5187d25" title="Pointer inside est to sufficient statistics.">beta</a>;
278	<a name="l00312"></a>00312 <span class="keyword">public</span>:
279	<a name="l00314"></a><a class="code" href="classbdm_1_1multiBM.html#c4dd6d9522a8a605776d21bac9bd9daf">00314</a> <a class="code" href="classbdm_1_1multiBM.html#c4dd6d9522a8a605776d21bac9bd9daf" title="Default constructor.">multiBM</a> ( ) : <a class="code" href="classbdm_1_1BMEF.html" title="Estimator for Exponential family.">BMEF</a> ( ),<a class="code" href="classbdm_1_1multiBM.html#9ecc6878abbd20eb8d8e43b6ab3f941a" title="Conjugate prior and posterior.">est</a> ( ),<a class="code" href="classbdm_1_1multiBM.html#044263356944c92209eecd39a5187d25" title="Pointer inside est to sufficient statistics.">beta</a> ( <a class="code" href="classbdm_1_1multiBM.html#9ecc6878abbd20eb8d8e43b6ab3f941a" title="Conjugate prior and posterior.">est</a>._beta() )
280	<a name="l00315"></a>00315 {
281	<a name="l00316"></a>00316 <span class="keywordflow">if</span> ( <a class="code" href="classbdm_1_1multiBM.html#044263356944c92209eecd39a5187d25" title="Pointer inside est to sufficient statistics.">beta</a>.length() >0 ) {<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_1multiBM.html#9ecc6878abbd20eb8d8e43b6ab3f941a" title="Conjugate prior and posterior.">est</a>.<a class="code" href="classbdm_1_1eDirich.html#279a99f6266c82fe2273e83841f19eb2" title="logarithm of the normalizing constant, ">lognc</a>();}
282	<a name="l00317"></a>00317 <span class="keywordflow">else</span>{<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>=0.0;}
283	<a name="l00318"></a>00318 }
284	<a name="l00320"></a><a class="code" href="classbdm_1_1multiBM.html#c4378cf8037f6bed29c74eea63344b31">00320</a> <a class="code" href="classbdm_1_1multiBM.html#c4378cf8037f6bed29c74eea63344b31" title="Copy constructor.">multiBM</a> ( <span class="keyword">const</span> <a class="code" href="classbdm_1_1multiBM.html" title="Estimator for Multinomial density.">multiBM</a> &B ) : <a class="code" href="classbdm_1_1BMEF.html" title="Estimator for Exponential family.">BMEF</a> ( B ),<a class="code" href="classbdm_1_1multiBM.html#9ecc6878abbd20eb8d8e43b6ab3f941a" title="Conjugate prior and posterior.">est</a> ( B.<a class="code" href="classbdm_1_1multiBM.html#9ecc6878abbd20eb8d8e43b6ab3f941a" title="Conjugate prior and posterior.">est</a> ),<a class="code" href="classbdm_1_1multiBM.html#044263356944c92209eecd39a5187d25" title="Pointer inside est to sufficient statistics.">beta</a> ( <a class="code" href="classbdm_1_1multiBM.html#9ecc6878abbd20eb8d8e43b6ab3f941a" title="Conjugate prior and posterior.">est</a>._beta() ) {}
285	<a name="l00322"></a><a class="code" href="classbdm_1_1multiBM.html#dbe6b90d410dc062a233d1dc09eeba52">00322</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1multiBM.html#dbe6b90d410dc062a233d1dc09eeba52" title="Sets sufficient statistics to match that of givefrom mB0.">set_statistics</a> ( <span class="keyword">const</span> <a class="code" href="classbdm_1_1BM.html" title="Bayesian Model of a system, i.e. all uncertainty is modeled by probabilities.">BM</a>* mB0 ) {<span class="keyword">const</span> <a class="code" href="classbdm_1_1multiBM.html" title="Estimator for Multinomial density.">multiBM</a>* mB=<span class="keyword">dynamic_cast<</span><span class="keyword">const </span><a class="code" href="classbdm_1_1multiBM.html" title="Estimator for Multinomial density.">multiBM</a>*<span class="keyword">></span> ( mB0 ); <a class="code" href="classbdm_1_1multiBM.html#044263356944c92209eecd39a5187d25" title="Pointer inside est to sufficient statistics.">beta</a>=mB-><a class="code" href="classbdm_1_1multiBM.html#044263356944c92209eecd39a5187d25" title="Pointer inside est to sufficient statistics.">beta</a>;}
286	<a name="l00323"></a><a class="code" href="classbdm_1_1multiBM.html#1e4bf41b61937fd80f34049742e23f95">00323</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1multiBM.html#1e4bf41b61937fd80f34049742e23f95" title="Incremental Bayes rule.">bayes</a> ( <span class="keyword">const</span> vec &dt )
287	<a name="l00324"></a>00324 {
288	<a name="l00325"></a>00325 <span class="keywordflow">if</span> ( <a class="code" href="classbdm_1_1BMEF.html#1331865e10fb1ccef65bb4c47fa3be64" title="forgetting factor">frg</a><1.0 ) {<a class="code" href="classbdm_1_1multiBM.html#044263356944c92209eecd39a5187d25" title="Pointer inside est to sufficient statistics.">beta</a>*=<a class="code" href="classbdm_1_1BMEF.html#1331865e10fb1ccef65bb4c47fa3be64" title="forgetting factor">frg</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_1multiBM.html#9ecc6878abbd20eb8d8e43b6ab3f941a" title="Conjugate prior and posterior.">est</a>.<a class="code" href="classbdm_1_1eDirich.html#279a99f6266c82fe2273e83841f19eb2" title="logarithm of the normalizing constant, ">lognc</a>();}
289	<a name="l00326"></a>00326 <a class="code" href="classbdm_1_1multiBM.html#044263356944c92209eecd39a5187d25" title="Pointer inside est to sufficient statistics.">beta</a>+=dt;
290	<a name="l00327"></a>00327 <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_1BM.html#4064b6559d962633e4372b12f4cd204a" title="Logarithm of marginalized data likelihood.">ll</a>=<a class="code" href="classbdm_1_1multiBM.html#9ecc6878abbd20eb8d8e43b6ab3f941a" title="Conjugate prior and posterior.">est</a>.<a class="code" href="classbdm_1_1eDirich.html#279a99f6266c82fe2273e83841f19eb2" title="logarithm of the normalizing constant, ">lognc</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>;}
291	<a name="l00328"></a>00328 }
292	<a name="l00329"></a><a class="code" href="classbdm_1_1multiBM.html#e157b607c1e3fa91d42aeea44458e2bf">00329</a> <span class="keywordtype">double</span> <a class="code" href="classbdm_1_1multiBM.html#e157b607c1e3fa91d42aeea44458e2bf">logpred</a> ( <span class="keyword">const</span> vec &dt )<span class="keyword"> const</span>
293	<a name="l00330"></a>00330 <span class="keyword"> </span>{
294	<a name="l00331"></a>00331 <a class="code" href="classbdm_1_1eDirich.html" title="Dirichlet posterior density.">eDirich</a> pred ( <a class="code" href="classbdm_1_1multiBM.html#9ecc6878abbd20eb8d8e43b6ab3f941a" title="Conjugate prior and posterior.">est</a> );
295	<a name="l00332"></a>00332 vec &<a class="code" href="classbdm_1_1multiBM.html#044263356944c92209eecd39a5187d25" title="Pointer inside est to sufficient statistics.">beta</a> = pred.<a class="code" href="classbdm_1_1eDirich.html#175e0add26d2105c28d8121eefb9e324" title="access function">_beta</a>();
296	<a name="l00333"></a>00333
297	<a name="l00334"></a>00334 <span class="keywordtype">double</span> lll;
298	<a name="l00335"></a>00335 <span class="keywordflow">if</span> ( <a class="code" href="classbdm_1_1BMEF.html#1331865e10fb1ccef65bb4c47fa3be64" title="forgetting factor">frg</a><1.0 )
299	<a name="l00336"></a>00336 {beta*=<a class="code" href="classbdm_1_1BMEF.html#1331865e10fb1ccef65bb4c47fa3be64" title="forgetting factor">frg</a>;lll=pred.<a class="code" href="classbdm_1_1eDirich.html#279a99f6266c82fe2273e83841f19eb2" title="logarithm of the normalizing constant, ">lognc</a>();}
300	<a name="l00337"></a>00337 <span class="keywordflow">else</span>
301	<a name="l00338"></a>00338 <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> ) {lll=<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>;}
302	<a name="l00339"></a>00339 <span class="keywordflow">else</span>{lll=pred.<a class="code" href="classbdm_1_1eDirich.html#279a99f6266c82fe2273e83841f19eb2" title="logarithm of the normalizing constant, ">lognc</a>();}
303	<a name="l00340"></a>00340
304	<a name="l00341"></a>00341 beta+=dt;
305	<a name="l00342"></a>00342 <span class="keywordflow">return</span> pred.<a class="code" href="classbdm_1_1eDirich.html#279a99f6266c82fe2273e83841f19eb2" title="logarithm of the normalizing constant, ">lognc</a>()-lll;
306	<a name="l00343"></a>00343 }
307	<a name="l00344"></a><a class="code" href="classbdm_1_1multiBM.html#aaeb18c989088feb8d26d300e4971732">00344</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1multiBM.html#aaeb18c989088feb8d26d300e4971732" 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 )
308	<a name="l00345"></a>00345 {
309	<a name="l00346"></a>00346 <span class="keyword">const</span> <a class="code" href="classbdm_1_1multiBM.html" title="Estimator for Multinomial density.">multiBM</a>* E=<span class="keyword">dynamic_cast<</span><span class="keyword">const </span><a class="code" href="classbdm_1_1multiBM.html" title="Estimator for Multinomial density.">multiBM</a>*<span class="keyword">></span> ( B );
310	<a name="l00347"></a>00347 <span class="comment">// sum(beta) should be equal to sum(B.beta)</span>
311	<a name="l00348"></a>00348 <span class="keyword">const</span> vec &Eb=E-><a class="code" href="classbdm_1_1multiBM.html#044263356944c92209eecd39a5187d25" title="Pointer inside est to sufficient statistics.">beta</a>;<span class="comment">//const_cast<multiBM*> ( E )->_beta();</span>
312	<a name="l00349"></a>00349 <a class="code" href="classbdm_1_1multiBM.html#044263356944c92209eecd39a5187d25" title="Pointer inside est to sufficient statistics.">beta</a>*= ( sum ( Eb ) /sum ( <a class="code" href="classbdm_1_1multiBM.html#044263356944c92209eecd39a5187d25" title="Pointer inside est to sufficient statistics.">beta</a> ) );
313	<a name="l00350"></a>00350 <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_1multiBM.html#9ecc6878abbd20eb8d8e43b6ab3f941a" title="Conjugate prior and posterior.">est</a>.<a class="code" href="classbdm_1_1eDirich.html#279a99f6266c82fe2273e83841f19eb2" title="logarithm of the normalizing constant, ">lognc</a>();}
314	<a name="l00351"></a>00351 }
315	<a name="l00352"></a>00352 <span class="keyword">const</span> <a class="code" href="classbdm_1_1epdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a>& posterior()<span class="keyword"> const </span>{<span class="keywordflow">return</span> <a class="code" href="classbdm_1_1multiBM.html#9ecc6878abbd20eb8d8e43b6ab3f941a" title="Conjugate prior and posterior.">est</a>;};
316	<a name="l00353"></a>00353 <span class="keyword">const</span> eDirich* _e()<span class="keyword"> const </span>{<span class="keywordflow">return</span> &<a class="code" href="classbdm_1_1multiBM.html#9ecc6878abbd20eb8d8e43b6ab3f941a" title="Conjugate prior and posterior.">est</a>;};
317	<a name="l00354"></a>00354 <span class="keywordtype">void</span> set_parameters ( <span class="keyword">const</span> vec &beta0 )
318	<a name="l00355"></a>00355 {
319	<a name="l00356"></a>00356 <a class="code" href="classbdm_1_1multiBM.html#9ecc6878abbd20eb8d8e43b6ab3f941a" title="Conjugate prior and posterior.">est</a>.set_parameters ( beta0 );
320	<a name="l00357"></a>00357 <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_1multiBM.html#9ecc6878abbd20eb8d8e43b6ab3f941a" title="Conjugate prior and posterior.">est</a>.lognc();}
321	<a name="l00358"></a>00358 }
322	<a name="l00359"></a>00359 };
323	<a name="l00360"></a>00360
324	<a name="l00370"></a><a class="code" href="classbdm_1_1egamma.html">00370</a> <span class="keyword">class </span><a class="code" href="classbdm_1_1egamma.html" title="Gamma posterior density.">egamma</a> : <span class="keyword">public</span> <a class="code" href="classbdm_1_1eEF.html" title="General conjugate exponential family posterior density.">eEF</a>
325	<a name="l00371"></a>00371 {
326	<a name="l00372"></a>00372 <span class="keyword">protected</span>:
327	<a name="l00374"></a><a class="code" href="classbdm_1_1egamma.html#0901ec983e66b8337aaa506e13b122fa">00374</a> vec <a class="code" href="classbdm_1_1egamma.html#0901ec983e66b8337aaa506e13b122fa" title="Vector .">alpha</a>;
328	<a name="l00376"></a><a class="code" href="classbdm_1_1egamma.html#457bfb1ccb2057df85073e519a15ccc1">00376</a> vec <a class="code" href="classbdm_1_1egamma.html#457bfb1ccb2057df85073e519a15ccc1" title="Vector .">beta</a>;
329	<a name="l00377"></a>00377 <span class="keyword">public</span> :
330	<a name="l00380"></a>00380 <a class="code" href="classbdm_1_1egamma.html" title="Gamma posterior density.">egamma</a> ( ) :<a class="code" href="classbdm_1_1eEF.html" title="General conjugate exponential family posterior density.">eEF</a> ( ), <a class="code" href="classbdm_1_1egamma.html#0901ec983e66b8337aaa506e13b122fa" title="Vector .">alpha</a> ( 0 ), <a class="code" href="classbdm_1_1egamma.html#457bfb1ccb2057df85073e519a15ccc1" title="Vector .">beta</a> ( 0 ) {};
331	<a name="l00381"></a>00381 <a class="code" href="classbdm_1_1egamma.html" title="Gamma posterior density.">egamma</a> ( <span class="keyword">const</span> vec &a, <span class="keyword">const</span> vec &b ) {set_parameters ( a, b );};
332	<a name="l00382"></a>00382 <span class="keywordtype">void</span> set_parameters ( <span class="keyword">const</span> vec &a, <span class="keyword">const</span> vec &b ) {<a class="code" href="classbdm_1_1egamma.html#0901ec983e66b8337aaa506e13b122fa" title="Vector .">alpha</a>=a,<a class="code" href="classbdm_1_1egamma.html#457bfb1ccb2057df85073e519a15ccc1" title="Vector .">beta</a>=b;<a class="code" href="classbdm_1_1epdf.html#16adac20ec7fe07e1ea0b27d917788ce" title="dimension of the random variable">dim</a> = <a class="code" href="classbdm_1_1egamma.html#0901ec983e66b8337aaa506e13b122fa" title="Vector .">alpha</a>.length();};
333	<a name="l00384"></a>00384
334	<a name="l00385"></a>00385 vec <a class="code" href="classbdm_1_1egamma.html#6ed82f0fd05f6002487256d8e75a0bbd" title="Returns a sample, from density .">sample</a>() <span class="keyword">const</span>;
335	<a name="l00387"></a>00387 <span class="comment">// mat sample ( int N ) const;</span>
336	<a name="l00388"></a>00388 <span class="keywordtype">double</span> <a class="code" href="classbdm_1_1egamma.html#a8e11e5a580ff42a1b205974c60768c6" title="TODO: is it used anywhere?">evallog</a> ( <span class="keyword">const</span> vec &val ) <span class="keyword">const</span>;
337	<a name="l00389"></a>00389 <span class="keywordtype">double</span> <a class="code" href="classbdm_1_1egamma.html#9a66cbd100e8520c769ccb3c451f86f8" title="logarithm of the normalizing constant, ">lognc</a> () <span class="keyword">const</span>;
338	<a name="l00391"></a><a class="code" href="classbdm_1_1egamma.html#0865cb3d6339fdc7410806cf70a329ed">00391</a> vec& <a class="code" href="classbdm_1_1egamma.html#0865cb3d6339fdc7410806cf70a329ed" title="Returns poiter to alpha and beta. Potentially dengerous: use with care!">_alpha</a>() {<span class="keywordflow">return</span> <a class="code" href="classbdm_1_1egamma.html#0901ec983e66b8337aaa506e13b122fa" title="Vector .">alpha</a>;}
339	<a name="l00392"></a>00392 vec& _beta() {<span class="keywordflow">return</span> beta;}
340	<a name="l00393"></a><a class="code" href="classbdm_1_1egamma.html#49d256c42cce14c6faa56ec242b57e85">00393</a> vec <a class="code" href="classbdm_1_1egamma.html#49d256c42cce14c6faa56ec242b57e85" title="return expected value">mean</a>()<span class="keyword"> const </span>{<span class="keywordflow">return</span> elem_div ( <a class="code" href="classbdm_1_1egamma.html#0901ec983e66b8337aaa506e13b122fa" title="Vector .">alpha</a>,beta );}
