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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> Gamma_RNG 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#a4135778ecd9ab774762936c82a097c6">00047</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;};
88	<a name="l00049"></a><a class="code" href="classbdm_1_1eEF.html#a36d06ecdd6f4c79dc122510eaccc692">00049</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>{
89	<a name="l00050"></a>00050 <span class="keywordtype">double</span> tmp;
90	<a name="l00051"></a>00051 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>();
91	<a name="l00052"></a>00052 <span class="comment">// it_assert_debug ( std::isfinite ( tmp ),"Infinite value" );</span>
92	<a name="l00053"></a>00053 <span class="keywordflow">return</span> tmp;
93	<a name="l00054"></a>00054 }
94	<a name="l00056"></a><a class="code" href="classbdm_1_1eEF.html#6886c60b6b690e503913240db5de0c6f">00056</a> <span class="keyword">virtual</span> vec <a class="code" href="classbdm_1_1eEF.html#6886c60b6b690e503913240db5de0c6f" title="Evaluate normalized log-probability for many samples.">evallog_m</a> (<span class="keyword">const</span> mat &Val)<span class="keyword"> const </span>{
95	<a name="l00057"></a>00057 vec x (Val.cols());
96	<a name="l00058"></a>00058 <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)) ;}
97	<a name="l00059"></a>00059 <span class="keywordflow">return</span> x -<a class="code" href="classbdm_1_1eEF.html#cd678fc9b02007a4b8d6692e746f1bf8" title="logarithm of the normalizing constant, ">lognc</a>();
98	<a name="l00060"></a>00060 }
99	<a name="l00062"></a><a class="code" href="classbdm_1_1eEF.html#d793f4fd6d0dcec5f16bff0ae45fc7d5">00062</a> <span class="keyword">virtual</span> vec <a class="code" href="classbdm_1_1eEF.html#d793f4fd6d0dcec5f16bff0ae45fc7d5" title="Evaluate normalized log-probability for many samples.">evallog_m</a> (<span class="keyword">const</span> Array<vec> &Val)<span class="keyword"> const </span>{
100	<a name="l00063"></a>00063 vec x (Val.length());
101	<a name="l00064"></a>00064 <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0;i < Val.length();i++) {x (i) = <a class="code" href="classbdm_1_1eEF.html#a4135778ecd9ab774762936c82a097c6" title="Evaluate normalized log-probability.">evallog_nn</a> (Val (i)) ;}
102	<a name="l00065"></a>00065 <span class="keywordflow">return</span> x -<a class="code" href="classbdm_1_1eEF.html#cd678fc9b02007a4b8d6692e746f1bf8" title="logarithm of the normalizing constant, ">lognc</a>();
103	<a name="l00066"></a>00066 }
104	<a name="l00068"></a><a class="code" href="classbdm_1_1eEF.html#cf38af29e8e3d650c640509a52396053">00068</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>);};
105	<a name="l00069"></a>00069 };
106	<a name="l00070"></a>00070
107	<a name="l00071"></a>00071
108	<a name="l00073"></a><a class="code" href="classbdm_1_1BMEF.html">00073</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>
109	<a name="l00074"></a>00074 {
110	<a name="l00075"></a>00075 <span class="keyword">protected</span>:
111	<a name="l00077"></a><a class="code" href="classbdm_1_1BMEF.html#1331865e10fb1ccef65bb4c47fa3be64">00077</a> <span class="keywordtype">double</span> <a class="code" href="classbdm_1_1BMEF.html#1331865e10fb1ccef65bb4c47fa3be64" title="forgetting factor">frg</a>;
112	<a name="l00079"></a><a class="code" href="classbdm_1_1BMEF.html#06e7b3ac03e10017d4288c76888e2865">00079</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>;
113	<a name="l00080"></a>00080 <span class="keyword">public</span>:
114	<a name="l00082"></a><a class="code" href="classbdm_1_1BMEF.html#2def512872ed8a4fc3b702371ec0be55">00082</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) {}
115	<a name="l00084"></a><a class="code" href="classbdm_1_1BMEF.html#9662379513101405e159e76717104e62">00084</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>) {}
116	<a name="l00086"></a><a class="code" href="classbdm_1_1BMEF.html#d2b528b7a41ca67163152142f5404051">00086</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>);};
117	<a name="l00088"></a><a class="code" href="classbdm_1_1BMEF.html#bf58deb99af2a6cc674f13ff90300de6">00088</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) {};
118	<a name="l00089"></a>00089 <span class="comment">//original Bayes</span>
119	<a name="l00090"></a>00090 <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);
120	<a name="l00092"></a><a class="code" href="classbdm_1_1BMEF.html#b2916a2e71a958665054473124d5e749">00092</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>);}
121	<a name="l00094"></a>00094 <span class="comment">// virtual void flatten ( double nu0 ) {it_error ( "Not implemented" );}</span>
122	<a name="l00095"></a>00095
123	<a name="l00096"></a><a class="code" href="classbdm_1_1BMEF.html#62d2e4691bed41a1efa6b9c2e35e5c67">00096</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;};
124	<a name="l00097"></a>00097 };
125	<a name="l00098"></a>00098
126	<a name="l00099"></a>00099 <span class="keyword">template</span><<span class="keyword">class</span> sq_T, <span class="keyword">template</span> <<span class="keyword">typename</span>> <span class="keyword">class </span>TEpdf>
127	<a name="l00100"></a>00100 <span class="keyword">class </span>mlnorm;
128	<a name="l00101"></a>00101
129	<a name="l00107"></a>00107 <span class="keyword">template</span><<span class="keyword">class</span> sq_T>
130	<a name="l00108"></a><a class="code" href="classbdm_1_1enorm.html">00108</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>
131	<a name="l00109"></a>00109 {
132	<a name="l00110"></a>00110 <span class="keyword">protected</span>:
133	<a name="l00112"></a><a class="code" href="classbdm_1_1enorm.html#c702a194720853570d08b65482f842c7">00112</a> vec <a class="code" href="classbdm_1_1enorm.html#c702a194720853570d08b65482f842c7" title="mean value">mu</a>;
134	<a name="l00114"></a><a class="code" href="classbdm_1_1enorm.html#2d92dde696b2a7a5b10ddef5d22ba2c2">00114</a> sq_T <a class="code" href="classbdm_1_1enorm.html#2d92dde696b2a7a5b10ddef5d22ba2c2" title="Covariance matrix in decomposed form.">R</a>;
135	<a name="l00115"></a>00115 <span class="keyword">public</span>:
136	<a name="l00118"></a>00118
137	<a name="l00119"></a>00119 <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> () {};
138	<a name="l00120"></a>00120 <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);}
139	<a name="l00121"></a>00121 <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>);
140	<a name="l00122"></a>00122 <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1enorm.html#61bd470764020bea6e1ed35000f259e6">from_setting</a> (<span class="keyword">const</span> Setting &root);