341	<a name="l00394"></a><a class="code" href="classbdm_1_1egamma.html#36986cc01917cd0796fadc17125bdec1">00394</a> vec <a class="code" href="classbdm_1_1egamma.html#36986cc01917cd0796fadc17125bdec1" title="return expected variance (not covariance!)">variance</a>()<span class="keyword"> const </span>{<span class="keywordflow">return</span> elem_div ( <a class="code" href="classbdm_1_1egamma.html#0901ec983e66b8337aaa506e13b122fa" title="Vector .">alpha</a>,elem_mult ( beta,beta ) ); }
342	<a name="l00395"></a>00395
343	<a name="l00404"></a><a class="code" href="classbdm_1_1egamma.html#8a6fd1a1c0190f3e0d95a2a1f99aafc1">00404</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1egamma.html#8a6fd1a1c0190f3e0d95a2a1f99aafc1">from_setting</a>(<span class="keyword">const</span> Setting &<span class="keyword">set</span>){
344	<a name="l00405"></a>00405 <a class="code" href="classbdm_1_1egamma.html#8a6fd1a1c0190f3e0d95a2a1f99aafc1">epdf::from_setting</a>(<span class="keyword">set</span>); <span class="comment">// reads rv</span>
345	<a name="l00406"></a>00406 <a class="code" href="classbdm_1_1UI.html#cd1667e6fec99ec64dabcb3ca2ff922d">UI::get</a>(<a class="code" href="classbdm_1_1egamma.html#0901ec983e66b8337aaa506e13b122fa" title="Vector .">alpha</a>,<span class="keyword">set</span>,<span class="stringliteral">"alpha"</span>, UI::compulsory);
346	<a name="l00407"></a>00407 <a class="code" href="classbdm_1_1UI.html#cd1667e6fec99ec64dabcb3ca2ff922d">UI::get</a>(beta,<span class="keyword">set</span>,<span class="stringliteral">"beta"</span>, UI::compulsory);
347	<a name="l00408"></a>00408 <a class="code" href="classbdm_1_1egamma.html#c3a8d8ae8ba79d0fb35036711fa7d127" title="This method TODO.">validate</a>();
348	<a name="l00409"></a>00409 }
349	<a name="l00410"></a><a class="code" href="classbdm_1_1egamma.html#c3a8d8ae8ba79d0fb35036711fa7d127">00410</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1egamma.html#c3a8d8ae8ba79d0fb35036711fa7d127" title="This method TODO.">validate</a>(){
350	<a name="l00411"></a>00411 it_assert(<a class="code" href="classbdm_1_1egamma.html#0901ec983e66b8337aaa506e13b122fa" title="Vector .">alpha</a>.length() ==beta.length(), <span class="stringliteral">"parameters do not match"</span>);
351	<a name="l00412"></a>00412 <a class="code" href="classbdm_1_1epdf.html#16adac20ec7fe07e1ea0b27d917788ce" title="dimension of the random variable">dim</a> =<a class="code" href="classbdm_1_1egamma.html#0901ec983e66b8337aaa506e13b122fa" title="Vector .">alpha</a>.length();
352	<a name="l00413"></a>00413 }
353	<a name="l00414"></a>00414 };
354	<a name="l00415"></a>00415 <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>(egamma);
355	<a name="l00432"></a><a class="code" href="classbdm_1_1eigamma.html">00432</a> <span class="keyword">class </span><a class="code" href="classbdm_1_1eigamma.html" title="Inverse-Gamma posterior density.">eigamma</a> : <span class="keyword">public</span> <a class="code" href="classbdm_1_1egamma.html" title="Gamma posterior density.">egamma</a>
356	<a name="l00433"></a>00433 {
357	<a name="l00434"></a>00434 <span class="keyword">protected</span>:
358	<a name="l00435"></a>00435 <span class="keyword">public</span> :
359	<a name="l00440"></a>00440
360	<a name="l00441"></a><a class="code" href="classbdm_1_1eigamma.html#3aff7bf25ddac27731c60826fcfd878f">00441</a> vec <a class="code" href="classbdm_1_1eigamma.html#3aff7bf25ddac27731c60826fcfd878f" title="Returns a sample, from density .">sample</a>()<span class="keyword"> const </span>{<span class="keywordflow">return</span> 1.0/<a class="code" href="classbdm_1_1eigamma.html#3aff7bf25ddac27731c60826fcfd878f" title="Returns a sample, from density .">egamma::sample</a>();};
361	<a name="l00443"></a><a class="code" href="classbdm_1_1eigamma.html#46cecb295edbabd28120cb0f6f572bcb">00443</a> vec <a class="code" href="classbdm_1_1eigamma.html#46cecb295edbabd28120cb0f6f572bcb" title="Returns poiter to alpha and beta. Potentially dangerous: use with care!">mean</a>()<span class="keyword"> const </span>{<span class="keywordflow">return</span> elem_div ( <a class="code" href="classbdm_1_1egamma.html#457bfb1ccb2057df85073e519a15ccc1" title="Vector .">beta</a>,<a class="code" href="classbdm_1_1egamma.html#0901ec983e66b8337aaa506e13b122fa" title="Vector .">alpha</a>-1 );}
362	<a name="l00444"></a><a class="code" href="classbdm_1_1eigamma.html#c2c696f8c668e9f65392c9449f6a5133">00444</a> vec <a class="code" href="classbdm_1_1eigamma.html#c2c696f8c668e9f65392c9449f6a5133" title="return expected variance (not covariance!)">variance</a>()<span class="keyword"> const </span>{vec mea=<a class="code" href="classbdm_1_1eigamma.html#46cecb295edbabd28120cb0f6f572bcb" title="Returns poiter to alpha and beta. Potentially dangerous: use with care!">mean</a>(); <span class="keywordflow">return</span> elem_div ( elem_mult ( mea,mea ),<a class="code" href="classbdm_1_1egamma.html#0901ec983e66b8337aaa506e13b122fa" title="Vector .">alpha</a>-2 );}
363	<a name="l00445"></a>00445 };
364	<a name="l00446"></a>00446 <span class="comment">/*</span>
365	<a name="l00448"></a>00448 <span class="comment"> class emix : public epdf {</span>
366	<a name="l00449"></a>00449 <span class="comment"> protected:</span>
367	<a name="l00450"></a>00450 <span class="comment"> int n;</span>
368	<a name="l00451"></a>00451 <span class="comment"> vec &w;</span>
369	<a name="l00452"></a>00452 <span class="comment"> Array<epdf*> Coms;</span>
370	<a name="l00453"></a>00453 <span class="comment"> public:</span>
371	<a name="l00455"></a>00455 <span class="comment"> emix ( const RV &rv, vec &w0): epdf(rv), n(w0.length()), w(w0), Coms(n) {};</span>
372	<a name="l00456"></a>00456 <span class="comment"> void set_parameters( int &i, double wi, epdf* ep){w(i)=wi;Coms(i)=ep;}</span>
373	<a name="l00457"></a>00457 <span class="comment"> vec mean(){vec pom; for(int i=0;i<n;i++){pom+=Coms(i)->mean()*w(i);} return pom;};</span>
374	<a name="l00458"></a>00458 <span class="comment"> vec sample() {it_error ( "Not implemented" );return 0;}</span>
375	<a name="l00459"></a>00459 <span class="comment"> };</span>
376	<a name="l00460"></a>00460 <span class="comment"> */</span>
377	<a name="l00461"></a>00461
378	<a name="l00463"></a>00463
379	<a name="l00464"></a><a class="code" href="classbdm_1_1euni.html">00464</a> <span class="keyword">class </span><a class="code" href="classbdm_1_1euni.html" title="Uniform distributed density on a rectangular support.">euni</a>: <span class="keyword">public</span> <a class="code" href="classbdm_1_1epdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a>
380	<a name="l00465"></a>00465 {
381	<a name="l00466"></a>00466 <span class="keyword">protected</span>:
382	<a name="l00468"></a><a class="code" href="classbdm_1_1euni.html#ff7ce6a2ef5ef0015bbd1398bed12f32">00468</a> vec <a class="code" href="classbdm_1_1euni.html#ff7ce6a2ef5ef0015bbd1398bed12f32" title="lower bound on support">low</a>;
383	<a name="l00470"></a><a class="code" href="classbdm_1_1euni.html#cfad2dea4a62db6872bda8abd75f0de1">00470</a> vec <a class="code" href="classbdm_1_1euni.html#cfad2dea4a62db6872bda8abd75f0de1" title="upper bound on support">high</a>;
384	<a name="l00472"></a><a class="code" href="classbdm_1_1euni.html#d3c27e331f90c754d80228108de8ed4c">00472</a> vec <a class="code" href="classbdm_1_1euni.html#d3c27e331f90c754d80228108de8ed4c" title="internal">distance</a>;
385	<a name="l00474"></a><a class="code" href="classbdm_1_1euni.html#31bb13e8449a8eff35246d46dae35c20">00474</a> <span class="keywordtype">double</span> <a class="code" href="classbdm_1_1euni.html#31bb13e8449a8eff35246d46dae35c20" title="normalizing coefficients">nk</a>;
386	<a name="l00476"></a><a class="code" href="classbdm_1_1euni.html#3e63be48dd58659663ca60cd18700476">00476</a> <span class="keywordtype">double</span> <a class="code" href="classbdm_1_1euni.html#3e63be48dd58659663ca60cd18700476" title="cache of log( nk )">lnk</a>;
387	<a name="l00477"></a>00477 <span class="keyword">public</span>:
388	<a name="l00480"></a>00480 <a class="code" href="classbdm_1_1euni.html" title="Uniform distributed density on a rectangular support.">euni</a> ( ) :<a class="code" href="classbdm_1_1epdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a> ( ) {}
389	<a name="l00481"></a>00481 <a class="code" href="classbdm_1_1euni.html" title="Uniform distributed density on a rectangular support.">euni</a> ( <span class="keyword">const</span> vec &low0, <span class="keyword">const</span> vec &high0 ) {set_parameters ( low0,high0 );}
390	<a name="l00482"></a>00482 <span class="keywordtype">void</span> set_parameters ( <span class="keyword">const</span> vec &low0, <span class="keyword">const</span> vec &high0 )
391	<a name="l00483"></a>00483 {
392	<a name="l00484"></a>00484 <a class="code" href="classbdm_1_1euni.html#d3c27e331f90c754d80228108de8ed4c" title="internal">distance</a> = high0-low0;
393	<a name="l00485"></a>00485 it_assert_debug ( min ( <a class="code" href="classbdm_1_1euni.html#d3c27e331f90c754d80228108de8ed4c" title="internal">distance</a> ) >0.0,<span class="stringliteral">"bad support"</span> );
394	<a name="l00486"></a>00486 <a class="code" href="classbdm_1_1euni.html#ff7ce6a2ef5ef0015bbd1398bed12f32" title="lower bound on support">low</a> = low0;
395	<a name="l00487"></a>00487 <a class="code" href="classbdm_1_1euni.html#cfad2dea4a62db6872bda8abd75f0de1" title="upper bound on support">high</a> = high0;
396	<a name="l00488"></a>00488 <a class="code" href="classbdm_1_1euni.html#31bb13e8449a8eff35246d46dae35c20" title="normalizing coefficients">nk</a> = prod ( 1.0/<a class="code" href="classbdm_1_1euni.html#d3c27e331f90c754d80228108de8ed4c" title="internal">distance</a> );
397	<a name="l00489"></a>00489 <a class="code" href="classbdm_1_1euni.html#3e63be48dd58659663ca60cd18700476" title="cache of log( nk )">lnk</a> = log ( <a class="code" href="classbdm_1_1euni.html#31bb13e8449a8eff35246d46dae35c20" title="normalizing coefficients">nk</a> );
398	<a name="l00490"></a>00490 <a class="code" href="classbdm_1_1epdf.html#16adac20ec7fe07e1ea0b27d917788ce" title="dimension of the random variable">dim</a> = <a class="code" href="classbdm_1_1euni.html#ff7ce6a2ef5ef0015bbd1398bed12f32" title="lower bound on support">low</a>.length();
399	<a name="l00491"></a>00491 }
400	<a name="l00493"></a>00493
401	<a name="l00494"></a>00494 <span class="keywordtype">double</span> eval ( <span class="keyword">const</span> vec &val )<span class="keyword"> const </span>{<span class="keywordflow">return</span> <a class="code" href="classbdm_1_1euni.html#31bb13e8449a8eff35246d46dae35c20" title="normalizing coefficients">nk</a>;}
402	<a name="l00495"></a><a class="code" href="classbdm_1_1euni.html#caa07b8307bd793d5339d6583e0aba81">00495</a> <span class="keywordtype">double</span> <a class="code" href="classbdm_1_1euni.html#caa07b8307bd793d5339d6583e0aba81">evallog</a> ( <span class="keyword">const</span> vec &val )<span class="keyword"> const </span>{
403	<a name="l00496"></a>00496 <span class="keywordflow">if</span> (any(val<<a class="code" href="classbdm_1_1euni.html#ff7ce6a2ef5ef0015bbd1398bed12f32" title="lower bound on support">low</a>) && any(val><a class="code" href="classbdm_1_1euni.html#cfad2dea4a62db6872bda8abd75f0de1" title="upper bound on support">high</a>)) {<span class="keywordflow">return</span> inf;}
404	<a name="l00497"></a>00497 <span class="keywordflow">else</span> <span class="keywordflow">return</span> <a class="code" href="classbdm_1_1euni.html#3e63be48dd58659663ca60cd18700476" title="cache of log( nk )">lnk</a>;
405	<a name="l00498"></a>00498 }
406	<a name="l00499"></a><a class="code" href="classbdm_1_1euni.html#fc5df80359ead2918384b2004ce67194">00499</a> vec <a class="code" href="classbdm_1_1euni.html#fc5df80359ead2918384b2004ce67194" title="Returns a sample, from density .">sample</a>()<span class="keyword"> const</span>
407	<a name="l00500"></a>00500 <span class="keyword"> </span>{
408	<a name="l00501"></a>00501 vec smp ( <a class="code" href="classbdm_1_1epdf.html#16adac20ec7fe07e1ea0b27d917788ce" title="dimension of the random variable">dim</a> );
409	<a name="l00502"></a>00502 <span class="preprocessor">#pragma omp critical</span>
410	<a name="l00503"></a>00503 <span class="preprocessor"></span> UniRNG.sample_vector ( <a class="code" href="classbdm_1_1epdf.html#16adac20ec7fe07e1ea0b27d917788ce" title="dimension of the random variable">dim</a> ,smp );
411	<a name="l00504"></a>00504 <span class="keywordflow">return</span> <a class="code" href="classbdm_1_1euni.html#ff7ce6a2ef5ef0015bbd1398bed12f32" title="lower bound on support">low</a>+elem_mult ( <a class="code" href="classbdm_1_1euni.html#d3c27e331f90c754d80228108de8ed4c" title="internal">distance</a>,smp );
412	<a name="l00505"></a>00505 }
413	<a name="l00507"></a><a class="code" href="classbdm_1_1euni.html#46caa8c13aba2e6228f964208918b226">00507</a> vec <a class="code" href="classbdm_1_1euni.html#46caa8c13aba2e6228f964208918b226" title="set values of low and high ">mean</a>()<span class="keyword"> const </span>{<span class="keywordflow">return</span> ( <a class="code" href="classbdm_1_1euni.html#cfad2dea4a62db6872bda8abd75f0de1" title="upper bound on support">high</a>-<a class="code" href="classbdm_1_1euni.html#ff7ce6a2ef5ef0015bbd1398bed12f32" title="lower bound on support">low</a> ) /2.0;}
414	<a name="l00508"></a><a class="code" href="classbdm_1_1euni.html#951f932155111f6053c980f672b4c22c">00508</a> vec <a class="code" href="classbdm_1_1euni.html#951f932155111f6053c980f672b4c22c" title="return expected variance (not covariance!)">variance</a>()<span class="keyword"> const </span>{<span class="keywordflow">return</span> ( pow ( <a class="code" href="classbdm_1_1euni.html#cfad2dea4a62db6872bda8abd75f0de1" title="upper bound on support">high</a>,2 ) +pow ( <a class="code" href="classbdm_1_1euni.html#ff7ce6a2ef5ef0015bbd1398bed12f32" title="lower bound on support">low</a>,2 ) +elem_mult ( <a class="code" href="classbdm_1_1euni.html#cfad2dea4a62db6872bda8abd75f0de1" title="upper bound on support">high</a>,<a class="code" href="classbdm_1_1euni.html#ff7ce6a2ef5ef0015bbd1398bed12f32" title="lower bound on support">low</a> ) ) /3.0;}
415	<a name="l00517"></a><a class="code" href="classbdm_1_1euni.html#77f5fef1f006fe056066da23b9e5f042">00517</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1euni.html#77f5fef1f006fe056066da23b9e5f042">from_setting</a>(<span class="keyword">const</span> Setting &<span class="keyword">set</span>){
416	<a name="l00518"></a>00518 <a class="code" href="classbdm_1_1euni.html#77f5fef1f006fe056066da23b9e5f042">epdf::from_setting</a>(<span class="keyword">set</span>); <span class="comment">// reads rv and rvc</span>
417	<a name="l00519"></a>00519
418	<a name="l00520"></a>00520 <a class="code" href="classbdm_1_1UI.html#cd1667e6fec99ec64dabcb3ca2ff922d">UI::get</a>(<a class="code" href="classbdm_1_1euni.html#cfad2dea4a62db6872bda8abd75f0de1" title="upper bound on support">high</a>,<span class="keyword">set</span>,<span class="stringliteral">"high"</span>, UI::compulsory);