141	<a name="l00123"></a><a class="code" href="classbdm_1_1enorm.html#38eb17ecb75d94a50b6782fcf735cfea">00123</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1enorm.html#38eb17ecb75d94a50b6782fcf735cfea" title="This method TODO.">validate</a>() {
142	<a name="l00124"></a>00124 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>);
143	<a name="l00125"></a>00125 <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();
144	<a name="l00126"></a>00126 }
145	<a name="l00128"></a>00128
146	<a name="l00131"></a>00131
147	<a name="l00133"></a>00133 <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);
148	<a name="l00134"></a>00134
149	<a name="l00135"></a>00135 vec <a class="code" href="classbdm_1_1enorm.html#e1a48f52351ec3a349bd443b713b1766" title="Returns a sample, from density .">sample</a>() <span class="keyword">const</span>;
150	<a name="l00136"></a>00136
151	<a name="l00137"></a>00137 <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>;
152	<a name="l00138"></a>00138 <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>;
153	<a name="l00139"></a><a class="code" href="classbdm_1_1enorm.html#b2fa2915c35366392fe9bb022ca1a600">00139</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>;}
154	<a name="l00140"></a><a class="code" href="classbdm_1_1enorm.html#729c75ef0fa8abae03d58ad1f81e6773">00140</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());}
155	<a name="l00141"></a>00141 <span class="comment">// mlnorm<sq_T>* condition ( const RV &rvn ) const ; <=========== fails to cmpile. Why?</span>
156	<a name="l00142"></a>00142 <a class="code" href="classbdm_1_1shared__ptr.html">shared_ptr<mpdf></a> <a class="code" href="classbdm_1_1enorm.html#40201ca12c6900f7aeb493bb7c582e20" 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>;
157	<a name="l00143"></a>00143
158	<a name="l00144"></a>00144 <span class="comment">// target not typed to mlnorm<sq_T, enorm<sq_T> > &</span>
159	<a name="l00145"></a>00145 <span class="comment">// because that doesn't compile (perhaps because we</span>
160	<a name="l00146"></a>00146 <span class="comment">// haven't finished defining enorm yet), but the type</span>
161	<a name="l00147"></a>00147 <span class="comment">// is required</span>
162	<a name="l00148"></a>00148 <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1enorm.html#40201ca12c6900f7aeb493bb7c582e20" 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, <a class="code" href="classbdm_1_1mpdf.html" title="Conditional probability density, e.g. modeling , where is random variable, rv, and...">mpdf</a> &target ) <span class="keyword">const</span>;
163	<a name="l00149"></a>00149
164	<a name="l00150"></a>00150 <a class="code" href="classbdm_1_1shared__ptr.html">shared_ptr<epdf></a> <a class="code" href="classbdm_1_1enorm.html#dcb739443669ba0a8faf634196284c08" 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> &rvn ) <span class="keyword">const</span>;
165	<a name="l00151"></a>00151 <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1enorm.html#dcb739443669ba0a8faf634196284c08" 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> &rvn, <a class="code" href="classbdm_1_1enorm.html" title="Gaussian density with positive definite (decomposed) covariance matrix.">enorm<sq_T></a> &target ) <span class="keyword">const</span>;
166	<a name="l00153"></a>00153
167	<a name="l00156"></a>00156
168	<a name="l00157"></a>00157 vec& _mu() {<span class="keywordflow">return</span> <a class="code" href="classbdm_1_1enorm.html#c702a194720853570d08b65482f842c7" title="mean value">mu</a>;}
169	<a name="l00158"></a>00158 <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;}
170	<a name="l00159"></a>00159 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>;}
171	<a name="l00160"></a>00160 <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>;}
172	<a name="l00162"></a>00162
173	<a name="l00163"></a>00163 };
174	<a name="l00164"></a>00164 <a class="code" href="user__info_8h.html#b06f1e7c44a8306e321f62a0099210b9" title="Variant of UIREGISTER for templated classes.">UIREGISTER2</a> (enorm, chmat);
175	<a name="l00165"></a>00165 SHAREDPTR2 ( enorm, chmat );
176	<a name="l00166"></a>00166 <a class="code" href="user__info_8h.html#b06f1e7c44a8306e321f62a0099210b9" title="Variant of UIREGISTER for templated classes.">UIREGISTER2</a> (enorm, ldmat);
177	<a name="l00167"></a>00167 SHAREDPTR2 ( enorm, ldmat );
178	<a name="l00168"></a>00168 <a class="code" href="user__info_8h.html#b06f1e7c44a8306e321f62a0099210b9" title="Variant of UIREGISTER for templated classes.">UIREGISTER2</a> (enorm, fsqmat);
179	<a name="l00169"></a>00169 SHAREDPTR2 ( enorm, fsqmat );
180	<a name="l00170"></a>00170
181	<a name="l00171"></a>00171
182	<a name="l00178"></a><a class="code" href="classbdm_1_1egiw.html">00178</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>
183	<a name="l00179"></a>00179 {
184	<a name="l00180"></a>00180 <span class="keyword">protected</span>:
185	<a name="l00182"></a><a class="code" href="classbdm_1_1egiw.html#ae56852845c6af176fd9017dbebbbd52">00182</a> <a class="code" href="classbdm_1_1ldmat.html" title="Matrix stored in LD form, (commonly known as UD).">ldmat</a> <a class="code" href="classbdm_1_1egiw.html#ae56852845c6af176fd9017dbebbbd52" title="Extended information matrix of sufficient statistics.">V</a>;
186	<a name="l00184"></a><a class="code" href="classbdm_1_1egiw.html#447eacf19d4f4083872686f044814dc4">00184</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>;
187	<a name="l00186"></a><a class="code" href="classbdm_1_1egiw.html#23e4d78bea7e98840f3da30e76a2b57a">00186</a> <span class="keywordtype">int</span> <a class="code" href="classbdm_1_1egiw.html#23e4d78bea7e98840f3da30e76a2b57a" title="Dimension of the output.">dimx</a>;
188	<a name="l00188"></a><a class="code" href="classbdm_1_1egiw.html#322414c32d9a21a006a5aab0311f64fd">00188</a> <span class="keywordtype">int</span> <a class="code" href="classbdm_1_1egiw.html#322414c32d9a21a006a5aab0311f64fd" title="Dimension of the regressor.">nPsi</a>;
189	<a name="l00189"></a>00189 <span class="keyword">public</span>:
190	<a name="l00192"></a>00192 <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>() {};
191	<a name="l00193"></a>00193 <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="classbdm_1_1ldmat.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);};
192	<a name="l00194"></a>00194
193	<a name="l00195"></a>00195 <span class="keywordtype">void</span> set_parameters (<span class="keywordtype">int</span> dimx0, ldmat V0, <span class="keywordtype">double</span> nu0 = -1.0) {
194	<a name="l00196"></a>00196 <a class="code" href="classbdm_1_1egiw.html#23e4d78bea7e98840f3da30e76a2b57a" title="Dimension of the output.">dimx</a> = dimx0;