419	<a name="l00521"></a>00521 <a class="code" href="classbdm_1_1UI.html#cd1667e6fec99ec64dabcb3ca2ff922d">UI::get</a>(<a class="code" href="classbdm_1_1euni.html#ff7ce6a2ef5ef0015bbd1398bed12f32" title="lower bound on support">low</a>,<span class="keyword">set</span>,<span class="stringliteral">"low"</span>, UI::compulsory);
420	<a name="l00522"></a>00522 }
421	<a name="l00523"></a>00523 };
422	<a name="l00524"></a>00524
423	<a name="l00525"></a>00525
424	<a name="l00531"></a>00531 <span class="keyword">template</span><<span class="keyword">class</span> sq_T>
425	<a name="l00532"></a><a class="code" href="classbdm_1_1mlnorm.html">00532</a> <span class="keyword">class </span><a class="code" href="classbdm_1_1mlnorm.html" title="Normal distributed linear function with linear function of mean value;.">mlnorm</a> : <span class="keyword">public</span> <a class="code" href="classbdm_1_1mEF.html" title="Exponential family model.">mEF</a>
426	<a name="l00533"></a>00533 {
427	<a name="l00534"></a>00534 <span class="keyword">protected</span>:
428	<a name="l00536"></a><a class="code" href="classbdm_1_1mlnorm.html#6de45ab731143e70a94318df586c36ba">00536</a> <a class="code" href="classbdm_1_1shared__ptr.html" title="A naive implementation of roughly a subset of the std::tr1:shared_ptr spec (really...">shared_ptr<enorm<sq_T></a> > <a class="code" href="classbdm_1_1mlnorm.html#6de45ab731143e70a94318df586c36ba" title="Internal epdf that arise by conditioning on rvc.">iepdf</a>;
429	<a name="l00537"></a>00537 mat A;
430	<a name="l00538"></a>00538 vec mu_const;
431	<a name="l00539"></a>00539 vec& _mu; <span class="comment">//cached epdf.mu;</span>
432	<a name="l00540"></a>00540 <span class="keyword">public</span>:
433	<a name="l00543"></a>00543 <a class="code" href="classbdm_1_1mlnorm.html" title="Normal distributed linear function with linear function of mean value;.">mlnorm</a>():<a class="code" href="classbdm_1_1mlnorm.html#6de45ab731143e70a94318df586c36ba" title="Internal epdf that arise by conditioning on rvc.">iepdf</a>(new <a class="code" href="classbdm_1_1enorm.html" title="Gaussian density with positive definite (decomposed) covariance matrix.">enorm</a><sq_T>()), _mu(<a class="code" href="classbdm_1_1mlnorm.html#6de45ab731143e70a94318df586c36ba" title="Internal epdf that arise by conditioning on rvc.">iepdf</a>->_mu()) { set_ep(<a class="code" href="classbdm_1_1mlnorm.html#6de45ab731143e70a94318df586c36ba" title="Internal epdf that arise by conditioning on rvc.">iepdf</a>); };
434	<a name="l00544"></a>00544 <a class="code" href="classbdm_1_1mlnorm.html" title="Normal distributed linear function with linear function of mean value;.">mlnorm</a> (<span class="keyword">const</span> mat &A, <span class="keyword">const</span> vec &mu0, <span class="keyword">const</span> sq_T &R ) :<a class="code" href="classbdm_1_1mlnorm.html#6de45ab731143e70a94318df586c36ba" title="Internal epdf that arise by conditioning on rvc.">iepdf</a>(new <a class="code" href="classbdm_1_1enorm.html" title="Gaussian density with positive definite (decomposed) covariance matrix.">enorm</a><sq_T>()), _mu(<a class="code" href="classbdm_1_1mlnorm.html#6de45ab731143e70a94318df586c36ba" title="Internal epdf that arise by conditioning on rvc.">iepdf</a>->_mu())
435	<a name="l00545"></a>00545 {
436	<a name="l00546"></a>00546 set_ep(<a class="code" href="classbdm_1_1mlnorm.html#6de45ab731143e70a94318df586c36ba" title="Internal epdf that arise by conditioning on rvc.">iepdf</a>); <a class="code" href="classbdm_1_1mlnorm.html#5d18dec3167584338a4775c1d165d96f" title="Set A and R.">set_parameters</a> ( A,mu0,R );
437	<a name="l00547"></a>00547 }
438	<a name="l00548"></a>00548
439	<a name="l00550"></a>00550 <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1mlnorm.html#5d18dec3167584338a4775c1d165d96f" title="Set A and R.">set_parameters</a> ( <span class="keyword">const</span> mat &A, <span class="keyword">const</span> vec &mu0, <span class="keyword">const</span> sq_T &R );
440	<a name="l00553"></a>00553 <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1mlnorm.html#0dafc0196e7e07fd06dc6716e0e18bc2">condition</a> ( <span class="keyword">const</span> vec &cond );
441	<a name="l00554"></a>00554
442	<a name="l00556"></a><a class="code" href="classbdm_1_1mlnorm.html#56e587952f94fcac6cfc999eae6dbced">00556</a> vec& <a class="code" href="classbdm_1_1mlnorm.html#56e587952f94fcac6cfc999eae6dbced" title="access function">_mu_const</a>() {<span class="keywordflow">return</span> mu_const;}
443	<a name="l00558"></a><a class="code" href="classbdm_1_1mlnorm.html#262a2a486bff585f34bb6a5005b02614">00558</a> mat& <a class="code" href="classbdm_1_1mlnorm.html#262a2a486bff585f34bb6a5005b02614" title="access function">_A</a>() {<span class="keywordflow">return</span> A;}
444	<a name="l00560"></a><a class="code" href="classbdm_1_1mlnorm.html#78120ecd1c2b1d7e80124b4603504604">00560</a> mat <a class="code" href="classbdm_1_1mlnorm.html#78120ecd1c2b1d7e80124b4603504604" title="access function">_R</a>() { <span class="keywordflow">return</span> <a class="code" href="classbdm_1_1mlnorm.html#6de45ab731143e70a94318df586c36ba" title="Internal epdf that arise by conditioning on rvc.">iepdf</a>->_R().to_mat(); }
445	<a name="l00561"></a>00561
446	<a name="l00562"></a>00562 <span class="keyword">template</span><<span class="keyword">class</span> sq_M>
447	<a name="l00563"></a>00563 <span class="keyword">friend</span> std::ostream &operator<< ( std::ostream &os, mlnorm<sq_M> &ml );
448	<a name="l00564"></a>00564
449	<a name="l00565"></a><a class="code" href="classbdm_1_1mlnorm.html#8582928555c309a2865f385dd0441fd1">00565</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1mlnorm.html#8582928555c309a2865f385dd0441fd1">from_setting</a>(<span class="keyword">const</span> Setting &<span class="keyword">set</span>){
450	<a name="l00566"></a>00566 <a class="code" href="classbdm_1_1mlnorm.html#8582928555c309a2865f385dd0441fd1">mpdf::from_setting</a>(<span class="keyword">set</span>);
451	<a name="l00567"></a>00567
452	<a name="l00568"></a>00568 <a class="code" href="classbdm_1_1UI.html#cd1667e6fec99ec64dabcb3ca2ff922d">UI::get</a>(A,<span class="keyword">set</span>,<span class="stringliteral">"A"</span>, UI::compulsory);
453	<a name="l00569"></a>00569 <a class="code" href="classbdm_1_1UI.html#cd1667e6fec99ec64dabcb3ca2ff922d">UI::get</a>(mu_const,<span class="keyword">set</span>,<span class="stringliteral">"const"</span>, UI::compulsory);
454	<a name="l00570"></a>00570 mat R0;
455	<a name="l00571"></a>00571 <a class="code" href="classbdm_1_1UI.html#cd1667e6fec99ec64dabcb3ca2ff922d">UI::get</a>(R0,<span class="keyword">set</span>,<span class="stringliteral">"R"</span>, UI::compulsory);
456	<a name="l00572"></a>00572 <a class="code" href="classbdm_1_1mlnorm.html#5d18dec3167584338a4775c1d165d96f" title="Set A and R.">set_parameters</a>(A,mu_const,R0);
457	<a name="l00573"></a>00573 };
458	<a name="l00574"></a>00574 };
459	<a name="l00575"></a>00575 <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>(mlnorm<ldmat>);
460	<a name="l00576"></a>00576 <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>(mlnorm<fsqmat>);
461	<a name="l00577"></a>00577 <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>(mlnorm<chmat>);
462	<a name="l00578"></a>00578
463	<a name="l00580"></a>00580 <span class="keyword">template</span><<span class="keyword">class</span> sq_T>
464	<a name="l00581"></a><a class="code" href="classbdm_1_1mgnorm.html">00581</a> <span class="keyword">class </span><a class="code" href="classbdm_1_1mgnorm.html" title="Mpdf with general function for mean value.">mgnorm</a> : <span class="keyword">public</span> <a class="code" href="classbdm_1_1mEF.html" title="Exponential family model.">mEF</a>
465	<a name="l00582"></a>00582 {
466	<a name="l00583"></a>00583 <span class="keyword">protected</span>:
467	<a name="l00585"></a><a class="code" href="classbdm_1_1mgnorm.html#e63ba612a75f761c03025d22463219cb">00585</a> <a class="code" href="classbdm_1_1shared__ptr.html" title="A naive implementation of roughly a subset of the std::tr1:shared_ptr spec (really...">shared_ptr<enorm<sq_T></a> > <a class="code" href="classbdm_1_1mgnorm.html#e63ba612a75f761c03025d22463219cb" title="Internal epdf that arise by conditioning on rvc.">iepdf</a>;
468	<a name="l00586"></a>00586 vec &mu;
469	<a name="l00587"></a>00587 <a class="code" href="classbdm_1_1fnc.html" title="Class representing function of variable represented by rv.">fnc</a>* g;
470	<a name="l00588"></a>00588 <span class="keyword">public</span>:
471	<a name="l00590"></a><a class="code" href="classbdm_1_1mgnorm.html#1b014915d74470d3efab74e07cacb97d">00590</a> <a class="code" href="classbdm_1_1mgnorm.html#1b014915d74470d3efab74e07cacb97d" title="default constructor">mgnorm</a>():<a class="code" href="classbdm_1_1mgnorm.html#e63ba612a75f761c03025d22463219cb" title="Internal epdf that arise by conditioning on rvc.">iepdf</a>(new <a class="code" href="classbdm_1_1enorm.html" title="Gaussian density with positive definite (decomposed) covariance matrix.">enorm</a><sq_T>()), mu(<a class="code" href="classbdm_1_1mgnorm.html#e63ba612a75f761c03025d22463219cb" title="Internal epdf that arise by conditioning on rvc.">iepdf</a>->_mu()) { set_ep(<a class="code" href="classbdm_1_1mgnorm.html#e63ba612a75f761c03025d22463219cb" title="Internal epdf that arise by conditioning on rvc.">iepdf</a>); }
472	<a name="l00592"></a><a class="code" href="classbdm_1_1mgnorm.html#578e02458e2a0d17f3864826b6ebd564">00592</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1mgnorm.html#578e02458e2a0d17f3864826b6ebd564" title="set mean function">set_parameters</a> ( <a class="code" href="classbdm_1_1fnc.html" title="Class representing function of variable represented by rv.">fnc</a>* g0, <span class="keyword">const</span> sq_T &R0 ) {g=g0; <a class="code" href="classbdm_1_1mgnorm.html#e63ba612a75f761c03025d22463219cb" title="Internal epdf that arise by conditioning on rvc.">iepdf</a>->set_parameters ( zeros ( g-><a class="code" href="classbdm_1_1fnc.html#083832294da9d1e40804158b979c4341" title="access function">dimension</a>() ), R0 );}
473	<a name="l00593"></a><a class="code" href="classbdm_1_1mgnorm.html#b31d63472cf6a1030cd8dbd8094c1f6d">00593</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1mgnorm.html#b31d63472cf6a1030cd8dbd8094c1f6d" title="Update ep so that it represents this mpdf conditioned on rvc = cond.">condition</a> ( <span class="keyword">const</span> vec &cond ) {mu=g-><a class="code" href="classbdm_1_1fnc.html#6277b11d7fffc7ef8a2fa3e84ae5bad4" title="function evaluates numerical value of at cond ">eval</a> ( cond );};
474	<a name="l00594"></a>00594
475	<a name="l00595"></a>00595
476	<a name="l00623"></a><a class="code" href="classbdm_1_1mgnorm.html#d717dacc6a9eb967f8410994dc6dc6f9">00623</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1mgnorm.html#d717dacc6a9eb967f8410994dc6dc6f9">from_setting</a>( <span class="keyword">const</span> Setting &<span class="keyword">set</span> )
477	<a name="l00624"></a>00624 {
478	<a name="l00625"></a>00625 <a class="code" href="classbdm_1_1fnc.html" title="Class representing function of variable represented by rv.">fnc</a>* g = UI::build<fnc>( <span class="keyword">set</span>, <span class="stringliteral">"g"</span>, UI::compulsory );
479	<a name="l00626"></a>00626
480	<a name="l00627"></a>00627 mat R;
481	<a name="l00628"></a>00628 vec dR;
482	<a name="l00629"></a>00629 <span class="keywordflow">if</span> ( <a class="code" href="classbdm_1_1UI.html#cd1667e6fec99ec64dabcb3ca2ff922d">UI::get</a>( dR, <span class="keyword">set</span>, <span class="stringliteral">"dR"</span> ) )
483	<a name="l00630"></a>00630 R=diag(dR);
484	<a name="l00631"></a>00631 <span class="keywordflow">else</span>
485	<a name="l00632"></a>00632 <a class="code" href="classbdm_1_1UI.html#cd1667e6fec99ec64dabcb3ca2ff922d">UI::get</a>( R, <span class="keyword">set</span>, <span class="stringliteral">"R"</span>, UI::compulsory);
486	<a name="l00633"></a>00633
487	<a name="l00634"></a>00634 <a class="code" href="classbdm_1_1mgnorm.html#578e02458e2a0d17f3864826b6ebd564" title="set mean function">set_parameters</a>(g,R);
488	<a name="l00635"></a>00635 }
489	<a name="l00636"></a>00636 };
490	<a name="l00637"></a>00637
491	<a name="l00638"></a>00638 <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>(mgnorm<chmat>);
492	<a name="l00639"></a>00639
493	<a name="l00640"></a>00640
494	<a name="l00648"></a><a class="code" href="classbdm_1_1mlstudent.html">00648</a> <span class="keyword">class </span><a class="code" href="classbdm_1_1mlstudent.html">mlstudent</a> : <span class="keyword">public</span> <a class="code" href="classbdm_1_1mlnorm.html" title="Normal distributed linear function with linear function of mean value;.">mlnorm</a><ldmat>
495	<a name="l00649"></a>00649 {
496	<a name="l00650"></a>00650 <span class="keyword">protected</span>:
497	<a name="l00651"></a>00651 <a class="code" href="classldmat.html" title="Matrix stored in LD form, (commonly known as UD).">ldmat</a> Lambda;
498	<a name="l00652"></a>00652 <a class="code" href="classldmat.html" title="Matrix stored in LD form, (commonly known as UD).">ldmat</a> &<a class="code" href="classbdm_1_1mlnorm.html#78120ecd1c2b1d7e80124b4603504604" title="access function">_R</a>;
499	<a name="l00653"></a>00653 <a class="code" href="classldmat.html" title="Matrix stored in LD form, (commonly known as UD).">ldmat</a> Re;
500	<a name="l00654"></a>00654 <span class="keyword">public</span>:
501	<a name="l00655"></a>00655 <a class="code" href="classbdm_1_1mlstudent.html">mlstudent</a> ( ) :<a class="code" href="classbdm_1_1mlnorm.html">mlnorm<ldmat></a> (),
502	<a name="l00656"></a>00656 Lambda (), <a class="code" href="classbdm_1_1mlnorm.html#78120ecd1c2b1d7e80124b4603504604" title="access function">_R</a> ( <a class="code" href="classbdm_1_1mlnorm.html#6de45ab731143e70a94318df586c36ba" title="Internal epdf that arise by conditioning on rvc.">iepdf</a>->_R() ) {}
503	<a name="l00657"></a>00657 <span class="keywordtype">void</span> set_parameters ( <span class="keyword">const</span> mat &A0, <span class="keyword">const</span> vec &mu0, <span class="keyword">const</span> <a class="code" href="classldmat.html" title="Matrix stored in LD form, (commonly known as UD).">ldmat</a> &R0, <span class="keyword">const</span> <a class="code" href="classldmat.html" title="Matrix stored in LD form, (commonly known as UD).">ldmat</a>& Lambda0 )
504	<a name="l00658"></a>00658 {
505	<a name="l00659"></a>00659 it_assert_debug ( A0.rows() ==mu0.length(),<span class="stringliteral">""</span> );
506	<a name="l00660"></a>00660 it_assert_debug ( R0.<a class="code" href="classsqmat.html#071e80ced9cc3b8cbb360fa7462eb646" title="Reimplementing common functions of mat: rows().">rows</a>() ==A0.rows(),<span class="stringliteral">""</span> );
507	<a name="l00661"></a>00661
508	<a name="l00662"></a>00662 <a class="code" href="classbdm_1_1mlnorm.html#6de45ab731143e70a94318df586c36ba" title="Internal epdf that arise by conditioning on rvc.">iepdf</a>->set_parameters ( mu0,Lambda ); <span class="comment">//</span>
509	<a name="l00663"></a>00663 A = A0;
510	<a name="l00664"></a>00664 mu_const = mu0;
511	<a name="l00665"></a>00665 Re=R0;
512	<a name="l00666"></a>00666 Lambda = Lambda0;
513	<a name="l00667"></a>00667 }
514	<a name="l00668"></a><a class="code" href="classbdm_1_1mlstudent.html#efd37560585c8613897f30d3c2f58d0d">00668</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1mlstudent.html#efd37560585c8613897f30d3c2f58d0d">condition</a> ( <span class="keyword">const</span> vec &cond )
515	<a name="l00669"></a>00669 {
516	<a name="l00670"></a>00670 _mu = A*cond + mu_const;
517	<a name="l00671"></a>00671 <span class="keywordtype">double</span> zeta;
518	<a name="l00672"></a>00672 <span class="comment">//ugly hack!</span>
519	<a name="l00673"></a>00673 <span class="keywordflow">if</span> ( ( cond.length() +1 ) ==Lambda.<a class="code" href="classsqmat.html#071e80ced9cc3b8cbb360fa7462eb646" title="Reimplementing common functions of mat: rows().">rows</a>() )
520	<a name="l00674"></a>00674 {
521	<a name="l00675"></a>00675 zeta = Lambda.<a class="code" href="classldmat.html#d876c5f83e02b3e809b35c9de5068f14" title="Evaluates quadratic form ;.">invqform</a> ( concat ( cond, vec_1 ( 1.0 ) ) );
522	<a name="l00676"></a>00676 }
523	<a name="l00677"></a>00677 <span class="keywordflow">else</span>
524	<a name="l00678"></a>00678 {
525	<a name="l00679"></a>00679 zeta = Lambda.<a class="code" href="classldmat.html#d876c5f83e02b3e809b35c9de5068f14" title="Evaluates quadratic form ;.">invqform</a> ( cond );
526	<a name="l00680"></a>00680 }
527	<a name="l00681"></a>00681 <a class="code" href="classbdm_1_1mlnorm.html#78120ecd1c2b1d7e80124b4603504604" title="access function">_R</a> = Re;
528	<a name="l00682"></a>00682 <a class="code" href="classbdm_1_1mlnorm.html#78120ecd1c2b1d7e80124b4603504604" title="access function">_R</a>*= ( 1+zeta );<span class="comment">// / ( nu ); << nu is in Re!!!!!!</span>
529	<a name="l00683"></a>00683 };
530	<a name="l00684"></a>00684
531	<a name="l00685"></a>00685 };
532	<a name="l00695"></a><a class="code" href="classbdm_1_1mgamma.html">00695</a> <span class="keyword">class </span><a class="code" href="classbdm_1_1mgamma.html" title="Gamma random walk.">mgamma</a> : <span class="keyword">public</span> <a class="code" href="classbdm_1_1mEF.html" title="Exponential family model.">mEF</a>
533	<a name="l00696"></a>00696 {
534	<a name="l00697"></a>00697 <span class="keyword">protected</span>:
535	<a name="l00699"></a><a class="code" href="classbdm_1_1mgamma.html#413aa1c71b58a71d64c08da3aa642c08">00699</a> <a class="code" href="classbdm_1_1shared__ptr.html">shared_ptr<egamma></a> <a class="code" href="classbdm_1_1mgamma.html#413aa1c71b58a71d64c08da3aa642c08" title="Internal epdf that arise by conditioning on rvc.">iepdf</a>;
536	<a name="l00700"></a>00700
537	<a name="l00702"></a><a class="code" href="classbdm_1_1mgamma.html#b20cf88cca1fe9b0b8f2a412608bfd09">00702</a> <span class="keywordtype">double</span> <a class="code" href="classbdm_1_1mgamma.html#b20cf88cca1fe9b0b8f2a412608bfd09" title="Constant .">k</a>;
538	<a name="l00703"></a>00703
539	<a name="l00705"></a><a class="code" href="classbdm_1_1mgamma.html#3d95f4dde9214ff6dba265e18af60312">00705</a> vec &<a class="code" href="classbdm_1_1mgamma.html#3d95f4dde9214ff6dba265e18af60312" title="cache of iepdf.beta">_beta</a>;
540	<a name="l00706"></a>00706
541	<a name="l00707"></a>00707 <span class="keyword">public</span>:
542	<a name="l00709"></a><a class="code" href="classbdm_1_1mgamma.html#1a9dc8661e5b214a8185d6e6b9956eb1">00709</a> <a class="code" href="classbdm_1_1mgamma.html#1a9dc8661e5b214a8185d6e6b9956eb1" title="Constructor.">mgamma</a>():<a class="code" href="classbdm_1_1mgamma.html#413aa1c71b58a71d64c08da3aa642c08" title="Internal epdf that arise by conditioning on rvc.">iepdf</a>(new <a class="code" href="classbdm_1_1egamma.html" title="Gamma posterior density.">egamma</a>()), <a class="code" href="classbdm_1_1mgamma.html#b20cf88cca1fe9b0b8f2a412608bfd09" title="Constant .">k</a>(0),
543	<a name="l00710"></a>00710 <a class="code" href="classbdm_1_1mgamma.html#3d95f4dde9214ff6dba265e18af60312" title="cache of iepdf.beta">_beta</a>(<a class="code" href="classbdm_1_1mgamma.html#413aa1c71b58a71d64c08da3aa642c08" title="Internal epdf that arise by conditioning on rvc.">iepdf</a>-><a class="code" href="classbdm_1_1mgamma.html#3d95f4dde9214ff6dba265e18af60312" title="cache of iepdf.beta">_beta</a>()) {
544	<a name="l00711"></a>00711 set_ep(<a class="code" href="classbdm_1_1mgamma.html#413aa1c71b58a71d64c08da3aa642c08" title="Internal epdf that arise by conditioning on rvc.">iepdf</a>);
545	<a name="l00712"></a>00712 }
546	<a name="l00713"></a>00713
547	<a name="l00715"></a>00715 <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1mgamma.html#a0f21c2557b233a85838b497d040ab14" title="Set value of k.">set_parameters</a>(<span class="keywordtype">double</span> <a class="code" href="classbdm_1_1mgamma.html#b20cf88cca1fe9b0b8f2a412608bfd09" title="Constant .">k</a>, <span class="keyword">const</span> vec &beta0);
548	<a name="l00716"></a>00716
549	<a name="l00717"></a><a class="code" href="classbdm_1_1mgamma.html#8996500f1885e39cde30221b20900bff">00717</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1mgamma.html#8996500f1885e39cde30221b20900bff" title="Update ep so that it represents this mpdf conditioned on rvc = cond.">condition</a> ( <span class="keyword">const</span> vec &val ) {<a class="code" href="classbdm_1_1mgamma.html#3d95f4dde9214ff6dba265e18af60312" title="cache of iepdf.beta">_beta</a>=<a class="code" href="classbdm_1_1mgamma.html#b20cf88cca1fe9b0b8f2a412608bfd09" title="Constant .">k</a>/val;};
550	<a name="l00727"></a><a class="code" href="classbdm_1_1mgamma.html#da2af0f327e5452bee71d1bf97452ae4">00727</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1mgamma.html#da2af0f327e5452bee71d1bf97452ae4">from_setting</a>(<span class="keyword">const</span> Setting &<span class="keyword">set</span>){
551	<a name="l00728"></a>00728 <a class="code" href="classbdm_1_1mgamma.html#da2af0f327e5452bee71d1bf97452ae4">mpdf::from_setting</a>(<span class="keyword">set</span>); <span class="comment">// reads rv and rvc</span>
552	<a name="l00729"></a>00729 vec betatmp; <span class="comment">// ugly but necessary</span>
553	<a name="l00730"></a>00730 <a class="code" href="classbdm_1_1UI.html#cd1667e6fec99ec64dabcb3ca2ff922d">UI::get</a>(betatmp,<span class="keyword">set</span>,<span class="stringliteral">"beta"</span>, UI::compulsory);
554	<a name="l00731"></a>00731 <a class="code" href="classbdm_1_1UI.html#cd1667e6fec99ec64dabcb3ca2ff922d">UI::get</a>(<a class="code" href="classbdm_1_1mgamma.html#b20cf88cca1fe9b0b8f2a412608bfd09" title="Constant .">k</a>,<span class="keyword">set</span>,<span class="stringliteral">"k"</span>, UI::compulsory);
555	<a name="l00732"></a>00732 <a class="code" href="classbdm_1_1mgamma.html#a0f21c2557b233a85838b497d040ab14" title="Set value of k.">set_parameters</a>(<a class="code" href="classbdm_1_1mgamma.html#b20cf88cca1fe9b0b8f2a412608bfd09" title="Constant .">k</a>,betatmp);
556	<a name="l00733"></a>00733 }
557	<a name="l00734"></a>00734 };
558	<a name="l00735"></a>00735 <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>(mgamma);
559	<a name="l00736"></a>00736
560	<a name="l00746"></a><a class="code" href="classbdm_1_1migamma.html">00746</a> <span class="keyword">class </span><a class="code" href="classbdm_1_1migamma.html" title="Inverse-Gamma random walk.">migamma</a> : <span class="keyword">public</span> <a class="code" href="classbdm_1_1mEF.html" title="Exponential family model.">mEF</a>
561	<a name="l00747"></a>00747 {
562	<a name="l00748"></a>00748 <span class="keyword">protected</span>:
563	<a name="l00750"></a><a class="code" href="classbdm_1_1migamma.html#f1636dbded763fecbd1c6a22dc6971fa">00750</a> <a class="code" href="classbdm_1_1shared__ptr.html">shared_ptr<eigamma></a> <a class="code" href="classbdm_1_1migamma.html#f1636dbded763fecbd1c6a22dc6971fa" title="Internal epdf that arise by conditioning on rvc.">iepdf</a>;
564	<a name="l00751"></a>00751
565	<a name="l00753"></a><a class="code" href="classbdm_1_1migamma.html#dc56bc9da542e0103ec16b9be8e5e38c">00753</a> <span class="keywordtype">double</span> <a class="code" href="classbdm_1_1migamma.html#dc56bc9da542e0103ec16b9be8e5e38c" title="Constant .">k</a>;
566	<a name="l00754"></a>00754
567	<a name="l00756"></a><a class="code" href="classbdm_1_1migamma.html#c9847093da59a9ba0ebb68d2c592f5dc">00756</a> vec &<a class="code" href="classbdm_1_1migamma.html#c9847093da59a9ba0ebb68d2c592f5dc" title="cache of iepdf.alpha">_alpha</a>;
568	<a name="l00757"></a>00757
569	<a name="l00759"></a><a class="code" href="classbdm_1_1migamma.html#0d854c047001b5465cf1ba21f52904b5">00759</a> vec &<a class="code" href="classbdm_1_1migamma.html#0d854c047001b5465cf1ba21f52904b5" title="cache of iepdf.beta">_beta</a>;
570	<a name="l00760"></a>00760
571	<a name="l00761"></a>00761 <span class="keyword">public</span>:
572	<a name="l00764"></a>00764 <a class="code" href="classbdm_1_1migamma.html" title="Inverse-Gamma random walk.">migamma</a>():<a class="code" href="classbdm_1_1migamma.html#f1636dbded763fecbd1c6a22dc6971fa" title="Internal epdf that arise by conditioning on rvc.">iepdf</a>(new <a class="code" href="classbdm_1_1eigamma.html" title="Inverse-Gamma posterior density.">eigamma</a>()),
573	<a name="l00765"></a>00765 <a class="code" href="classbdm_1_1migamma.html#dc56bc9da542e0103ec16b9be8e5e38c" title="Constant .">k</a>(0),
574	<a name="l00766"></a>00766 <a class="code" href="classbdm_1_1migamma.html#c9847093da59a9ba0ebb68d2c592f5dc" title="cache of iepdf.alpha">_alpha</a>(<a class="code" href="classbdm_1_1migamma.html#f1636dbded763fecbd1c6a22dc6971fa" title="Internal epdf that arise by conditioning on rvc.">iepdf</a>-><a class="code" href="classbdm_1_1migamma.html#c9847093da59a9ba0ebb68d2c592f5dc" title="cache of iepdf.alpha">_alpha</a>()),
575	<a name="l00767"></a>00767 <a class="code" href="classbdm_1_1migamma.html#0d854c047001b5465cf1ba21f52904b5" title="cache of iepdf.beta">_beta</a>(<a class="code" href="classbdm_1_1migamma.html#f1636dbded763fecbd1c6a22dc6971fa" title="Internal epdf that arise by conditioning on rvc.">iepdf</a>-><a class="code" href="classbdm_1_1migamma.html#0d854c047001b5465cf1ba21f52904b5" title="cache of iepdf.beta">_beta</a>()) {
576	<a name="l00768"></a>00768 set_ep(<a class="code" href="classbdm_1_1migamma.html#f1636dbded763fecbd1c6a22dc6971fa" title="Internal epdf that arise by conditioning on rvc.">iepdf</a>);
577	<a name="l00769"></a>00769 }
578	<a name="l00770"></a>00770
579	<a name="l00771"></a>00771 <a class="code" href="classbdm_1_1migamma.html" title="Inverse-Gamma random walk.">migamma</a>(<span class="keyword">const</span> <a class="code" href="classbdm_1_1migamma.html" title="Inverse-Gamma random walk.">migamma</a> &m):<a class="code" href="classbdm_1_1migamma.html#f1636dbded763fecbd1c6a22dc6971fa" title="Internal epdf that arise by conditioning on rvc.">iepdf</a>(m.<a class="code" href="classbdm_1_1migamma.html#f1636dbded763fecbd1c6a22dc6971fa" title="Internal epdf that arise by conditioning on rvc.">iepdf</a>),
580	<a name="l00772"></a>00772 <a class="code" href="classbdm_1_1migamma.html#dc56bc9da542e0103ec16b9be8e5e38c" title="Constant .">k</a>(0),
581	<a name="l00773"></a>00773 <a class="code" href="classbdm_1_1migamma.html#c9847093da59a9ba0ebb68d2c592f5dc" title="cache of iepdf.alpha">_alpha</a>(<a class="code" href="classbdm_1_1migamma.html#f1636dbded763fecbd1c6a22dc6971fa" title="Internal epdf that arise by conditioning on rvc.">iepdf</a>-><a class="code" href="classbdm_1_1migamma.html#c9847093da59a9ba0ebb68d2c592f5dc" title="cache of iepdf.alpha">_alpha</a>()),
582	<a name="l00774"></a>00774 <a class="code" href="classbdm_1_1migamma.html#0d854c047001b5465cf1ba21f52904b5" title="cache of iepdf.beta">_beta</a>(<a class="code" href="classbdm_1_1migamma.html#f1636dbded763fecbd1c6a22dc6971fa" title="Internal epdf that arise by conditioning on rvc.">iepdf</a>-><a class="code" href="classbdm_1_1migamma.html#0d854c047001b5465cf1ba21f52904b5" title="cache of iepdf.beta">_beta</a>()) {
583	<a name="l00775"></a>00775 set_ep(<a class="code" href="classbdm_1_1migamma.html#f1636dbded763fecbd1c6a22dc6971fa" title="Internal epdf that arise by conditioning on rvc.">iepdf</a>);
584	<a name="l00776"></a>00776 }
585	<a name="l00778"></a>00778
586	<a name="l00780"></a><a class="code" href="classbdm_1_1migamma.html#8b10ab922e2a7bae2fb6bb3efc7b6151">00780</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1migamma.html#8b10ab922e2a7bae2fb6bb3efc7b6151" title="Set value of k.">set_parameters</a> ( <span class="keywordtype">int</span> len, <span class="keywordtype">double</span> k0 )
587	<a name="l00781"></a>00781 {
588	<a name="l00782"></a>00782 <a class="code" href="classbdm_1_1migamma.html#dc56bc9da542e0103ec16b9be8e5e38c" title="Constant .">k</a>=k0;
589	<a name="l00783"></a>00783 <a class="code" href="classbdm_1_1migamma.html#f1636dbded763fecbd1c6a22dc6971fa" title="Internal epdf that arise by conditioning on rvc.">iepdf</a>->set_parameters ( ( 1.0/ ( <a class="code" href="classbdm_1_1migamma.html#dc56bc9da542e0103ec16b9be8e5e38c" title="Constant .">k</a><a class="code" href="classbdm_1_1migamma.html#dc56bc9da542e0103ec16b9be8e5e38c" title="Constant .">k</a> ) +2.0 ) ones ( len ) <span class="comment">/alpha/</span>, ones ( len ) <span class="comment">/beta/</span> );
590	<a name="l00784"></a>00784 <a class="code" href="classbdm_1_1mpdf.html#7c1900976ff13dbc09c9729b3bbff9e6" title="dimension of the condition">dimc</a> = dimension();
591	<a name="l00785"></a>00785 };
592	<a name="l00786"></a><a class="code" href="classbdm_1_1migamma.html#7a34b1e2e3aa2250d7c0ed7df1665b8c">00786</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1migamma.html#7a34b1e2e3aa2250d7c0ed7df1665b8c" title="Update ep so that it represents this mpdf conditioned on rvc = cond.">condition</a> ( <span class="keyword">const</span> vec &val )
593	<a name="l00787"></a>00787 {
594	<a name="l00788"></a>00788 <a class="code" href="classbdm_1_1migamma.html#0d854c047001b5465cf1ba21f52904b5" title="cache of iepdf.beta">_beta</a>=elem_mult ( val, ( <a class="code" href="classbdm_1_1migamma.html#c9847093da59a9ba0ebb68d2c592f5dc" title="cache of iepdf.alpha">_alpha</a>-1.0 ) );
595	<a name="l00789"></a>00789 };
596	<a name="l00790"></a>00790 };
597	<a name="l00791"></a>00791
598	<a name="l00792"></a>00792
599	<a name="l00804"></a><a class="code" href="classbdm_1_1mgamma__fix.html">00804</a> <span class="keyword">class </span><a class="code" href="classbdm_1_1mgamma__fix.html" title="Gamma random walk around a fixed point.">mgamma_fix</a> : <span class="keyword">public</span> <a class="code" href="classbdm_1_1mgamma.html" title="Gamma random walk.">mgamma</a>
600	<a name="l00805"></a>00805 {
601	<a name="l00806"></a>00806 <span class="keyword">protected</span>:
602	<a name="l00808"></a><a class="code" href="classbdm_1_1mgamma__fix.html#1eb701506aabb2e6af007e487212d6fa">00808</a> <span class="keywordtype">double</span> <a class="code" href="classbdm_1_1mgamma__fix.html#1eb701506aabb2e6af007e487212d6fa" title="parameter l">l</a>;