195	<a name="l00197"></a>00197 <a class="code" href="classbdm_1_1egiw.html#322414c32d9a21a006a5aab0311f64fd" title="Dimension of the regressor.">nPsi</a> = V0.rows() - <a class="code" href="classbdm_1_1egiw.html#23e4d78bea7e98840f3da30e76a2b57a" title="Dimension of the output.">dimx</a>;
196	<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>
197	<a name="l00199"></a>00199
198	<a name="l00200"></a>00200 <a class="code" href="classbdm_1_1egiw.html#ae56852845c6af176fd9017dbebbbd52" title="Extended information matrix of sufficient statistics.">V</a> = V0;
199	<a name="l00201"></a>00201 <span class="keywordflow">if</span> (nu0 < 0) {
200	<a name="l00202"></a>00202 <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>
201	<a name="l00203"></a>00203 <span class="comment">// terms before that are sufficient for finite normalization</span>
202	<a name="l00204"></a>00204 } <span class="keywordflow">else</span> {
203	<a name="l00205"></a>00205 <a class="code" href="classbdm_1_1egiw.html#447eacf19d4f4083872686f044814dc4" title="Number of data records (degrees of freedom) of sufficient statistics.">nu</a> = nu0;
204	<a name="l00206"></a>00206 }
205	<a name="l00207"></a>00207 }
206	<a name="l00209"></a>00209
207	<a name="l00210"></a>00210 vec <a class="code" href="classbdm_1_1egiw.html#920f21548b7a3723923dd108fe514c61" title="Returns a sample, from density .">sample</a>() <span class="keyword">const</span>;
208	<a name="l00211"></a>00211 vec <a class="code" href="classbdm_1_1egiw.html#df70c05f918c3a6f86d60f10c1fd6ba2" title="return expected value">mean</a>() <span class="keyword">const</span>;
209	<a name="l00212"></a>00212 vec <a class="code" href="classbdm_1_1egiw.html#c1ecc406613cc2341225dc10c3d3b46a" title="return expected variance (not covariance!)">variance</a>() <span class="keyword">const</span>;
210	<a name="l00213"></a>00213
211	<a name="l00215"></a>00215 vec <a class="code" href="classbdm_1_1egiw.html#66d2ba9295c306012b309efcc9e516f0" title="LS estimate of .">est_theta</a>() <span class="keyword">const</span>;
212	<a name="l00216"></a>00216
213	<a name="l00218"></a>00218 ldmat <a class="code" href="classbdm_1_1egiw.html#88c321a2051d1afdbb31a098896a717b" title="Covariance of the LS estimate.">est_theta_cov</a>() <span class="keyword">const</span>;
214	<a name="l00219"></a>00219
215	<a name="l00221"></a>00221 <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1egiw.html#d2075aa2306648b3e4fe40bb86628d5c" title="expected values of the linear coefficient and the covariance matrix are written to...">mean_mat</a> (mat &M, mat&R) <span class="keyword">const</span>;
216	<a name="l00223"></a>00223 <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>;
217	<a name="l00224"></a>00224 <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>;
218	<a name="l00225"></a><a class="code" href="classbdm_1_1egiw.html#8e610e95401a11baf34f65e16ecd87be">00225</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;};
219	<a name="l00226"></a>00226
220	<a name="l00229"></a>00229
221	<a name="l00230"></a>00230 <a class="code" href="classbdm_1_1ldmat.html" title="Matrix stored in LD form, (commonly known as UD).">ldmat</a>& _V() {<span class="keywordflow">return</span> V;}
222	<a name="l00231"></a>00231 <span class="keyword">const</span> ldmat& _V()<span class="keyword"> const </span>{<span class="keywordflow">return</span> V;}
223	<a name="l00232"></a>00232 <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>;}
224	<a name="l00233"></a>00233 <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>;}
225	<a name="l00234"></a><a class="code" href="classbdm_1_1egiw.html#55b76ec75bd2df5ef9cab3be20a33bbb">00234</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>) {
226	<a name="l00235"></a>00235 <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>, UI::compulsory);
227	<a name="l00236"></a>00236 <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>, UI::compulsory);
228	<a name="l00237"></a>00237 mat V;
229	<a name="l00238"></a>00238 <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);
230	<a name="l00239"></a>00239 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>);
231	<a name="l00240"></a>00240 <a class="code" href="classbdm_1_1shared__ptr.html" title="A naive implementation of roughly a subset of the std::tr1:shared_ptr spec.">shared_ptr<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);
232	<a name="l00241"></a>00241 <a class="code" href="classbdm_1_1epdf.html#f423e28448dbb69ef4905295ec8de8ff" title="Name its rv.">set_rv</a> (*rv);
233	<a name="l00242"></a>00242 }
234	<a name="l00244"></a>00244 };
235	<a name="l00245"></a>00245 <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 );
236	<a name="l00246"></a>00246 SHAREDPTR ( egiw );
237	<a name="l00247"></a>00247
238	<a name="l00256"></a><a class="code" href="classbdm_1_1eDirich.html">00256</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>
239	<a name="l00257"></a>00257 {
240	<a name="l00258"></a>00258 <span class="keyword">protected</span>:
241	<a name="l00260"></a><a class="code" href="classbdm_1_1eDirich.html#f25886a49b4667af61245de81c83b5d2">00260</a> vec <a class="code" href="classbdm_1_1eDirich.html#f25886a49b4667af61245de81c83b5d2" title="sufficient statistics">beta</a>;
242	<a name="l00261"></a>00261 <span class="keyword">public</span>:
243	<a name="l00264"></a>00264
244	<a name="l00265"></a>00265 <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> () {};
245	<a name="l00266"></a>00266 <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>);};
246	<a name="l00267"></a>00267 eDirich (<span class="keyword">const</span> vec &beta0) {set_parameters (beta0);};
247	<a name="l00268"></a>00268 <span class="keywordtype">void</span> set_parameters (<span class="keyword">const</span> vec &beta0) {
248	<a name="l00269"></a>00269 <a class="code" href="classbdm_1_1eDirich.html#f25886a49b4667af61245de81c83b5d2" title="sufficient statistics">beta</a> = beta0;
249	<a name="l00270"></a>00270 <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();
250	<a name="l00271"></a>00271 }
251	<a name="l00273"></a>00273
252	<a name="l00274"></a><a class="code" href="classbdm_1_1eDirich.html#3290613d31d58daa8a45a54b003871fc">00274</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);};
253	<a name="l00275"></a><a class="code" href="classbdm_1_1eDirich.html#cb343355ec791298bb5a3404cd482fb6">00275</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>);};
254	<a name="l00276"></a><a class="code" href="classbdm_1_1eDirich.html#43c547a2507e233706f92712d8c2aacc">00276</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));}