603	<a name="l00810"></a><a class="code" href="classbdm_1_1mgamma__fix.html#018c6f901a04e419455308a07eb3b0b2">00810</a> vec <a class="code" href="classbdm_1_1mgamma__fix.html#018c6f901a04e419455308a07eb3b0b2" title="reference vector">refl</a>;
604	<a name="l00811"></a>00811 <span class="keyword">public</span>:
605	<a name="l00813"></a><a class="code" href="classbdm_1_1mgamma__fix.html#9a31bc9b4b60188a18a2a6b588dc4b2d">00813</a> <a class="code" href="classbdm_1_1mgamma__fix.html#9a31bc9b4b60188a18a2a6b588dc4b2d" title="Constructor.">mgamma_fix</a> ( ) : <a class="code" href="classbdm_1_1mgamma.html" title="Gamma random walk.">mgamma</a> ( ),<a class="code" href="classbdm_1_1mgamma__fix.html#018c6f901a04e419455308a07eb3b0b2" title="reference vector">refl</a> () {};
606	<a name="l00815"></a><a class="code" href="classbdm_1_1mgamma__fix.html#1bfd30e90db9dc1fbda4a9fbb0b716b2">00815</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1mgamma__fix.html#1bfd30e90db9dc1fbda4a9fbb0b716b2" title="Set value of k.">set_parameters</a> ( <span class="keywordtype">double</span> k0 , vec ref0, <span class="keywordtype">double</span> l0 )
607	<a name="l00816"></a>00816 {
608	<a name="l00817"></a>00817 <a class="code" href="classbdm_1_1mgamma__fix.html#1bfd30e90db9dc1fbda4a9fbb0b716b2" title="Set value of k.">mgamma::set_parameters</a> ( k0, ref0 );
609	<a name="l00818"></a>00818 <a class="code" href="classbdm_1_1mgamma__fix.html#018c6f901a04e419455308a07eb3b0b2" title="reference vector">refl</a>=pow ( ref0,1.0-l0 );<a class="code" href="classbdm_1_1mgamma__fix.html#1eb701506aabb2e6af007e487212d6fa" title="parameter l">l</a>=l0;
610	<a name="l00819"></a>00819 <a class="code" href="classbdm_1_1mpdf.html#7c1900976ff13dbc09c9729b3bbff9e6" title="dimension of the condition">dimc</a>=dimension();
611	<a name="l00820"></a>00820 };
612	<a name="l00821"></a>00821
613	<a name="l00822"></a><a class="code" href="classbdm_1_1mgamma__fix.html#1d539591deb7a38bb3403c2b396c8ff7">00822</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1mgamma__fix.html#1d539591deb7a38bb3403c2b396c8ff7" title="Update ep so that it represents this mpdf conditioned on rvc = cond.">condition</a> ( <span class="keyword">const</span> vec &val ) {vec mean=elem_mult ( <a class="code" href="classbdm_1_1mgamma__fix.html#018c6f901a04e419455308a07eb3b0b2" title="reference vector">refl</a>,pow ( val,<a class="code" href="classbdm_1_1mgamma__fix.html#1eb701506aabb2e6af007e487212d6fa" title="parameter l">l</a> ) ); <a class="code" href="classbdm_1_1mgamma.html#3d95f4dde9214ff6dba265e18af60312" title="cache of iepdf.beta">_beta</a>=<a class="code" href="classbdm_1_1mgamma.html#b20cf88cca1fe9b0b8f2a412608bfd09" title="Constant .">k</a>/mean;};
614	<a name="l00823"></a>00823 };
615	<a name="l00824"></a>00824
616	<a name="l00825"></a>00825
617	<a name="l00838"></a><a class="code" href="classbdm_1_1migamma__ref.html">00838</a> <span class="keyword">class </span><a class="code" href="classbdm_1_1migamma__ref.html" title="Inverse-Gamma random walk around a fixed point.">migamma_ref</a> : <span class="keyword">public</span> <a class="code" href="classbdm_1_1migamma.html" title="Inverse-Gamma random walk.">migamma</a>
618	<a name="l00839"></a>00839 {
619	<a name="l00840"></a>00840 <span class="keyword">protected</span>:
620	<a name="l00842"></a><a class="code" href="classbdm_1_1migamma__ref.html#cdc1345ba8375fbdb18a69322d2f841d">00842</a> <span class="keywordtype">double</span> <a class="code" href="classbdm_1_1migamma__ref.html#cdc1345ba8375fbdb18a69322d2f841d" title="parameter l">l</a>;
621	<a name="l00844"></a><a class="code" href="classbdm_1_1migamma__ref.html#3692dc67caf4367e15564d37f45476f6">00844</a> vec <a class="code" href="classbdm_1_1migamma__ref.html#3692dc67caf4367e15564d37f45476f6" title="reference vector">refl</a>;
622	<a name="l00845"></a>00845 <span class="keyword">public</span>:
623	<a name="l00847"></a><a class="code" href="classbdm_1_1migamma__ref.html#f45b15a10f084991ba6b48295f10421f">00847</a> <a class="code" href="classbdm_1_1migamma__ref.html#f45b15a10f084991ba6b48295f10421f" title="Constructor.">migamma_ref</a> ( ) : <a class="code" href="classbdm_1_1migamma.html" title="Inverse-Gamma random walk.">migamma</a> (),<a class="code" href="classbdm_1_1migamma__ref.html#3692dc67caf4367e15564d37f45476f6" title="reference vector">refl</a> ( ) {};
624	<a name="l00849"></a><a class="code" href="classbdm_1_1migamma__ref.html#b0b4eb278ef5d0831ec4954ba7bd2800">00849</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1migamma__ref.html#b0b4eb278ef5d0831ec4954ba7bd2800" title="Set value of k.">set_parameters</a> ( <span class="keywordtype">double</span> k0 , vec ref0, <span class="keywordtype">double</span> l0 )
625	<a name="l00850"></a>00850 {
626	<a name="l00851"></a>00851 <a class="code" href="classbdm_1_1migamma__ref.html#b0b4eb278ef5d0831ec4954ba7bd2800" title="Set value of k.">migamma::set_parameters</a> ( ref0.length(), k0 );
627	<a name="l00852"></a>00852 <a class="code" href="classbdm_1_1migamma__ref.html#3692dc67caf4367e15564d37f45476f6" title="reference vector">refl</a>=pow ( ref0,1.0-l0 );
628	<a name="l00853"></a>00853 <a class="code" href="classbdm_1_1migamma__ref.html#cdc1345ba8375fbdb18a69322d2f841d" title="parameter l">l</a>=l0;
629	<a name="l00854"></a>00854 <a class="code" href="classbdm_1_1mpdf.html#7c1900976ff13dbc09c9729b3bbff9e6" title="dimension of the condition">dimc</a> = dimension();
630	<a name="l00855"></a>00855 };
631	<a name="l00856"></a>00856
632	<a name="l00857"></a><a class="code" href="classbdm_1_1migamma__ref.html#ae86b2e4ff963d62e05d4e130514634a">00857</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1migamma__ref.html#ae86b2e4ff963d62e05d4e130514634a" title="Update ep so that it represents this mpdf conditioned on rvc = cond.">condition</a> ( <span class="keyword">const</span> vec &val )
633	<a name="l00858"></a>00858 {
634	<a name="l00859"></a>00859 vec mean=elem_mult ( <a class="code" href="classbdm_1_1migamma__ref.html#3692dc67caf4367e15564d37f45476f6" title="reference vector">refl</a>,pow ( val,<a class="code" href="classbdm_1_1migamma__ref.html#cdc1345ba8375fbdb18a69322d2f841d" title="parameter l">l</a> ) );
635	<a name="l00860"></a>00860 <a class="code" href="classbdm_1_1migamma__ref.html#ae86b2e4ff963d62e05d4e130514634a" title="Update ep so that it represents this mpdf conditioned on rvc = cond.">migamma::condition</a> ( mean );
636	<a name="l00861"></a>00861 };
637	<a name="l00862"></a>00862
638	<a name="l00883"></a>00883 <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1migamma__ref.html#9e7e0f7d2aa9ecca8ec1af8cbcb5ef1d">from_setting</a>( <span class="keyword">const</span> Setting &<span class="keyword">set</span> );
639	<a name="l00884"></a>00884
640	<a name="l00885"></a>00885 <span class="comment">// TODO dodelat void to_setting( Setting &set ) const;</span>
641	<a name="l00886"></a>00886 };
642	<a name="l00887"></a>00887
643	<a name="l00888"></a>00888
644	<a name="l00889"></a>00889 <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>(migamma_ref);
645	<a name="l00890"></a>00890
646	<a name="l00900"></a><a class="code" href="classbdm_1_1elognorm.html">00900</a> <span class="keyword">class </span><a class="code" href="classbdm_1_1elognorm.html">elognorm</a>: <span class="keyword">public</span> <a class="code" href="classbdm_1_1enorm.html" title="Gaussian density with positive definite (decomposed) covariance matrix.">enorm</a><ldmat>
647	<a name="l00901"></a>00901 {
648	<a name="l00902"></a>00902 <span class="keyword">public</span>:
649	<a name="l00903"></a><a class="code" href="classbdm_1_1elognorm.html#8b948e2bce1253765a2542199913aaba">00903</a> vec <a class="code" href="classbdm_1_1elognorm.html#8b948e2bce1253765a2542199913aaba" title="Returns a sample, from density .">sample</a>()<span class="keyword"> const </span>{<span class="keywordflow">return</span> exp ( <a class="code" href="classbdm_1_1enorm.html" title="Gaussian density with positive definite (decomposed) covariance matrix.">enorm<ldmat>::sample</a>() );};
650	<a name="l00904"></a><a class="code" href="classbdm_1_1elognorm.html#adb41e4f4d6600dec6f8c1dbc5ed9eea">00904</a> vec <a class="code" href="classbdm_1_1elognorm.html#adb41e4f4d6600dec6f8c1dbc5ed9eea" title="return expected value">mean</a>()<span class="keyword"> const </span>{vec var=<a class="code" href="classbdm_1_1enorm.html#729c75ef0fa8abae03d58ad1f81e6773" title="return expected variance (not covariance!)">enorm<ldmat>::variance</a>();<span class="keywordflow">return</span> exp ( <a class="code" href="classbdm_1_1enorm.html#c702a194720853570d08b65482f842c7" title="mean value">mu</a> - 0.5*var );};
651	<a name="l00905"></a>00905
652	<a name="l00906"></a>00906 };
653	<a name="l00907"></a>00907
654	<a name="l00919"></a><a class="code" href="classbdm_1_1mlognorm.html">00919</a> <span class="keyword">class </span><a class="code" href="classbdm_1_1mlognorm.html" title="Log-Normal random walk.">mlognorm</a> : <span class="keyword">public</span> <a class="code" href="classbdm_1_1mpdf.html" title="Conditional probability density, e.g. modeling some dependencies.">mpdf</a>
655	<a name="l00920"></a>00920 {
656	<a name="l00921"></a>00921 <span class="keyword">protected</span>:
657	<a name="l00922"></a>00922 <a class="code" href="classbdm_1_1shared__ptr.html">shared_ptr<elognorm></a> eno;
658	<a name="l00923"></a>00923
659	<a name="l00925"></a><a class="code" href="classbdm_1_1mlognorm.html#a51128a2e503b8b2ce698244b9e0db1a">00925</a> <span class="keywordtype">double</span> <a class="code" href="classbdm_1_1mlognorm.html#a51128a2e503b8b2ce698244b9e0db1a" title="parameter 1/2*sigma^2">sig2</a>;
660	<a name="l00926"></a>00926
661	<a name="l00928"></a><a class="code" href="classbdm_1_1mlognorm.html#7d0063f77d899ef22e8c5edd642176d2">00928</a> vec &<a class="code" href="classbdm_1_1mlognorm.html#7d0063f77d899ef22e8c5edd642176d2" title="access">mu</a>;
662	<a name="l00929"></a>00929 <span class="keyword">public</span>:
663	<a name="l00931"></a><a class="code" href="classbdm_1_1mlognorm.html#a5d6eb2688d02e0348b96c4fbd7bde41">00931</a> <a class="code" href="classbdm_1_1mlognorm.html#a5d6eb2688d02e0348b96c4fbd7bde41" title="Constructor.">mlognorm</a>():eno(new <a class="code" href="classbdm_1_1elognorm.html">elognorm</a>()),
664	<a name="l00932"></a>00932 <a class="code" href="classbdm_1_1mlognorm.html#a51128a2e503b8b2ce698244b9e0db1a" title="parameter 1/2*sigma^2">sig2</a>(0),
665	<a name="l00933"></a>00933 <a class="code" href="classbdm_1_1mlognorm.html#7d0063f77d899ef22e8c5edd642176d2" title="access">mu</a>(eno->_mu()) {
666	<a name="l00934"></a>00934 set_ep(eno);
667	<a name="l00935"></a>00935 }
668	<a name="l00936"></a>00936
669	<a name="l00938"></a><a class="code" href="classbdm_1_1mlognorm.html#604cab0e8a76f9041dc3c606043bb39f">00938</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1mlognorm.html#604cab0e8a76f9041dc3c606043bb39f" title="Set value of k.">set_parameters</a> ( <span class="keywordtype">int</span> size, <span class="keywordtype">double</span> k )
670	<a name="l00939"></a>00939 {
671	<a name="l00940"></a>00940 <a class="code" href="classbdm_1_1mlognorm.html#a51128a2e503b8b2ce698244b9e0db1a" title="parameter 1/2sigma^2">sig2</a> = 0.5log ( k*k+1 );
672	<a name="l00941"></a>00941 eno->set_parameters ( zeros ( size ),2<a class="code" href="classbdm_1_1mlognorm.html#a51128a2e503b8b2ce698244b9e0db1a" title="parameter 1/2sigma^2">sig2</a>*eye ( size ) );
673	<a name="l00942"></a>00942
674	<a name="l00943"></a>00943 <a class="code" href="classbdm_1_1mpdf.html#7c1900976ff13dbc09c9729b3bbff9e6" title="dimension of the condition">dimc</a> = size;
675	<a name="l00944"></a>00944 };
676	<a name="l00945"></a>00945
677	<a name="l00946"></a><a class="code" href="classbdm_1_1mlognorm.html#9106d8fd8bdf2b6be675ffd8f3ca584e">00946</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1mlognorm.html#9106d8fd8bdf2b6be675ffd8f3ca584e" title="Update ep so that it represents this mpdf conditioned on rvc = cond.">condition</a> ( <span class="keyword">const</span> vec &val )
678	<a name="l00947"></a>00947 {
679	<a name="l00948"></a>00948 <a class="code" href="classbdm_1_1mlognorm.html#7d0063f77d899ef22e8c5edd642176d2" title="access">mu</a>=log ( val )-<a class="code" href="classbdm_1_1mlognorm.html#a51128a2e503b8b2ce698244b9e0db1a" title="parameter 1/2*sigma^2">sig2</a>;<span class="comment">//elem_mult ( refl,pow ( val,l ) );</span>
680	<a name="l00949"></a>00949 };
681	<a name="l00950"></a>00950
682	<a name="l00969"></a>00969 <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1mlognorm.html#49e45ea13a869da607ef9be7a229128a">from_setting</a>( <span class="keyword">const</span> Setting &<span class="keyword">set</span> );
683	<a name="l00970"></a>00970
684	<a name="l00971"></a>00971 <span class="comment">// TODO dodelat void to_setting( Setting &set ) const;</span>
685	<a name="l00972"></a>00972
686	<a name="l00973"></a>00973 };
687	<a name="l00974"></a>00974
688	<a name="l00975"></a>00975 <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>(mlognorm);
689	<a name="l00976"></a>00976
690	<a name="l00980"></a><a class="code" href="classbdm_1_1eWishartCh.html">00980</a> <span class="keyword">class </span><a class="code" href="classbdm_1_1eWishartCh.html">eWishartCh</a> : <span class="keyword">public</span> <a class="code" href="classbdm_1_1epdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a>
691	<a name="l00981"></a>00981 {
692	<a name="l00982"></a>00982 <span class="keyword">protected</span>:
693	<a name="l00984"></a><a class="code" href="classbdm_1_1eWishartCh.html#1b42f9284a32f23b0b253a628cda7490">00984</a> <a class="code" href="classchmat.html" title="Symmetric matrix stored in square root decomposition using upper cholesky.">chmat</a> <a class="code" href="classbdm_1_1eWishartCh.html#1b42f9284a32f23b0b253a628cda7490" title="Upper-Triagle of Choleski decomposition of .">Y</a>;
694	<a name="l00986"></a><a class="code" href="classbdm_1_1eWishartCh.html#b745c73faef785009484180582050a1f">00986</a> <span class="keywordtype">int</span> <a class="code" href="classbdm_1_1eWishartCh.html#b745c73faef785009484180582050a1f" title="dimension of matrix ">p</a>;
695	<a name="l00988"></a><a class="code" href="classbdm_1_1eWishartCh.html#1879a14d7d2bb05062523b189baa11c3">00988</a> <span class="keywordtype">double</span> <a class="code" href="classbdm_1_1eWishartCh.html#1879a14d7d2bb05062523b189baa11c3" title="degrees of freedom ">delta</a>;
696	<a name="l00989"></a>00989 <span class="keyword">public</span>:
697	<a name="l00990"></a>00990 <span class="keywordtype">void</span> set_parameters ( <span class="keyword">const</span> mat &Y0, <span class="keyword">const</span> <span class="keywordtype">double</span> delta0 ) {<a class="code" href="classbdm_1_1eWishartCh.html#1b42f9284a32f23b0b253a628cda7490" title="Upper-Triagle of Choleski decomposition of .">Y</a>=<a class="code" href="classchmat.html" title="Symmetric matrix stored in square root decomposition using upper cholesky.">chmat</a> ( Y0 );<a class="code" href="classbdm_1_1eWishartCh.html#1879a14d7d2bb05062523b189baa11c3" title="degrees of freedom ">delta</a>=delta0; <a class="code" href="classbdm_1_1eWishartCh.html#b745c73faef785009484180582050a1f" title="dimension of matrix ">p</a>=<a class="code" href="classbdm_1_1eWishartCh.html#1b42f9284a32f23b0b253a628cda7490" title="Upper-Triagle of Choleski decomposition of .">Y</a>.<a class="code" href="classsqmat.html#071e80ced9cc3b8cbb360fa7462eb646" title="Reimplementing common functions of mat: rows().">rows</a>(); <a class="code" href="classbdm_1_1epdf.html#16adac20ec7fe07e1ea0b27d917788ce" title="dimension of the random variable">dim</a> = <a class="code" href="classbdm_1_1eWishartCh.html#b745c73faef785009484180582050a1f" title="dimension of matrix ">p</a>*<a class="code" href="classbdm_1_1eWishartCh.html#b745c73faef785009484180582050a1f" title="dimension of matrix ">p</a>; }
698	<a name="l00991"></a>00991 mat sample_mat()<span class="keyword"> const</span>
699	<a name="l00992"></a>00992 <span class="keyword"> </span>{
700	<a name="l00993"></a>00993 mat X=zeros ( <a class="code" href="classbdm_1_1eWishartCh.html#b745c73faef785009484180582050a1f" title="dimension of matrix ">p</a>,<a class="code" href="classbdm_1_1eWishartCh.html#b745c73faef785009484180582050a1f" title="dimension of matrix ">p</a> );
701	<a name="l00994"></a>00994
702	<a name="l00995"></a>00995 <span class="comment">//sample diagonal</span>
703	<a name="l00996"></a>00996 <span class="keywordflow">for</span> ( <span class="keywordtype">int</span> i=0;i<<a class="code" href="classbdm_1_1eWishartCh.html#b745c73faef785009484180582050a1f" title="dimension of matrix ">p</a>;i++ )
704	<a name="l00997"></a>00997 {
705	<a name="l00998"></a>00998 GamRNG.<a class="code" href="classitpp_1_1Gamma__RNG.html#dfaae19411e39aa87e1f72e409b6babe" title="Set lambda.">setup</a> ( 0.5* ( <a class="code" href="classbdm_1_1eWishartCh.html#1879a14d7d2bb05062523b189baa11c3" title="degrees of freedom ">delta</a>-i ) , 0.5 ); <span class="comment">// no +1 !! index if from 0</span>
706	<a name="l00999"></a>00999 <span class="preprocessor">#pragma omp critical</span>
707	<a name="l01000"></a>01000 <span class="preprocessor"></span> X ( i,i ) =sqrt ( GamRNG() );
708	<a name="l01001"></a>01001 }
709	<a name="l01002"></a>01002 <span class="comment">//do the rest</span>
710	<a name="l01003"></a>01003 <span class="keywordflow">for</span> ( <span class="keywordtype">int</span> i=0;i<p;i++ )
711	<a name="l01004"></a>01004 {
712	<a name="l01005"></a>01005 <span class="keywordflow">for</span> ( <span class="keywordtype">int</span> j=i+1;j<p;j++ )
713	<a name="l01006"></a>01006 {
714	<a name="l01007"></a>01007 <span class="preprocessor">#pragma omp critical</span>
715	<a name="l01008"></a>01008 <span class="preprocessor"></span> X ( i,j ) =NorRNG.sample();
716	<a name="l01009"></a>01009 }
717	<a name="l01010"></a>01010 }
718	<a name="l01011"></a>01011 <span class="keywordflow">return</span> X*<a class="code" href="classbdm_1_1eWishartCh.html#1b42f9284a32f23b0b253a628cda7490" title="Upper-Triagle of Choleski decomposition of .">Y</a>.<a class="code" href="classchmat.html#9c50d31c999d85d8e9d8cf2b69b6ac8c" title="Access function.">_Ch</a>();<span class="comment">// return upper triangular part of the decomposition</span>
719	<a name="l01012"></a>01012 }
720	<a name="l01013"></a><a class="code" href="classbdm_1_1eWishartCh.html#8f2154b8b5be8f4c5788f261b6d57b9a">01013</a> vec <a class="code" href="classbdm_1_1eWishartCh.html#8f2154b8b5be8f4c5788f261b6d57b9a" title="Returns a sample, from density .">sample</a> ()<span class="keyword"> const</span>
721	<a name="l01014"></a>01014 <span class="keyword"> </span>{
722	<a name="l01015"></a>01015 <span class="keywordflow">return</span> vec ( sample_mat()._data(),p*p );
723	<a name="l01016"></a>01016 }
724	<a name="l01018"></a><a class="code" href="classbdm_1_1eWishartCh.html#4eee757c0535c2a88bb20f0767c64981">01018</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1eWishartCh.html#4eee757c0535c2a88bb20f0767c64981" title="fast access function y0 will be copied into Y.Ch.">setY</a> ( <span class="keyword">const</span> mat &Ch0 ) {copy_vector ( <a class="code" href="classbdm_1_1epdf.html#16adac20ec7fe07e1ea0b27d917788ce" title="dimension of the random variable">dim</a>,Ch0._data(), <a class="code" href="classbdm_1_1eWishartCh.html#1b42f9284a32f23b0b253a628cda7490" title="Upper-Triagle of Choleski decomposition of .">Y</a>.<a class="code" href="classchmat.html#9c50d31c999d85d8e9d8cf2b69b6ac8c" title="Access function.">_Ch</a>()._data() );}
725	<a name="l01020"></a><a class="code" href="classbdm_1_1eWishartCh.html#7eac414ec10b85aa5536b0092c57bc4a">01020</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1eWishartCh.html#7eac414ec10b85aa5536b0092c57bc4a" title="fast access function y0 will be copied into Y.Ch.">_setY</a> ( <span class="keyword">const</span> vec &ch0 ) {copy_vector ( <a class="code" href="classbdm_1_1epdf.html#16adac20ec7fe07e1ea0b27d917788ce" title="dimension of the random variable">dim</a>, ch0._data(), <a class="code" href="classbdm_1_1eWishartCh.html#1b42f9284a32f23b0b253a628cda7490" title="Upper-Triagle of Choleski decomposition of .">Y</a>.<a class="code" href="classchmat.html#9c50d31c999d85d8e9d8cf2b69b6ac8c" title="Access function.">_Ch</a>()._data() ); }
726	<a name="l01022"></a><a class="code" href="classbdm_1_1eWishartCh.html#1708cacb5d8cb1b96395d35f5327cb7e">01022</a> <span class="keyword">const</span> <a class="code" href="classchmat.html" title="Symmetric matrix stored in square root decomposition using upper cholesky.">chmat</a>& <a class="code" href="classbdm_1_1eWishartCh.html#1708cacb5d8cb1b96395d35f5327cb7e" title="access function">getY</a>()<span class="keyword">const </span>{<span class="keywordflow">return</span> <a class="code" href="classbdm_1_1eWishartCh.html#1b42f9284a32f23b0b253a628cda7490" title="Upper-Triagle of Choleski decomposition of .">Y</a>;}
727	<a name="l01023"></a>01023 };
728	<a name="l01024"></a>01024
729	<a name="l01025"></a>01025 <span class="keyword">class </span>eiWishartCh: <span class="keyword">public</span> epdf
730	<a name="l01026"></a>01026 {
731	<a name="l01027"></a>01027 <span class="keyword">protected</span>:
732	<a name="l01028"></a>01028 eWishartCh W;
733	<a name="l01029"></a>01029 <span class="keywordtype">int</span> p;
734	<a name="l01030"></a>01030 <span class="keywordtype">double</span> delta;
735	<a name="l01031"></a>01031 <span class="keyword">public</span>:
736	<a name="l01032"></a>01032 <span class="keywordtype">void</span> set_parameters ( <span class="keyword">const</span> mat &Y0, <span class="keyword">const</span> <span class="keywordtype">double</span> delta0) {
737	<a name="l01033"></a>01033 delta = delta0;
738	<a name="l01034"></a>01034 W.set_parameters ( inv ( Y0 ),delta0 );
739	<a name="l01035"></a>01035 dim = W.dimension(); p=Y0.rows();
740	<a name="l01036"></a>01036 }
741	<a name="l01037"></a>01037 vec sample()<span class="keyword"> const </span>{mat iCh; iCh=inv ( W.sample_mat() ); <span class="keywordflow">return</span> vec ( iCh._data(),<a class="code" href="classbdm_1_1epdf.html#16adac20ec7fe07e1ea0b27d917788ce" title="dimension of the random variable">dim</a> );}
742	<a name="l01038"></a>01038 <span class="keywordtype">void</span> _setY ( <span class="keyword">const</span> vec &y0 )
743	<a name="l01039"></a>01039 {
744	<a name="l01040"></a>01040 mat Ch ( p,p );
745	<a name="l01041"></a>01041 mat iCh ( p,p );
746	<a name="l01042"></a>01042 copy_vector ( dim, y0._data(), Ch._data() );
747	<a name="l01043"></a>01043
748	<a name="l01044"></a>01044 iCh=inv ( Ch );
749	<a name="l01045"></a>01045 W.setY ( iCh );
750	<a name="l01046"></a>01046 }
751	<a name="l01047"></a>01047 <span class="keyword">virtual</span> <span class="keywordtype">double</span> evallog ( <span class="keyword">const</span> vec &val )<span class="keyword"> const </span>{
752	<a name="l01048"></a>01048 <a class="code" href="classchmat.html" title="Symmetric matrix stored in square root decomposition using upper cholesky.">chmat</a> X(p);
753	<a name="l01049"></a>01049 <span class="keyword">const</span> <a class="code" href="classchmat.html" title="Symmetric matrix stored in square root decomposition using upper cholesky.">chmat</a>& Y=W.getY();
754	<a name="l01050"></a>01050
755	<a name="l01051"></a>01051 copy_vector(p*p,val._data(),X._Ch()._data());
756	<a name="l01052"></a>01052 <a class="code" href="classchmat.html" title="Symmetric matrix stored in square root decomposition using upper cholesky.">chmat</a> iX(p);X.inv(iX);
757	<a name="l01053"></a>01053 <span class="comment">// compute </span>
758	<a name="l01054"></a>01054 <span class="comment">// \frac{ \|\Psi\|^{m/2}\|X\|^{-(m+p+1)/2}e^{-tr(\Psi X^{-1})/2} }{ 2^{mp/2}\Gamma_p(m/2)},</span>
759	<a name="l01055"></a>01055 mat M=Y.<a class="code" href="classchmat.html#045addd685f8d978efda232d7dcb070e" title="Conversion to full matrix.">to_mat</a>()*iX.to_mat();
760	<a name="l01056"></a>01056
761	<a name="l01057"></a>01057 <span class="keywordtype">double</span> log1 = 0.5p(2Y.<a class="code" href="classchmat.html#b504ca818203b13e667cb3c503980382" title="Logarithm of a determinant.">logdet</a>())-0.5(delta+p+1)(2X.logdet())-0.5*trace(M);
762	<a name="l01058"></a>01058 <span class="comment">//Fixme! Multivariate gamma omitted!! it is ok for sampling, but not otherwise!!</span>
763	<a name="l01059"></a>01059
764	<a name="l01060"></a>01060 <span class="comment">/* if (0) {</span>
765	<a name="l01061"></a>01061 <span class="comment"> mat XX=X.to_mat();</span>
766	<a name="l01062"></a>01062 <span class="comment"> mat YY=Y.to_mat();</span>
767	<a name="l01063"></a>01063 <span class="comment"> </span>
768	<a name="l01064"></a>01064 <span class="comment"> double log2 = 0.5plog(det(YY))-0.5(delta+p+1)log(det(XX))-0.5trace(YYinv(XX)); </span>
769	<a name="l01065"></a>01065 <span class="comment"> cout << log1 << "," << log2 << endl;</span>
770	<a name="l01066"></a>01066 <span class="comment"> }*/</span>
771	<a name="l01067"></a>01067 <span class="keywordflow">return</span> log1;
772	<a name="l01068"></a>01068 };
773	<a name="l01069"></a>01069
774	<a name="l01070"></a>01070 };
775	<a name="l01071"></a>01071
776	<a name="l01072"></a>01072 <span class="keyword">class </span>rwiWishartCh : <span class="keyword">public</span> mpdf
777	<a name="l01073"></a>01073 {
778	<a name="l01074"></a>01074 <span class="keyword">protected</span>:
779	<a name="l01075"></a>01075 shared_ptr<eiWishartCh> eiW;
780	<a name="l01077"></a>01077 <span class="keywordtype">double</span> sqd;
781	<a name="l01078"></a>01078 <span class="comment">//reference point for diagonal</span>
782	<a name="l01079"></a>01079 vec refl;
783	<a name="l01080"></a>01080 <span class="keywordtype">double</span> l;
784	<a name="l01081"></a>01081 <span class="keywordtype">int</span> p;
785	<a name="l01082"></a>01082
786	<a name="l01083"></a>01083 <span class="keyword">public</span>:
787	<a name="l01084"></a>01084 rwiWishartCh():eiW(new eiWishartCh()),
788	<a name="l01085"></a>01085 sqd(0), l(0), p(0) {
789	<a name="l01086"></a>01086 set_ep(eiW);
790	<a name="l01087"></a>01087 }
791	<a name="l01088"></a>01088
792	<a name="l01089"></a>01089 <span class="keywordtype">void</span> set_parameters ( <span class="keywordtype">int</span> p0, <span class="keywordtype">double</span> k, vec ref0, <span class="keywordtype">double</span> l0 )
793	<a name="l01090"></a>01090 {
794	<a name="l01091"></a>01091 p=p0;
795	<a name="l01092"></a>01092 <span class="keywordtype">double</span> delta = 2/(k*k)+p+3;
796	<a name="l01093"></a>01093 sqd=sqrt ( delta-p-1 );
797	<a name="l01094"></a>01094 l=l0;
798	<a name="l01095"></a>01095 refl=pow(ref0,1-l);
799	<a name="l01096"></a>01096
800	<a name="l01097"></a>01097 eiW->set_parameters ( eye ( p ),delta );
801	<a name="l01098"></a>01098 <a class="code" href="classbdm_1_1mpdf.html#7c1900976ff13dbc09c9729b3bbff9e6" title="dimension of the condition">dimc</a>=eiW->dimension();
802	<a name="l01099"></a>01099 }
803	<a name="l01100"></a>01100 <span class="keywordtype">void</span> condition ( <span class="keyword">const</span> vec &c ) {
804	<a name="l01101"></a>01101 vec z=c;
805	<a name="l01102"></a>01102 <span class="keywordtype">int</span> ri=0;
806	<a name="l01103"></a>01103 <span class="keywordflow">for</span>(<span class="keywordtype">int</span> i=0;i<p*p;i+=(p+1)){<span class="comment">//trace diagonal element</span>
807	<a name="l01104"></a>01104 z(i) = pow(z(i),l)*refl(ri);
808	<a name="l01105"></a>01105 ri++;
809	<a name="l01106"></a>01106 }
810	<a name="l01107"></a>01107
811	<a name="l01108"></a>01108 eiW->_setY ( sqd*z );
812	<a name="l01109"></a>01109 }
813	<a name="l01110"></a>01110 };
814	<a name="l01111"></a>01111
815	<a name="l01113"></a>01113 <span class="keyword">enum</span> RESAMPLING_METHOD { MULTINOMIAL = 0, STRATIFIED = 1, SYSTEMATIC = 3 };
816	<a name="l01119"></a><a class="code" href="classbdm_1_1eEmp.html">01119</a> <span class="keyword">class </span><a class="code" href="classbdm_1_1eEmp.html" title="Weighted empirical density.">eEmp</a>: <span class="keyword">public</span> <a class="code" href="classbdm_1_1epdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a>
817	<a name="l01120"></a>01120 {
818	<a name="l01121"></a>01121 <span class="keyword">protected</span> :
819	<a name="l01123"></a><a class="code" href="classbdm_1_1eEmp.html#9798006271ca77629855113f1283a031">01123</a> <span class="keywordtype">int</span> <a class="code" href="classbdm_1_1eEmp.html#9798006271ca77629855113f1283a031" title="Number of particles.">n</a>;
820	<a name="l01125"></a><a class="code" href="classbdm_1_1eEmp.html#9d39241aab7c4bbeb07c6d516421c67d">01125</a> vec <a class="code" href="classbdm_1_1eEmp.html#9d39241aab7c4bbeb07c6d516421c67d" title="Sample weights .">w</a>;
821	<a name="l01127"></a><a class="code" href="classbdm_1_1eEmp.html#73d819553a0f268b055a087d2d4486f3">01127</a> Array<vec> <a class="code" href="classbdm_1_1eEmp.html#73d819553a0f268b055a087d2d4486f3" title="Samples .">samples</a>;
822	<a name="l01128"></a>01128 <span class="keyword">public</span>:
823	<a name="l01131"></a>01131 <a class="code" href="classbdm_1_1eEmp.html" title="Weighted empirical density.">eEmp</a> ( ) :<a class="code" href="classbdm_1_1epdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a> ( ),<a class="code" href="classbdm_1_1eEmp.html#9d39241aab7c4bbeb07c6d516421c67d" title="Sample weights .">w</a> ( ),<a class="code" href="classbdm_1_1eEmp.html#73d819553a0f268b055a087d2d4486f3" title="Samples .">samples</a> ( ) {};
824	<a name="l01133"></a><a class="code" href="classbdm_1_1eEmp.html#a3daf6363455af099921715e1233c076">01133</a> <a class="code" href="classbdm_1_1eEmp.html#a3daf6363455af099921715e1233c076" title="copy constructor">eEmp</a> ( <span class="keyword">const</span> <a class="code" href="classbdm_1_1eEmp.html" title="Weighted empirical density.">eEmp</a> &e ) : <a class="code" href="classbdm_1_1epdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a> ( e ), <a class="code" href="classbdm_1_1eEmp.html#9d39241aab7c4bbeb07c6d516421c67d" title="Sample weights .">w</a> ( e.<a class="code" href="classbdm_1_1eEmp.html#9d39241aab7c4bbeb07c6d516421c67d" title="Sample weights .">w</a> ), <a class="code" href="classbdm_1_1eEmp.html#73d819553a0f268b055a087d2d4486f3" title="Samples .">samples</a> ( e.<a class="code" href="classbdm_1_1eEmp.html#73d819553a0f268b055a087d2d4486f3" title="Samples .">samples</a> ) {};