255	<a name="l00278"></a><a class="code" href="classbdm_1_1eDirich.html#e09a24938e80c3d94b0ee842d1552318">00278</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>{
256	<a name="l00279"></a>00279 <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="l00280"></a>00280 <span class="comment">// it_assert_debug ( std::isfinite ( tmp ),"Infinite value" );</span>
258	<a name="l00281"></a>00281 <span class="keywordflow">return</span> tmp;
259	<a name="l00282"></a>00282 };
260	<a name="l00283"></a><a class="code" href="classbdm_1_1eDirich.html#279a99f6266c82fe2273e83841f19eb2">00283</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="l00284"></a>00284 <span class="keywordtype">double</span> tmp;
262	<a name="l00285"></a>00285 <span class="keywordtype">double</span> gam = sum (<a class="code" href="classbdm_1_1eDirich.html#f25886a49b4667af61245de81c83b5d2" title="sufficient statistics">beta</a>);
263	<a name="l00286"></a>00286 <span class="keywordtype">double</span> lgb = 0.0;
264	<a name="l00287"></a>00287 <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));}
265	<a name="l00288"></a>00288 tmp = lgb - lgamma (gam);
266	<a name="l00289"></a>00289 <span class="comment">// it_assert_debug ( std::isfinite ( tmp ),"Infinite value" );</span>
267	<a name="l00290"></a>00290 <span class="keywordflow">return</span> tmp;
268	<a name="l00291"></a>00291 };
269	<a name="l00293"></a><a class="code" href="classbdm_1_1eDirich.html#175e0add26d2105c28d8121eefb9e324">00293</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>;}
270	<a name="l00295"></a>00295 };
271	<a name="l00296"></a>00296
272	<a name="l00298"></a><a class="code" href="classbdm_1_1multiBM.html">00298</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>
273	<a name="l00299"></a>00299 {
274	<a name="l00300"></a>00300 <span class="keyword">protected</span>:
275	<a name="l00302"></a><a class="code" href="classbdm_1_1multiBM.html#9ecc6878abbd20eb8d8e43b6ab3f941a">00302</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>;
276	<a name="l00304"></a><a class="code" href="classbdm_1_1multiBM.html#044263356944c92209eecd39a5187d25">00304</a> vec &<a class="code" href="classbdm_1_1multiBM.html#044263356944c92209eecd39a5187d25" title="Pointer inside est to sufficient statistics.">beta</a>;
277	<a name="l00305"></a>00305 <span class="keyword">public</span>:
278	<a name="l00307"></a><a class="code" href="classbdm_1_1multiBM.html#c4dd6d9522a8a605776d21bac9bd9daf">00307</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()) {
279	<a name="l00308"></a>00308 <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>();}
280	<a name="l00309"></a>00309 <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;}
281	<a name="l00310"></a>00310 }
282	<a name="l00312"></a><a class="code" href="classbdm_1_1multiBM.html#c4378cf8037f6bed29c74eea63344b31">00312</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()) {}
283	<a name="l00314"></a><a class="code" href="classbdm_1_1multiBM.html#dbe6b90d410dc062a233d1dc09eeba52">00314</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>;}
284	<a name="l00315"></a><a class="code" href="classbdm_1_1multiBM.html#1e4bf41b61937fd80f34049742e23f95">00315</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) {
285	<a name="l00316"></a>00316 <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>();}
286	<a name="l00317"></a>00317 <a class="code" href="classbdm_1_1multiBM.html#044263356944c92209eecd39a5187d25" title="Pointer inside est to sufficient statistics.">beta</a> += dt;
287	<a name="l00318"></a>00318 <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>;}
288	<a name="l00319"></a>00319 }
289	<a name="l00320"></a><a class="code" href="classbdm_1_1multiBM.html#e157b607c1e3fa91d42aeea44458e2bf">00320</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>{
290	<a name="l00321"></a>00321 <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>);
291	<a name="l00322"></a>00322 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>();
292	<a name="l00323"></a>00323
293	<a name="l00324"></a>00324 <span class="keywordtype">double</span> lll;
294	<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)
295	<a name="l00326"></a>00326 {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>();}
296	<a name="l00327"></a>00327 <span class="keywordflow">else</span>
297	<a name="l00328"></a>00328 <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>;}
298	<a name="l00329"></a>00329 <span class="keywordflow">else</span>{lll = pred.<a class="code" href="classbdm_1_1eDirich.html#279a99f6266c82fe2273e83841f19eb2" title="logarithm of the normalizing constant, ">lognc</a>();}
299	<a name="l00330"></a>00330
300	<a name="l00331"></a>00331 beta += dt;
301	<a name="l00332"></a>00332 <span class="keywordflow">return</span> pred.<a class="code" href="classbdm_1_1eDirich.html#279a99f6266c82fe2273e83841f19eb2" title="logarithm of the normalizing constant, ">lognc</a>() - lll;
302	<a name="l00333"></a>00333 }
303	<a name="l00334"></a><a class="code" href="classbdm_1_1multiBM.html#aaeb18c989088feb8d26d300e4971732">00334</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) {
304	<a name="l00335"></a>00335 <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);
305	<a name="l00336"></a>00336 <span class="comment">// sum(beta) should be equal to sum(B.beta)</span>
306	<a name="l00337"></a>00337 <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>
307	<a name="l00338"></a>00338 <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>));
308	<a name="l00339"></a>00339 <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>();}
309	<a name="l00340"></a>00340 }
310	<a name="l00342"></a><a class="code" href="classbdm_1_1multiBM.html#31ff93f89473f099e489b9e1dc8d9513">00342</a> <span class="keyword">const</span> <a class="code" href="classbdm_1_1eDirich.html" title="Dirichlet posterior density.">eDirich</a>& <a class="code" href="classbdm_1_1multiBM.html#31ff93f89473f099e489b9e1dc8d9513" title="reimplemnetation of BM::posterior()">posterior</a>()<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>;};
311	<a name="l00344"></a><a class="code" href="classbdm_1_1multiBM.html#7a480eace4446661bacca94c57499f01">00344</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1multiBM.html#7a480eace4446661bacca94c57499f01" title="constructor function">set_parameters</a> (<span class="keyword">const</span> vec &beta0) {
312	<a name="l00345"></a>00345 <a class="code" href="classbdm_1_1multiBM.html#9ecc6878abbd20eb8d8e43b6ab3f941a" title="Conjugate prior and posterior.">est</a>.<a class="code" href="classbdm_1_1eDirich.html#a06af2376976a33e1eceaed7e8da75a5">set_parameters</a> (beta0);
313	<a name="l00346"></a>00346 <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="l00347"></a>00347 }
315	<a name="l00348"></a>00348 };
316	<a name="l00349"></a>00349
317	<a name="l00359"></a><a class="code" href="classbdm_1_1egamma.html">00359</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>
318	<a name="l00360"></a>00360 {
319	<a name="l00361"></a>00361 <span class="keyword">protected</span>:
320	<a name="l00363"></a><a class="code" href="classbdm_1_1egamma.html#0901ec983e66b8337aaa506e13b122fa">00363</a> vec <a class="code" href="classbdm_1_1egamma.html#0901ec983e66b8337aaa506e13b122fa" title="Vector .">alpha</a>;
321	<a name="l00365"></a><a class="code" href="classbdm_1_1egamma.html#457bfb1ccb2057df85073e519a15ccc1">00365</a> vec <a class="code" href="classbdm_1_1egamma.html#457bfb1ccb2057df85073e519a15ccc1" title="Vector .">beta</a>;
322	<a name="l00366"></a>00366 <span class="keyword">public</span> :
323	<a name="l00369"></a>00369 <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) {};
324	<a name="l00370"></a>00370 <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);};
325	<a name="l00371"></a>00371 <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();};
326	<a name="l00373"></a>00373
327	<a name="l00374"></a>00374 vec <a class="code" href="classbdm_1_1egamma.html#6ed82f0fd05f6002487256d8e75a0bbd" title="Returns a sample, from density .">sample</a>() <span class="keyword">const</span>;
328	<a name="l00375"></a>00375 <span class="keywordtype">double</span> <a class="code" href="classbdm_1_1egamma.html#a8e11e5a580ff42a1b205974c60768c6" title="Evaluate normalized log-probability.">evallog</a> (<span class="keyword">const</span> vec &val) <span class="keyword">const</span>;
329	<a name="l00376"></a>00376 <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>;
330	<a name="l00378"></a><a class="code" href="classbdm_1_1egamma.html#0865cb3d6339fdc7410806cf70a329ed">00378</a> vec& <a class="code" href="classbdm_1_1egamma.html#0865cb3d6339fdc7410806cf70a329ed" title="Returns pointer to internal alpha. 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>;}
331	<a name="l00380"></a><a class="code" href="classbdm_1_1egamma.html#c42cadd9cbd344caaa69b0b433cd16ca">00380</a> vec& <a class="code" href="classbdm_1_1egamma.html#c42cadd9cbd344caaa69b0b433cd16ca" title="Returns pointer to internal beta. Potentially dengerous: use with care!">_beta</a>() {<span class="keywordflow">return</span> beta;}
332	<a name="l00381"></a><a class="code" href="classbdm_1_1egamma.html#49d256c42cce14c6faa56ec242b57e85">00381</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);}
333	<a name="l00382"></a><a class="code" href="classbdm_1_1egamma.html#36986cc01917cd0796fadc17125bdec1">00382</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)); }
334	<a name="l00383"></a>00383
335	<a name="l00392"></a><a class="code" href="classbdm_1_1egamma.html#8a6fd1a1c0190f3e0d95a2a1f99aafc1">00392</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>) {
336	<a name="l00393"></a>00393 <a class="code" href="classbdm_1_1egamma.html#8a6fd1a1c0190f3e0d95a2a1f99aafc1">epdf::from_setting</a> (<span class="keyword">set</span>); <span class="comment">// reads rv</span>
337	<a name="l00394"></a>00394 <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);
338	<a name="l00395"></a>00395 <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);
339	<a name="l00396"></a>00396 <a class="code" href="classbdm_1_1egamma.html#c3a8d8ae8ba79d0fb35036711fa7d127" title="This method TODO.">validate</a>();
340	<a name="l00397"></a>00397 }
341	<a name="l00398"></a><a class="code" href="classbdm_1_1egamma.html#c3a8d8ae8ba79d0fb35036711fa7d127">00398</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1egamma.html#c3a8d8ae8ba79d0fb35036711fa7d127" title="This method TODO.">validate</a>() {
342	<a name="l00399"></a>00399 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>);
343	<a name="l00400"></a>00400 <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();
344	<a name="l00401"></a>00401 }
345	<a name="l00402"></a>00402 };
346	<a name="l00403"></a>00403 <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);
347	<a name="l00404"></a>00404 SHAREDPTR ( egamma );
348	<a name="l00405"></a>00405
349	<a name="l00422"></a><a class="code" href="classbdm_1_1eigamma.html">00422</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>
350	<a name="l00423"></a>00423 {
351	<a name="l00424"></a>00424 <span class="keyword">protected</span>:
352	<a name="l00425"></a>00425 <span class="keyword">public</span> :
353	<a name="l00430"></a>00430
354	<a name="l00431"></a><a class="code" href="classbdm_1_1eigamma.html#3aff7bf25ddac27731c60826fcfd878f">00431</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>();};
355	<a name="l00433"></a><a class="code" href="classbdm_1_1eigamma.html#46cecb295edbabd28120cb0f6f572bcb">00433</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);}
356	<a name="l00434"></a><a class="code" href="classbdm_1_1eigamma.html#c2c696f8c668e9f65392c9449f6a5133">00434</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);}
357	<a name="l00435"></a>00435 };
358	<a name="l00436"></a>00436 <span class="comment">/*</span>
359	<a name="l00438"></a>00438 <span class="comment">class emix : public epdf {</span>
360	<a name="l00439"></a>00439 <span class="comment">protected:</span>
361	<a name="l00440"></a>00440 <span class="comment"> int n;</span>
362	<a name="l00441"></a>00441 <span class="comment"> vec &w;</span>
363	<a name="l00442"></a>00442 <span class="comment"> Array<epdf*> Coms;</span>
364	<a name="l00443"></a>00443 <span class="comment">public:</span>
365	<a name="l00445"></a>00445 <span class="comment"> emix ( const RV &rv, vec &w0): epdf(rv), n(w0.length()), w(w0), Coms(n) {};</span>
366	<a name="l00446"></a>00446 <span class="comment"> void set_parameters( int &i, double wi, epdf* ep){w(i)=wi;Coms(i)=ep;}</span>
367	<a name="l00447"></a>00447 <span class="comment"> vec mean(){vec pom; for(int i=0;i<n;i++){pom+=Coms(i)->mean()*w(i);} return pom;};</span>
368	<a name="l00448"></a>00448 <span class="comment"> vec sample() {it_error ( "Not implemented" );return 0;}</span>
369	<a name="l00449"></a>00449 <span class="comment">};</span>
370	<a name="l00450"></a>00450 <span class="comment">*/</span>
371	<a name="l00451"></a>00451
372	<a name="l00453"></a>00453
373	<a name="l00454"></a><a class="code" href="classbdm_1_1euni.html">00454</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>
374	<a name="l00455"></a>00455 {
375	<a name="l00456"></a>00456 <span class="keyword">protected</span>:
376	<a name="l00458"></a><a class="code" href="classbdm_1_1euni.html#ff7ce6a2ef5ef0015bbd1398bed12f32">00458</a> vec <a class="code" href="classbdm_1_1euni.html#ff7ce6a2ef5ef0015bbd1398bed12f32" title="lower bound on support">low</a>;