825	<a name="l01135"></a>01135
826	<a name="l01137"></a>01137 <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1eEmp.html#7cfd383180b486fe4526bdf0179350c0" title="Set samples and weights.">set_statistics</a> ( <span class="keyword">const</span> vec &w0, <span class="keyword">const</span> <a class="code" href="classbdm_1_1epdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a>* pdf0 );
827	<a name="l01139"></a><a class="code" href="classbdm_1_1eEmp.html#cef74aa5f87d10d440b9b1e8bc78c1e7">01139</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1eEmp.html#cef74aa5f87d10d440b9b1e8bc78c1e7" title="Set samples and weights.">set_statistics</a> ( <span class="keyword">const</span> <a class="code" href="classbdm_1_1epdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a>* pdf0 , <span class="keywordtype">int</span> <a class="code" href="classbdm_1_1eEmp.html#9798006271ca77629855113f1283a031" title="Number of particles.">n</a> ) {<a class="code" href="classbdm_1_1eEmp.html#cef74aa5f87d10d440b9b1e8bc78c1e7" title="Set samples and weights.">set_statistics</a> ( ones ( n ) /n,pdf0 );};
828	<a name="l01141"></a>01141 <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1eEmp.html#b62d802b8ef39f7c4dcbeb366c90951a" title="Set sample.">set_samples</a> ( <span class="keyword">const</span> <a class="code" href="classbdm_1_1epdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a>* pdf0 );
829	<a name="l01143"></a><a class="code" href="classbdm_1_1eEmp.html#c74c281d652356c19b6b079e42ca7ef1">01143</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1eEmp.html#c74c281d652356c19b6b079e42ca7ef1" title="Set sample.">set_parameters</a> ( <span class="keywordtype">int</span> n0, <span class="keywordtype">bool</span> copy=<span class="keyword">true</span> ) {<a class="code" href="classbdm_1_1eEmp.html#9798006271ca77629855113f1283a031" title="Number of particles.">n</a>=n0; <a class="code" href="classbdm_1_1eEmp.html#9d39241aab7c4bbeb07c6d516421c67d" title="Sample weights .">w</a>.set_size ( n0,copy );<a class="code" href="classbdm_1_1eEmp.html#73d819553a0f268b055a087d2d4486f3" title="Samples .">samples</a>.set_size ( n0,copy );};
830	<a name="l01145"></a><a class="code" href="classbdm_1_1eEmp.html#d7f83cc0415cd44ae7cc8b4bdad93aef">01145</a> vec& <a class="code" href="classbdm_1_1eEmp.html#d7f83cc0415cd44ae7cc8b4bdad93aef" title="Potentially dangerous, use with care.">_w</a>() {<span class="keywordflow">return</span> <a class="code" href="classbdm_1_1eEmp.html#9d39241aab7c4bbeb07c6d516421c67d" title="Sample weights .">w</a>;};
831	<a name="l01147"></a><a class="code" href="classbdm_1_1eEmp.html#b7d7106f486e3fad38590914a693d714">01147</a> <span class="keyword">const</span> vec& <a class="code" href="classbdm_1_1eEmp.html#b7d7106f486e3fad38590914a693d714" title="Potentially dangerous, use with care.">_w</a>()<span class="keyword"> const </span>{<span class="keywordflow">return</span> <a class="code" href="classbdm_1_1eEmp.html#9d39241aab7c4bbeb07c6d516421c67d" title="Sample weights .">w</a>;};
832	<a name="l01149"></a><a class="code" href="classbdm_1_1eEmp.html#c24966b0aaeb767bc8a6b4fd60931be2">01149</a> Array<vec>& <a class="code" href="classbdm_1_1eEmp.html#c24966b0aaeb767bc8a6b4fd60931be2" title="access function">_samples</a>() {<span class="keywordflow">return</span> <a class="code" href="classbdm_1_1eEmp.html#73d819553a0f268b055a087d2d4486f3" title="Samples .">samples</a>;};
833	<a name="l01151"></a><a class="code" href="classbdm_1_1eEmp.html#b59af0efdb009d98ea8ebfa965e74ae2">01151</a> <span class="keyword">const</span> Array<vec>& <a class="code" href="classbdm_1_1eEmp.html#b59af0efdb009d98ea8ebfa965e74ae2" title="access function">_samples</a>()<span class="keyword"> const </span>{<span class="keywordflow">return</span> <a class="code" href="classbdm_1_1eEmp.html#73d819553a0f268b055a087d2d4486f3" title="Samples .">samples</a>;};
834	<a name="l01153"></a>01153 ivec <a class="code" href="classbdm_1_1eEmp.html#f06ce255de5dbb2313f52ee51f82ba3d" title="Function performs resampling, i.e. removal of low-weight samples and duplication...">resample</a> ( RESAMPLING_METHOD method=SYSTEMATIC );
835	<a name="l01155"></a><a class="code" href="classbdm_1_1eEmp.html#97f1e07b5ae6eebc91c7365f0f88d270">01155</a> vec <a class="code" href="classbdm_1_1eEmp.html#97f1e07b5ae6eebc91c7365f0f88d270" title="inherited operation : NOT implemneted">sample</a>()<span class="keyword"> const </span>{it_error ( <span class="stringliteral">"Not implemented"</span> );<span class="keywordflow">return</span> 0;}
836	<a name="l01157"></a><a class="code" href="classbdm_1_1eEmp.html#01654c014d3aa068f8d4ecba4be86d09">01157</a> <span class="keywordtype">double</span> <a class="code" href="classbdm_1_1eEmp.html#01654c014d3aa068f8d4ecba4be86d09" title="inherited operation : NOT implemneted">evallog</a> ( <span class="keyword">const</span> vec &val )<span class="keyword"> const </span>{it_error ( <span class="stringliteral">"Not implemented"</span> );<span class="keywordflow">return</span> 0.0;}
837	<a name="l01158"></a><a class="code" href="classbdm_1_1eEmp.html#bbfcb4f868c7381298c281a256d8c4b9">01158</a> vec <a class="code" href="classbdm_1_1eEmp.html#bbfcb4f868c7381298c281a256d8c4b9" title="return expected value">mean</a>()<span class="keyword"> const</span>
838	<a name="l01159"></a>01159 <span class="keyword"> </span>{
839	<a name="l01160"></a>01160 vec pom=zeros ( <a class="code" href="classbdm_1_1epdf.html#16adac20ec7fe07e1ea0b27d917788ce" title="dimension of the random variable">dim</a> );
840	<a name="l01161"></a>01161 <span class="keywordflow">for</span> ( <span class="keywordtype">int</span> i=0;i<<a class="code" href="classbdm_1_1eEmp.html#9798006271ca77629855113f1283a031" title="Number of particles.">n</a>;i++ ) {pom+=<a class="code" href="classbdm_1_1eEmp.html#73d819553a0f268b055a087d2d4486f3" title="Samples .">samples</a> ( i ) *<a class="code" href="classbdm_1_1eEmp.html#9d39241aab7c4bbeb07c6d516421c67d" title="Sample weights .">w</a> ( i );}
841	<a name="l01162"></a>01162 <span class="keywordflow">return</span> pom;
842	<a name="l01163"></a>01163 }
843	<a name="l01164"></a><a class="code" href="classbdm_1_1eEmp.html#05e9ebf467ede737cb6a3621d7fd3c87">01164</a> vec <a class="code" href="classbdm_1_1eEmp.html#05e9ebf467ede737cb6a3621d7fd3c87" title="return expected variance (not covariance!)">variance</a>()<span class="keyword"> const</span>
844	<a name="l01165"></a>01165 <span class="keyword"> </span>{
845	<a name="l01166"></a>01166 vec pom=zeros ( <a class="code" href="classbdm_1_1epdf.html#16adac20ec7fe07e1ea0b27d917788ce" title="dimension of the random variable">dim</a> );
846	<a name="l01167"></a>01167 <span class="keywordflow">for</span> ( <span class="keywordtype">int</span> i=0;i<<a class="code" href="classbdm_1_1eEmp.html#9798006271ca77629855113f1283a031" title="Number of particles.">n</a>;i++ ) {pom+=pow ( <a class="code" href="classbdm_1_1eEmp.html#73d819553a0f268b055a087d2d4486f3" title="Samples .">samples</a> ( i ),2 ) *<a class="code" href="classbdm_1_1eEmp.html#9d39241aab7c4bbeb07c6d516421c67d" title="Sample weights .">w</a> ( i );}
847	<a name="l01168"></a>01168 <span class="keywordflow">return</span> pom-pow ( <a class="code" href="classbdm_1_1eEmp.html#bbfcb4f868c7381298c281a256d8c4b9" title="return expected value">mean</a>(),2 );
848	<a name="l01169"></a>01169 }
849	<a name="l01171"></a><a class="code" href="classbdm_1_1eEmp.html#b1c9df656144edf79ba2d885613f661f">01171</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1eEmp.html#b1c9df656144edf79ba2d885613f661f" title="For this class, qbounds are minimum and maximum value of the population!">qbounds</a> ( vec &lb, vec &ub, <span class="keywordtype">double</span> perc=0.95 )<span class="keyword"> const</span>
850	<a name="l01172"></a>01172 <span class="keyword"> </span>{
851	<a name="l01173"></a>01173 <span class="comment">// lb in inf so than it will be pushed below;</span>
852	<a name="l01174"></a>01174 lb.set_size ( <a class="code" href="classbdm_1_1epdf.html#16adac20ec7fe07e1ea0b27d917788ce" title="dimension of the random variable">dim</a> );
853	<a name="l01175"></a>01175 ub.set_size ( <a class="code" href="classbdm_1_1epdf.html#16adac20ec7fe07e1ea0b27d917788ce" title="dimension of the random variable">dim</a> );
854	<a name="l01176"></a>01176 lb = std::numeric_limits<double>::infinity();
855	<a name="l01177"></a>01177 ub = -std::numeric_limits<double>::infinity();
856	<a name="l01178"></a>01178 <span class="keywordtype">int</span> j;
857	<a name="l01179"></a>01179 <span class="keywordflow">for</span> ( <span class="keywordtype">int</span> i=0;i<<a class="code" href="classbdm_1_1eEmp.html#9798006271ca77629855113f1283a031" title="Number of particles.">n</a>;i++ )
858	<a name="l01180"></a>01180 {
859	<a name="l01181"></a>01181 <span class="keywordflow">for</span> ( j=0;j<<a class="code" href="classbdm_1_1epdf.html#16adac20ec7fe07e1ea0b27d917788ce" title="dimension of the random variable">dim</a>; j++ )
860	<a name="l01182"></a>01182 {
861	<a name="l01183"></a>01183 <span class="keywordflow">if</span> ( <a class="code" href="classbdm_1_1eEmp.html#73d819553a0f268b055a087d2d4486f3" title="Samples .">samples</a> ( i ) ( j ) <lb ( j ) ) {lb ( j ) =<a class="code" href="classbdm_1_1eEmp.html#73d819553a0f268b055a087d2d4486f3" title="Samples .">samples</a> ( i ) ( j );}
862	<a name="l01184"></a>01184 <span class="keywordflow">if</span> ( <a class="code" href="classbdm_1_1eEmp.html#73d819553a0f268b055a087d2d4486f3" title="Samples .">samples</a> ( i ) ( j ) >ub ( j ) ) {ub ( j ) =<a class="code" href="classbdm_1_1eEmp.html#73d819553a0f268b055a087d2d4486f3" title="Samples .">samples</a> ( i ) ( j );}
863	<a name="l01185"></a>01185 }
864	<a name="l01186"></a>01186 }
865	<a name="l01187"></a>01187 }
866	<a name="l01188"></a>01188 };
867	<a name="l01189"></a>01189
868	<a name="l01190"></a>01190
869	<a name="l01192"></a>01192
870	<a name="l01193"></a>01193 <span class="keyword">template</span><<span class="keyword">class</span> sq_T>
871	<a name="l01194"></a>01194 <span class="keywordtype">void</span> enorm<sq_T>::set_parameters ( <span class="keyword">const</span> vec &mu0, <span class="keyword">const</span> sq_T &R0 )
872	<a name="l01195"></a>01195 {
873	<a name="l01196"></a>01196 <span class="comment">//Fixme test dimensions of mu0 and R0;</span>
874	<a name="l01197"></a>01197 mu = mu0;
875	<a name="l01198"></a>01198 R = R0;
876	<a name="l01199"></a>01199 <a class="code" href="classbdm_1_1root.html#1c314bd6d6dacb8ba78ea5eb88fd9516" title="This method TODO.">validate</a>();
877	<a name="l01200"></a>01200 };
878	<a name="l01201"></a>01201
879	<a name="l01202"></a>01202 <span class="keyword">template</span><<span class="keyword">class</span> sq_T>
880	<a name="l01203"></a><a class="code" href="classbdm_1_1enorm.html#61bd470764020bea6e1ed35000f259e6">01203</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1enorm.html#61bd470764020bea6e1ed35000f259e6">enorm<sq_T>::from_setting</a>(<span class="keyword">const</span> Setting &<span class="keyword">set</span>){
881	<a name="l01204"></a>01204 <a class="code" href="classbdm_1_1enorm.html#61bd470764020bea6e1ed35000f259e6">epdf::from_setting</a>(<span class="keyword">set</span>); <span class="comment">//reads rv</span>
882	<a name="l01205"></a>01205
883	<a name="l01206"></a>01206 <a class="code" href="classbdm_1_1UI.html#cd1667e6fec99ec64dabcb3ca2ff922d">UI::get</a>(<a class="code" href="classbdm_1_1enorm.html#c702a194720853570d08b65482f842c7" title="mean value">mu</a>,<span class="keyword">set</span>,<span class="stringliteral">"mu"</span>, UI::compulsory);
884	<a name="l01207"></a>01207 mat Rtmp;<span class="comment">// necessary for conversion</span>
885	<a name="l01208"></a>01208 <a class="code" href="classbdm_1_1UI.html#cd1667e6fec99ec64dabcb3ca2ff922d">UI::get</a>(Rtmp,<span class="keyword">set</span>,<span class="stringliteral">"R"</span>, UI::compulsory);
886	<a name="l01209"></a>01209 <a class="code" href="classbdm_1_1enorm.html#2d92dde696b2a7a5b10ddef5d22ba2c2" title="Covariance matrix in decomposed form.">R</a>=Rtmp; <span class="comment">// conversion</span>
887	<a name="l01210"></a>01210 <a class="code" href="classbdm_1_1enorm.html#38eb17ecb75d94a50b6782fcf735cfea" title="This method TODO.">validate</a>();
888	<a name="l01211"></a>01211 }
889	<a name="l01212"></a>01212
890	<a name="l01213"></a>01213 <span class="keyword">template</span><<span class="keyword">class</span> sq_T>
891	<a name="l01214"></a><a class="code" href="classbdm_1_1enorm.html#d2e0d3a1e30ab3ab04df2d0c43ae74a2">01214</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1enorm.html#d2e0d3a1e30ab3ab04df2d0c43ae74a2" title="dupdate in exponential form (not really handy)">enorm<sq_T>::dupdate</a> ( mat &v, <span class="keywordtype">double</span> nu )
892	<a name="l01215"></a>01215 {
893	<a name="l01216"></a>01216 <span class="comment">//</span>
894	<a name="l01217"></a>01217 };
895	<a name="l01218"></a>01218
896	<a name="l01219"></a>01219 <span class="comment">// template<class sq_T></span>
897	<a name="l01220"></a>01220 <span class="comment">// void enorm<sq_T>::tupdate ( double phi, mat &vbar, double nubar ) {</span>
898	<a name="l01221"></a>01221 <span class="comment">// //</span>
899	<a name="l01222"></a>01222 <span class="comment">// };</span>
900	<a name="l01223"></a>01223
901	<a name="l01224"></a>01224 <span class="keyword">template</span><<span class="keyword">class</span> sq_T>
902	<a name="l01225"></a><a class="code" href="classbdm_1_1enorm.html#e1a48f52351ec3a349bd443b713b1766">01225</a> vec <a class="code" href="classbdm_1_1enorm.html#e1a48f52351ec3a349bd443b713b1766" title="Returns a sample, from density .">enorm<sq_T>::sample</a>()<span class="keyword"> const</span>
903	<a name="l01226"></a>01226 <span class="keyword"> </span>{
904	<a name="l01227"></a>01227 vec x ( <a class="code" href="classbdm_1_1epdf.html#16adac20ec7fe07e1ea0b27d917788ce" title="dimension of the random variable">dim</a> );
905	<a name="l01228"></a>01228 <span class="preprocessor">#pragma omp critical</span>
906	<a name="l01229"></a>01229 <span class="preprocessor"></span> NorRNG.sample_vector ( <a class="code" href="classbdm_1_1epdf.html#16adac20ec7fe07e1ea0b27d917788ce" title="dimension of the random variable">dim</a>,x );
907	<a name="l01230"></a>01230 vec smp = <a class="code" href="classbdm_1_1enorm.html#2d92dde696b2a7a5b10ddef5d22ba2c2" title="Covariance matrix in decomposed form.">R</a>.sqrt_mult ( x );
908	<a name="l01231"></a>01231
909	<a name="l01232"></a>01232 smp += <a class="code" href="classbdm_1_1enorm.html#c702a194720853570d08b65482f842c7" title="mean value">mu</a>;
910	<a name="l01233"></a>01233 <span class="keywordflow">return</span> smp;
911	<a name="l01234"></a>01234 };
912	<a name="l01235"></a>01235