377	<a name="l00460"></a><a class="code" href="classbdm_1_1euni.html#cfad2dea4a62db6872bda8abd75f0de1">00460</a> vec <a class="code" href="classbdm_1_1euni.html#cfad2dea4a62db6872bda8abd75f0de1" title="upper bound on support">high</a>;
378	<a name="l00462"></a><a class="code" href="classbdm_1_1euni.html#d3c27e331f90c754d80228108de8ed4c">00462</a> vec <a class="code" href="classbdm_1_1euni.html#d3c27e331f90c754d80228108de8ed4c" title="internal">distance</a>;
379	<a name="l00464"></a><a class="code" href="classbdm_1_1euni.html#31bb13e8449a8eff35246d46dae35c20">00464</a> <span class="keywordtype">double</span> <a class="code" href="classbdm_1_1euni.html#31bb13e8449a8eff35246d46dae35c20" title="normalizing coefficients">nk</a>;
380	<a name="l00466"></a><a class="code" href="classbdm_1_1euni.html#3e63be48dd58659663ca60cd18700476">00466</a> <span class="keywordtype">double</span> <a class="code" href="classbdm_1_1euni.html#3e63be48dd58659663ca60cd18700476" title="cache of log( nk )">lnk</a>;
381	<a name="l00467"></a>00467 <span class="keyword">public</span>:
382	<a name="l00470"></a>00470 <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> () {}
383	<a name="l00471"></a>00471 <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);}
384	<a name="l00472"></a>00472 <span class="keywordtype">void</span> set_parameters (<span class="keyword">const</span> vec &low0, <span class="keyword">const</span> vec &high0) {
385	<a name="l00473"></a>00473 <a class="code" href="classbdm_1_1euni.html#d3c27e331f90c754d80228108de8ed4c" title="internal">distance</a> = high0 - low0;
386	<a name="l00474"></a>00474 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>);
387	<a name="l00475"></a>00475 <a class="code" href="classbdm_1_1euni.html#ff7ce6a2ef5ef0015bbd1398bed12f32" title="lower bound on support">low</a> = low0;
388	<a name="l00476"></a>00476 <a class="code" href="classbdm_1_1euni.html#cfad2dea4a62db6872bda8abd75f0de1" title="upper bound on support">high</a> = high0;
389	<a name="l00477"></a>00477 <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>);
390	<a name="l00478"></a>00478 <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>);
391	<a name="l00479"></a>00479 <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();
392	<a name="l00480"></a>00480 }
393	<a name="l00482"></a>00482
394	<a name="l00483"></a><a class="code" href="classbdm_1_1euni.html#caa07b8307bd793d5339d6583e0aba81">00483</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>{
395	<a name="l00484"></a>00484 <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;}
396	<a name="l00485"></a>00485 <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>;
397	<a name="l00486"></a>00486 }
398	<a name="l00487"></a><a class="code" href="classbdm_1_1euni.html#fc5df80359ead2918384b2004ce67194">00487</a> vec <a class="code" href="classbdm_1_1euni.html#fc5df80359ead2918384b2004ce67194" title="Returns a sample, from density .">sample</a>()<span class="keyword"> const </span>{
399	<a name="l00488"></a>00488 vec smp (<a class="code" href="classbdm_1_1epdf.html#16adac20ec7fe07e1ea0b27d917788ce" title="dimension of the random variable">dim</a>);
400	<a name="l00489"></a>00489 <span class="preprocessor">#pragma omp critical</span>
401	<a name="l00490"></a>00490 <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);
402	<a name="l00491"></a>00491 <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);
403	<a name="l00492"></a>00492 }
404	<a name="l00494"></a><a class="code" href="classbdm_1_1euni.html#46caa8c13aba2e6228f964208918b226">00494</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;}
405	<a name="l00495"></a><a class="code" href="classbdm_1_1euni.html#951f932155111f6053c980f672b4c22c">00495</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;}
406	<a name="l00504"></a><a class="code" href="classbdm_1_1euni.html#77f5fef1f006fe056066da23b9e5f042">00504</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>) {
407	<a name="l00505"></a>00505 <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>
408	<a name="l00506"></a>00506
409	<a name="l00507"></a>00507 <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);
410	<a name="l00508"></a>00508 <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);
411	<a name="l00509"></a>00509 }
412	<a name="l00510"></a>00510 };
413	<a name="l00511"></a>00511
414	<a name="l00512"></a>00512
415	<a name="l00518"></a>00518 <span class="keyword">template</span> < <span class="keyword">class</span> sq_T, <span class="keyword">template</span> <<span class="keyword">typename</span>> <span class="keyword">class </span>TEpdf = enorm >
416	<a name="l00519"></a><a class="code" href="classbdm_1_1mlnorm.html">00519</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_1mpdf__internal.html" title="Mpdf with internal epdf that is modified by function condition.">mpdf_internal</a>< TEpdf<sq_T> >
417	<a name="l00520"></a>00520 {
418	<a name="l00521"></a>00521 <span class="keyword">protected</span>:
419	<a name="l00523"></a><a class="code" href="classbdm_1_1mlnorm.html#c71bbf59fc732beb2b459d7117bd6e42">00523</a> mat <a class="code" href="classbdm_1_1mlnorm.html#c71bbf59fc732beb2b459d7117bd6e42" title="Internal epdf that arise by conditioning on rvc.">A</a>;
420	<a name="l00525"></a><a class="code" href="classbdm_1_1mlnorm.html#831b50121cad10aa03a16682bd0c3ed6">00525</a> vec <a class="code" href="classbdm_1_1mlnorm.html#831b50121cad10aa03a16682bd0c3ed6" title="Constant additive term.">mu_const</a>;
421	<a name="l00526"></a>00526 <span class="comment">// vec& _mu; //cached epdf.mu; !!!!!! WHY NOT?</span>
422	<a name="l00527"></a>00527 <span class="keyword">public</span>:
423	<a name="l00530"></a>00530 <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_1mpdf__internal.html" title="Mpdf with internal epdf that is modified by function condition.">mpdf_internal</a>< TEpdf<sq_T> >() {};
424	<a name="l00531"></a>00531 <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 class="code" href="classbdm_1_1mlnorm.html#c71bbf59fc732beb2b459d7117bd6e42" title="Internal epdf that arise by conditioning on rvc.">A</a>, <span class="keyword">const</span> vec &mu0, <span class="keyword">const</span> sq_T &R) : <a class="code" href="classbdm_1_1mpdf__internal.html" title="Mpdf with internal epdf that is modified by function condition.">mpdf_internal</a>< TEpdf<sq_T> >() {
425	<a name="l00532"></a>00532 <a class="code" href="classbdm_1_1mlnorm.html#04f7c6cda7b2f95161dd5fbcf15d1fd5" title="Set A and R.">set_parameters</a> (A, mu0, R);
426	<a name="l00533"></a>00533 }
427	<a name="l00534"></a>00534
428	<a name="l00536"></a><a class="code" href="classbdm_1_1mlnorm.html#04f7c6cda7b2f95161dd5fbcf15d1fd5">00536</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1mlnorm.html#04f7c6cda7b2f95161dd5fbcf15d1fd5" title="Set A and R.">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) {
429	<a name="l00537"></a>00537 it_assert_debug (A0.rows() == mu0.length(), <span class="stringliteral">""</span>);
430	<a name="l00538"></a>00538 it_assert_debug (A0.rows() == R0.rows(), <span class="stringliteral">""</span>);
431	<a name="l00539"></a>00539
432	<a name="l00540"></a>00540 this-><a class="code" href="classbdm_1_1mpdf__internal.html#47bab632af15120c88aad647ae129468" title="Internal epdf used for sampling.">iepdf</a>.set_parameters (zeros (A0.rows()), R0);
433	<a name="l00541"></a>00541 <a class="code" href="classbdm_1_1mlnorm.html#c71bbf59fc732beb2b459d7117bd6e42" title="Internal epdf that arise by conditioning on rvc.">A</a> = A0;
434	<a name="l00542"></a>00542 <a class="code" href="classbdm_1_1mlnorm.html#831b50121cad10aa03a16682bd0c3ed6" title="Constant additive term.">mu_const</a> = mu0;
435	<a name="l00543"></a>00543 this-><a class="code" href="classbdm_1_1mpdf.html#7c1900976ff13dbc09c9729b3bbff9e6" title="dimension of the condition">dimc</a> = A0.cols();
436	<a name="l00544"></a>00544 }
437	<a name="l00547"></a><a class="code" href="classbdm_1_1mlnorm.html#c2895ae549ee76d961be98d7061bd110">00547</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1mlnorm.html#c2895ae549ee76d961be98d7061bd110">condition</a> (<span class="keyword">const</span> vec &cond) {
438	<a name="l00548"></a>00548 this-><a class="code" href="classbdm_1_1mpdf__internal.html#47bab632af15120c88aad647ae129468" title="Internal epdf used for sampling.">iepdf</a>._mu() = <a class="code" href="classbdm_1_1mlnorm.html#c71bbf59fc732beb2b459d7117bd6e42" title="Internal epdf that arise by conditioning on rvc.">A</a> * cond + <a class="code" href="classbdm_1_1mlnorm.html#831b50121cad10aa03a16682bd0c3ed6" title="Constant additive term.">mu_const</a>;
439	<a name="l00549"></a>00549 <span class="comment">//R is already assigned;</span>
440	<a name="l00550"></a>00550 }
441	<a name="l00551"></a>00551
442	<a name="l00553"></a><a class="code" href="classbdm_1_1mlnorm.html#6332e5200f3afa15db3f7f4bca09b17f">00553</a> vec& <a class="code" href="classbdm_1_1mlnorm.html#6332e5200f3afa15db3f7f4bca09b17f" title="access function">_mu_const</a>() {<span class="keywordflow">return</span> <a class="code" href="classbdm_1_1mlnorm.html#831b50121cad10aa03a16682bd0c3ed6" title="Constant additive term.">mu_const</a>;}
443	<a name="l00555"></a><a class="code" href="classbdm_1_1mlnorm.html#b256b547c5156b5898a3a1e5462f9540">00555</a> mat& <a class="code" href="classbdm_1_1mlnorm.html#b256b547c5156b5898a3a1e5462f9540" title="access function">_A</a>() {<span class="keywordflow">return</span> <a class="code" href="classbdm_1_1mlnorm.html#c71bbf59fc732beb2b459d7117bd6e42" title="Internal epdf that arise by conditioning on rvc.">A</a>;}
444	<a name="l00557"></a><a class="code" href="classbdm_1_1mlnorm.html#564715dea56f7bbff0083aec295ce97e">00557</a> mat <a class="code" href="classbdm_1_1mlnorm.html#564715dea56f7bbff0083aec295ce97e" title="access function">_R</a>() { <span class="keywordflow">return</span> this-><a class="code" href="classbdm_1_1mpdf__internal.html#47bab632af15120c88aad647ae129468" title="Internal epdf used for sampling.">iepdf</a>._R().to_mat(); }
445	<a name="l00558"></a>00558
446	<a name="l00560"></a>00560 <span class="keyword">template</span><<span class="keyword">typename</span> sq_M>
447	<a name="l00561"></a>00561 <span class="keyword">friend</span> std::ostream &operator<< (std::ostream &os, mlnorm<sq_M, enorm> &ml);
448	<a name="l00562"></a>00562
449	<a name="l00563"></a><a class="code" href="classbdm_1_1mlnorm.html#52980f13d80162d00b30d5864343f564">00563</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1mlnorm.html#52980f13d80162d00b30d5864343f564">from_setting</a> (<span class="keyword">const</span> Setting &<span class="keyword">set</span>) {
450	<a name="l00564"></a>00564 <a class="code" href="classbdm_1_1mlnorm.html#52980f13d80162d00b30d5864343f564">mpdf::from_setting</a> (<span class="keyword">set</span>);
451	<a name="l00565"></a>00565
452	<a name="l00566"></a>00566 <a class="code" href="classbdm_1_1UI.html#cd1667e6fec99ec64dabcb3ca2ff922d">UI::get</a> (<a class="code" href="classbdm_1_1mlnorm.html#c71bbf59fc732beb2b459d7117bd6e42" title="Internal epdf that arise by conditioning on rvc.">A</a>, <span class="keyword">set</span>, <span class="stringliteral">"A"</span>, UI::compulsory);
453	<a name="l00567"></a>00567 <a class="code" href="classbdm_1_1UI.html#cd1667e6fec99ec64dabcb3ca2ff922d">UI::get</a> (<a class="code" href="classbdm_1_1mlnorm.html#831b50121cad10aa03a16682bd0c3ed6" title="Constant additive term.">mu_const</a>, <span class="keyword">set</span>, <span class="stringliteral">"const"</span>, UI::compulsory);
454	<a name="l00568"></a>00568 mat R0;
455	<a name="l00569"></a>00569 <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="l00570"></a>00570 <a class="code" href="classbdm_1_1mlnorm.html#04f7c6cda7b2f95161dd5fbcf15d1fd5" title="Set A and R.">set_parameters</a> (<a class="code" href="classbdm_1_1mlnorm.html#c71bbf59fc732beb2b459d7117bd6e42" title="Internal epdf that arise by conditioning on rvc.">A</a>, <a class="code" href="classbdm_1_1mlnorm.html#831b50121cad10aa03a16682bd0c3ed6" title="Constant additive term.">mu_const</a>, R0);
457	<a name="l00571"></a>00571 };
458	<a name="l00572"></a>00572 };
459	<a name="l00573"></a>00573 <a class="code" href="user__info_8h.html#b06f1e7c44a8306e321f62a0099210b9" title="Variant of UIREGISTER for templated classes.">UIREGISTER2</a> (mlnorm,ldmat);
460	<a name="l00574"></a>00574 SHAREDPTR2 ( mlnorm, ldmat );
461	<a name="l00575"></a>00575 <a class="code" href="user__info_8h.html#b06f1e7c44a8306e321f62a0099210b9" title="Variant of UIREGISTER for templated classes.">UIREGISTER2</a> (mlnorm,fsqmat);
462	<a name="l00576"></a>00576 SHAREDPTR2 ( mlnorm, fsqmat );
463	<a name="l00577"></a>00577 <a class="code" href="user__info_8h.html#b06f1e7c44a8306e321f62a0099210b9" title="Variant of UIREGISTER for templated classes.">UIREGISTER2</a> (mlnorm, chmat);
464	<a name="l00578"></a>00578 SHAREDPTR2 ( mlnorm, chmat );
465	<a name="l00579"></a>00579
466	<a name="l00581"></a>00581 <span class="keyword">template</span><<span class="keyword">class</span> sq_T>
467	<a name="l00582"></a><a class="code" href="classbdm_1_1mgnorm.html">00582</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_1mpdf__internal.html" title="Mpdf with internal epdf that is modified by function condition.">mpdf_internal</a>< enorm< sq_T > >
468	<a name="l00583"></a>00583 {