913	<a name="l01236"></a>01236 <span class="comment">// template<class sq_T></span>
914	<a name="l01237"></a>01237 <span class="comment">// double enorm<sq_T>::eval ( const vec &val ) const {</span>
915	<a name="l01238"></a>01238 <span class="comment">// double pdfl,e;</span>
916	<a name="l01239"></a>01239 <span class="comment">// pdfl = evallog ( val );</span>
917	<a name="l01240"></a>01240 <span class="comment">// e = exp ( pdfl );</span>
918	<a name="l01241"></a>01241 <span class="comment">// return e;</span>
919	<a name="l01242"></a>01242 <span class="comment">// };</span>
920	<a name="l01243"></a>01243
921	<a name="l01244"></a>01244 <span class="keyword">template</span><<span class="keyword">class</span> sq_T>
922	<a name="l01245"></a><a class="code" href="classbdm_1_1enorm.html#e13aeed5b543b2179bacdc4fa2ae47a3">01245</a> <span class="keywordtype">double</span> <a class="code" href="classbdm_1_1enorm.html#e13aeed5b543b2179bacdc4fa2ae47a3" title="Evaluate normalized log-probability.">enorm<sq_T>::evallog_nn</a> ( <span class="keyword">const</span> vec &val )<span class="keyword"> const</span>
923	<a name="l01246"></a>01246 <span class="keyword"> </span>{
924	<a name="l01247"></a>01247 <span class="comment">// 1.83787706640935 = log(2pi)</span>
925	<a name="l01248"></a>01248 <span class="keywordtype">double</span> tmp=-0.5* ( <a class="code" href="classbdm_1_1enorm.html#2d92dde696b2a7a5b10ddef5d22ba2c2" title="Covariance matrix in decomposed form.">R</a>.invqform ( <a class="code" href="classbdm_1_1enorm.html#c702a194720853570d08b65482f842c7" title="mean value">mu</a>-val ) );<span class="comment">// - lognc();</span>
926	<a name="l01249"></a>01249 <span class="keywordflow">return</span> tmp;
927	<a name="l01250"></a>01250 };
928	<a name="l01251"></a>01251
929	<a name="l01252"></a>01252 <span class="keyword">template</span><<span class="keyword">class</span> sq_T>
930	<a name="l01253"></a><a class="code" href="classbdm_1_1enorm.html#25785343aff102cc5df1cab08ba16d32">01253</a> <span class="keyword">inline</span> <span class="keywordtype">double</span> <a class="code" href="classbdm_1_1enorm.html#25785343aff102cc5df1cab08ba16d32" title="logarithm of the normalizing constant, ">enorm<sq_T>::lognc</a> ()<span class="keyword"> const</span>
931	<a name="l01254"></a>01254 <span class="keyword"> </span>{
932	<a name="l01255"></a>01255 <span class="comment">// 1.83787706640935 = log(2pi)</span>
933	<a name="l01256"></a>01256 <span class="keywordtype">double</span> tmp=0.5* ( <a class="code" href="classbdm_1_1enorm.html#2d92dde696b2a7a5b10ddef5d22ba2c2" title="Covariance matrix in decomposed form.">R</a>.cols() * 1.83787706640935 +<a class="code" href="classbdm_1_1enorm.html#2d92dde696b2a7a5b10ddef5d22ba2c2" title="Covariance matrix in decomposed form.">R</a>.logdet() );
934	<a name="l01257"></a>01257 <span class="keywordflow">return</span> tmp;
935	<a name="l01258"></a>01258 };
936	<a name="l01259"></a>01259
937	<a name="l01260"></a>01260 <span class="keyword">template</span><<span class="keyword">class</span> sq_T>
938	<a name="l01261"></a><a class="code" href="classbdm_1_1mlnorm.html#5d18dec3167584338a4775c1d165d96f">01261</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1mlnorm.html#5d18dec3167584338a4775c1d165d96f" title="Set A and R.">mlnorm<sq_T>::set_parameters</a> ( <span class="keyword">const</span> mat &A0, <span class="keyword">const</span> vec &mu0, <span class="keyword">const</span> sq_T &R0 )
939	<a name="l01262"></a>01262 {
940	<a name="l01263"></a>01263 it_assert_debug ( A0.rows() ==mu0.length(),<span class="stringliteral">""</span> );
941	<a name="l01264"></a>01264 it_assert_debug ( A0.rows() ==R0.rows(),<span class="stringliteral">""</span> );
942	<a name="l01265"></a>01265
943	<a name="l01266"></a>01266 <a class="code" href="classbdm_1_1mlnorm.html#6de45ab731143e70a94318df586c36ba" title="Internal epdf that arise by conditioning on rvc.">iepdf</a>->set_parameters(zeros(A0.rows()), R0);
944	<a name="l01267"></a>01267 A = A0;
945	<a name="l01268"></a>01268 mu_const = mu0;
946	<a name="l01269"></a>01269 <a class="code" href="classbdm_1_1mpdf.html#7c1900976ff13dbc09c9729b3bbff9e6" title="dimension of the condition">dimc</a> = A0.cols();
947	<a name="l01270"></a>01270 }
948	<a name="l01271"></a>01271
949	<a name="l01272"></a>01272 <span class="comment">// template<class sq_T></span>
950	<a name="l01273"></a>01273 <span class="comment">// vec mlnorm<sq_T>::samplecond (const vec &cond, double &lik ) {</span>
951	<a name="l01274"></a>01274 <span class="comment">// this->condition ( cond );</span>
952	<a name="l01275"></a>01275 <span class="comment">// vec smp = epdf.sample();</span>
953	<a name="l01276"></a>01276 <span class="comment">// lik = epdf.eval ( smp );</span>
954	<a name="l01277"></a>01277 <span class="comment">// return smp;</span>
955	<a name="l01278"></a>01278 <span class="comment">// }</span>
956	<a name="l01279"></a>01279
957	<a name="l01280"></a>01280 <span class="comment">// template<class sq_T></span>
958	<a name="l01281"></a>01281 <span class="comment">// mat mlnorm<sq_T>::samplecond (const vec &cond, vec &lik, int n ) {</span>
959	<a name="l01282"></a>01282 <span class="comment">// int i;</span>
960	<a name="l01283"></a>01283 <span class="comment">// int dim = rv.count();</span>
961	<a name="l01284"></a>01284 <span class="comment">// mat Smp ( dim,n );</span>
962	<a name="l01285"></a>01285 <span class="comment">// vec smp ( dim );</span>
963	<a name="l01286"></a>01286 <span class="comment">// this->condition ( cond );</span>
964	<a name="l01287"></a>01287 <span class="comment">//</span>
965	<a name="l01288"></a>01288 <span class="comment">// for ( i=0; i<n; i++ ) {</span>
966	<a name="l01289"></a>01289 <span class="comment">// smp = epdf.sample();</span>
967	<a name="l01290"></a>01290 <span class="comment">// lik ( i ) = epdf.eval ( smp );</span>
968	<a name="l01291"></a>01291 <span class="comment">// Smp.set_col ( i ,smp );</span>
969	<a name="l01292"></a>01292 <span class="comment">// }</span>
970	<a name="l01293"></a>01293 <span class="comment">//</span>
971	<a name="l01294"></a>01294 <span class="comment">// return Smp;</span>
972	<a name="l01295"></a>01295 <span class="comment">// }</span>
973	<a name="l01296"></a>01296
974	<a name="l01297"></a>01297 <span class="keyword">template</span><<span class="keyword">class</span> sq_T>
975	<a name="l01298"></a><a class="code" href="classbdm_1_1mlnorm.html#0dafc0196e7e07fd06dc6716e0e18bc2">01298</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1mlnorm.html#0dafc0196e7e07fd06dc6716e0e18bc2">mlnorm<sq_T>::condition</a> ( <span class="keyword">const</span> vec &cond )
976	<a name="l01299"></a>01299 {
977	<a name="l01300"></a>01300 _mu = A*cond + mu_const;
978	<a name="l01301"></a>01301 <span class="comment">//R is already assigned;</span>
979	<a name="l01302"></a>01302 }
980	<a name="l01303"></a>01303
981	<a name="l01304"></a>01304 <span class="keyword">template</span><<span class="keyword">class</span> sq_T>
982	<a name="l01305"></a><a class="code" href="classbdm_1_1enorm.html#c2996bdaffad38fbe0fc776db54c9d80">01305</a> <a class="code" href="classbdm_1_1enorm.html" title="Gaussian density with positive definite (decomposed) covariance matrix.">enorm<sq_T></a>* <a class="code" href="classbdm_1_1enorm.html#c2996bdaffad38fbe0fc776db54c9d80" title="Return marginal density on the given RV, the remainig rvs are intergrated out.">enorm<sq_T>::marginal</a> ( <span class="keyword">const</span> <a class="code" href="classbdm_1_1RV.html" title="Class representing variables, most often random variables.">RV</a> &rvn )<span class="keyword"> const</span>
983	<a name="l01306"></a>01306 <span class="keyword"> </span>{
984	<a name="l01307"></a>01307 it_assert_debug ( <a class="code" href="classbdm_1_1epdf.html#c4b863ff84c7a4882fb3ad18556027f9" title="True if rv is assigned.">isnamed</a>(), <span class="stringliteral">"rv description is not assigned"</span> );
985	<a name="l01308"></a>01308 ivec irvn = rvn.<a class="code" href="classbdm_1_1RV.html#cbebdb5e0d30101a6eb63550ef701c55">dataind</a> ( <a class="code" href="classbdm_1_1epdf.html#62c5b8ff71d9ebe6cd58d3c342eb1dc8" title="Description of the random variable.">rv</a> );
986	<a name="l01309"></a>01309
987	<a name="l01310"></a>01310 sq_T Rn ( <a class="code" href="classbdm_1_1enorm.html#2d92dde696b2a7a5b10ddef5d22ba2c2" title="Covariance matrix in decomposed form.">R</a>,irvn ); <span class="comment">//select rows and columns of R</span>
988	<a name="l01311"></a>01311
989	<a name="l01312"></a>01312 <a class="code" href="classbdm_1_1enorm.html" title="Gaussian density with positive definite (decomposed) covariance matrix.">enorm<sq_T></a>* tmp = <span class="keyword">new</span> <a class="code" href="classbdm_1_1enorm.html" title="Gaussian density with positive definite (decomposed) covariance matrix.">enorm<sq_T></a>;
990	<a name="l01313"></a>01313 tmp-><a class="code" href="classbdm_1_1epdf.html#f423e28448dbb69ef4905295ec8de8ff" title="Name its rv.">set_rv</a> ( rvn );
991	<a name="l01314"></a>01314 tmp->set_parameters ( <a class="code" href="classbdm_1_1enorm.html#c702a194720853570d08b65482f842c7" title="mean value">mu</a> ( irvn ), Rn );
992	<a name="l01315"></a>01315 <span class="keywordflow">return</span> tmp;
993	<a name="l01316"></a>01316 }
994	<a name="l01317"></a>01317
995	<a name="l01318"></a>01318 <span class="keyword">template</span><<span class="keyword">class</span> sq_T>
996	<a name="l01319"></a><a class="code" href="classbdm_1_1enorm.html#baea4d49c657342b58297d68cda16d26">01319</a> <a class="code" href="classbdm_1_1mpdf.html" title="Conditional probability density, e.g. modeling some dependencies.">mpdf</a>* <a class="code" href="classbdm_1_1enorm.html#baea4d49c657342b58297d68cda16d26" title="Return conditional density on the given RV, the remaining rvs will be in conditioning...">enorm<sq_T>::condition</a> ( <span class="keyword">const</span> <a class="code" href="classbdm_1_1RV.html" title="Class representing variables, most often random variables.">RV</a> &rvn )<span class="keyword"> const</span>
997	<a name="l01320"></a>01320 <span class="keyword"> </span>{
998	<a name="l01321"></a>01321
999	<a name="l01322"></a>01322 it_assert_debug ( <a class="code" href="classbdm_1_1epdf.html#c4b863ff84c7a4882fb3ad18556027f9" title="True if rv is assigned.">isnamed</a>(),<span class="stringliteral">"rvs are not assigned"</span> );
1000	<a name="l01323"></a>01323
1001	<a name="l01324"></a>01324 <a class="code" href="classbdm_1_1RV.html" title="Class representing variables, most often random variables.">RV</a> rvc = <a class="code" href="classbdm_1_1epdf.html#62c5b8ff71d9ebe6cd58d3c342eb1dc8" title="Description of the random variable.">rv</a>.<a class="code" href="classbdm_1_1RV.html#aec44dabdf0a6d90fbae95e1356eda39" title="Subtract another variable from the current one.">subt</a> ( rvn );
1002	<a name="l01325"></a>01325 it_assert_debug ( ( rvc._dsize() +rvn._dsize() ==<a class="code" href="classbdm_1_1epdf.html#62c5b8ff71d9ebe6cd58d3c342eb1dc8" title="Description of the random variable.">rv</a>._dsize() ),<span class="stringliteral">"wrong rvn"</span> );
1003	<a name="l01326"></a>01326 <span class="comment">//Permutation vector of the new R</span>
1004	<a name="l01327"></a>01327 ivec irvn = rvn.<a class="code" href="classbdm_1_1RV.html#cbebdb5e0d30101a6eb63550ef701c55">dataind</a> ( <a class="code" href="classbdm_1_1epdf.html#62c5b8ff71d9ebe6cd58d3c342eb1dc8" title="Description of the random variable.">rv</a> );
1005	<a name="l01328"></a>01328 ivec irvc = rvc.<a class="code" href="classbdm_1_1RV.html#cbebdb5e0d30101a6eb63550ef701c55">dataind</a> ( <a class="code" href="classbdm_1_1epdf.html#62c5b8ff71d9ebe6cd58d3c342eb1dc8" title="Description of the random variable.">rv</a> );
1006	<a name="l01329"></a>01329 ivec perm=concat ( irvn , irvc );
1007	<a name="l01330"></a>01330 sq_T Rn ( <a class="code" href="classbdm_1_1enorm.html#2d92dde696b2a7a5b10ddef5d22ba2c2" title="Covariance matrix in decomposed form.">R</a>,perm );
1008	<a name="l01331"></a>01331
1009	<a name="l01332"></a>01332 <span class="comment">//fixme - could this be done in general for all sq_T?</span>
1010	<a name="l01333"></a>01333 mat S=Rn.to_mat();
1011	<a name="l01334"></a>01334 <span class="comment">//fixme</span>
1012	<a name="l01335"></a>01335 <span class="keywordtype">int</span> n=rvn._dsize()-1;
1013	<a name="l01336"></a>01336 <span class="keywordtype">int</span> end=<a class="code" href="classbdm_1_1enorm.html#2d92dde696b2a7a5b10ddef5d22ba2c2" title="Covariance matrix in decomposed form.">R</a>.rows()-1;
1014	<a name="l01337"></a>01337 mat S11 = S.get ( 0,n, 0, n );
1015	<a name="l01338"></a>01338 mat S12 = S.get ( 0, n , rvn._dsize(), end );
1016	<a name="l01339"></a>01339 mat S22 = S.get ( rvn._dsize(), end, rvn._dsize(), end );
1017	<a name="l01340"></a>01340
1018	<a name="l01341"></a>01341 vec mu1 = <a class="code" href="classbdm_1_1enorm.html#c702a194720853570d08b65482f842c7" title="mean value">mu</a> ( irvn );
1019	<a name="l01342"></a>01342 vec mu2 = <a class="code" href="classbdm_1_1enorm.html#c702a194720853570d08b65482f842c7" title="mean value">mu</a> ( irvc );
1020	<a name="l01343"></a>01343 mat A=S12*inv ( S22 );
1021	<a name="l01344"></a>01344 sq_T R_n ( S11 - A *S12.T() );
1022	<a name="l01345"></a>01345
1023	<a name="l01346"></a>01346 <a class="code" href="classbdm_1_1mlnorm.html" title="Normal distributed linear function with linear function of mean value;.">mlnorm<sq_T></a>* tmp=<span class="keyword">new</span> <a class="code" href="classbdm_1_1mlnorm.html" title="Normal distributed linear function with linear function of mean value;.">mlnorm<sq_T></a> ( );
1024	<a name="l01347"></a>01347 tmp->set_rv ( rvn ); tmp->set_rvc ( rvc );
1025	<a name="l01348"></a>01348 tmp->set_parameters ( A,mu1-A*mu2,R_n );
1026	<a name="l01349"></a>01349 <span class="keywordflow">return</span> tmp;
1027	<a name="l01350"></a>01350 }
1028	<a name="l01351"></a>01351
1029	<a name="l01353"></a>01353
1030	<a name="l01354"></a>01354 <span class="keyword">template</span><<span class="keyword">class</span> sq_T>
1031	<a name="l01355"></a>01355 std::ostream &operator<< ( std::ostream &os, mlnorm<sq_T> &ml )
1032	<a name="l01356"></a>01356 {
1033	<a name="l01357"></a>01357 os << <span class="stringliteral">"A:"</span><< ml.A<<endl;
1034	<a name="l01358"></a>01358 os << <span class="stringliteral">"mu:"</span><< ml.mu_const<<endl;
1035	<a name="l01359"></a>01359 os << <span class="stringliteral">"R:"</span> << ml.iepdf->_R().to_mat() <<endl;
1036	<a name="l01360"></a>01360 <span class="keywordflow">return</span> os;
1037	<a name="l01361"></a>01361 };
1038	<a name="l01362"></a>01362
1039	<a name="l01363"></a>01363 }
1040	<a name="l01364"></a>01364 <span class="preprocessor">#endif //EF_H</span>
1041	</pre></div></div>
1042	<hr size="1"><address style="text-align: right;"><small>Generated on Wed Aug 5 00:06:47 2009 for mixpp by
1043	<a href="http://www.doxygen.org/index.html">
1044	<img src="doxygen.png" alt="doxygen" align="middle" border="0"></a> 1.5.9 </small></address>
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