469	<a name="l00584"></a>00584 <span class="keyword">private</span>:
470	<a name="l00585"></a>00585 <span class="comment">// vec &mu; WHY NOT?</span>
471	<a name="l00586"></a>00586 <a class="code" href="classbdm_1_1shared__ptr.html">shared_ptr<fnc></a> g;
472	<a name="l00587"></a>00587
473	<a name="l00588"></a>00588 <span class="keyword">public</span>:
474	<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_1mpdf__internal.html" title="Mpdf with internal epdf that is modified by function condition.">mpdf_internal</a><<a class="code" href="classbdm_1_1enorm.html" title="Gaussian density with positive definite (decomposed) covariance matrix.">enorm</a><sq_T> >() { }
475	<a name="l00592"></a>00592 <span class="keyword">inline</span> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1mgnorm.html#b736332d20e418bf50d45836e129f339" title="set mean function">set_parameters</a> (<span class="keyword">const</span> <a class="code" href="classbdm_1_1shared__ptr.html">shared_ptr<fnc></a> &g0, <span class="keyword">const</span> sq_T &R0);
476	<a name="l00593"></a>00593 <span class="keyword">inline</span> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1mgnorm.html#b31d63472cf6a1030cd8dbd8094c1f6d">condition</a> (<span class="keyword">const</span> vec &cond);
477	<a name="l00594"></a>00594
478	<a name="l00595"></a>00595
479	<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>) {
480	<a name="l00624"></a>00624 <a class="code" href="classbdm_1_1shared__ptr.html">shared_ptr<fnc></a> g = UI::build<fnc> (<span class="keyword">set</span>, <span class="stringliteral">"g"</span>, UI::compulsory);
481	<a name="l00625"></a>00625
482	<a name="l00626"></a>00626 mat R;
483	<a name="l00627"></a>00627 vec dR;
484	<a name="l00628"></a>00628 <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>))
485	<a name="l00629"></a>00629 R = diag (dR);
486	<a name="l00630"></a>00630 <span class="keywordflow">else</span>
487	<a name="l00631"></a>00631 <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);
488	<a name="l00632"></a>00632
489	<a name="l00633"></a>00633 <a class="code" href="classbdm_1_1mgnorm.html#b736332d20e418bf50d45836e129f339" title="set mean function">set_parameters</a> (g, R);
490	<a name="l00634"></a>00634 }
491	<a name="l00635"></a>00635 };
492	<a name="l00636"></a>00636
493	<a name="l00637"></a>00637 <a class="code" href="user__info_8h.html#b06f1e7c44a8306e321f62a0099210b9" title="Variant of UIREGISTER for templated classes.">UIREGISTER2</a> (mgnorm, chmat);
494	<a name="l00638"></a>00638 SHAREDPTR2 ( mgnorm, chmat );
495	<a name="l00639"></a>00639
496	<a name="l00640"></a>00640
497	<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, enorm>
498	<a name="l00649"></a>00649 {
499	<a name="l00650"></a>00650 <span class="keyword">protected</span>:
500	<a name="l00652"></a><a class="code" href="classbdm_1_1mlstudent.html#41595144a79594acbe288c6b59412657">00652</a> <a class="code" href="classbdm_1_1ldmat.html" title="Matrix stored in LD form, (commonly known as UD).">ldmat</a> <a class="code" href="classbdm_1_1mlstudent.html#41595144a79594acbe288c6b59412657" title="Variable from theory.">Lambda</a>;
501	<a name="l00654"></a><a class="code" href="classbdm_1_1mlstudent.html#72e9bda4d6684e07faafc4b2192daf39">00654</a> <a class="code" href="classbdm_1_1ldmat.html" title="Matrix stored in LD form, (commonly known as UD).">ldmat</a> &<a class="code" href="classbdm_1_1mlnorm.html#564715dea56f7bbff0083aec295ce97e" title="access function">_R</a>;
502	<a name="l00656"></a><a class="code" href="classbdm_1_1mlstudent.html#1c063ad6cb6e079ee11bc4128c2c9fe8">00656</a> <a class="code" href="classbdm_1_1ldmat.html" title="Matrix stored in LD form, (commonly known as UD).">ldmat</a> <a class="code" href="classbdm_1_1mlstudent.html#1c063ad6cb6e079ee11bc4128c2c9fe8" title="Variable .">Re</a>;
503	<a name="l00657"></a>00657 <span class="keyword">public</span>:
504	<a name="l00658"></a>00658 <a class="code" href="classbdm_1_1mlstudent.html">mlstudent</a> () : <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_1ldmat.html" title="Matrix stored in LD form, (commonly known as UD).">ldmat</a>, <a class="code" href="classbdm_1_1enorm.html" title="Gaussian density with positive definite (decomposed) covariance matrix.">enorm</a>> (),
505	<a name="l00659"></a>00659 <a class="code" href="classbdm_1_1mlstudent.html#41595144a79594acbe288c6b59412657" title="Variable from theory.">Lambda</a> (), <a class="code" href="classbdm_1_1mlnorm.html#564715dea56f7bbff0083aec295ce97e" title="access function">_R</a> (<a class="code" href="classbdm_1_1mpdf__internal.html#47bab632af15120c88aad647ae129468" title="Internal epdf used for sampling.">iepdf</a>.<a class="code" href="classbdm_1_1mlnorm.html#564715dea56f7bbff0083aec295ce97e" title="access function">_R</a>()) {}
506	<a name="l00661"></a><a class="code" href="classbdm_1_1mlstudent.html#4cdf79aac1b2165c0290e73810a0e4a3">00661</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1mlstudent.html#4cdf79aac1b2165c0290e73810a0e4a3" title="constructor function">set_parameters</a> (<span class="keyword">const</span> mat &A0, <span class="keyword">const</span> vec &mu0, <span class="keyword">const</span> <a class="code" href="classbdm_1_1ldmat.html" title="Matrix stored in LD form, (commonly known as UD).">ldmat</a> &R0, <span class="keyword">const</span> <a class="code" href="classbdm_1_1ldmat.html" title="Matrix stored in LD form, (commonly known as UD).">ldmat</a>& Lambda0) {
507	<a name="l00662"></a>00662 it_assert_debug (A0.rows() == mu0.length(), <span class="stringliteral">""</span>);
508	<a name="l00663"></a>00663 it_assert_debug (R0.<a class="code" href="classbdm_1_1sqmat.html#73e639221343dcce76c3305524d67590" title="Reimplementing common functions of mat: rows().">rows</a>() == A0.rows(), <span class="stringliteral">""</span>);
509	<a name="l00664"></a>00664
510	<a name="l00665"></a>00665 <a class="code" href="classbdm_1_1mpdf__internal.html#47bab632af15120c88aad647ae129468" title="Internal epdf used for sampling.">iepdf</a>.<a class="code" href="classbdm_1_1enorm.html#b8322f2c11560871dd922c660f4771bb">set_parameters</a> (mu0, <a class="code" href="classbdm_1_1mlstudent.html#41595144a79594acbe288c6b59412657" title="Variable from theory.">Lambda</a>); <span class="comment">//</span>
511	<a name="l00666"></a>00666 <a class="code" href="classbdm_1_1mlnorm.html#c71bbf59fc732beb2b459d7117bd6e42" title="Internal epdf that arise by conditioning on rvc.">A</a> = A0;
512	<a name="l00667"></a>00667 <a class="code" href="classbdm_1_1mlnorm.html#831b50121cad10aa03a16682bd0c3ed6" title="Constant additive term.">mu_const</a> = mu0;
513	<a name="l00668"></a>00668 <a class="code" href="classbdm_1_1mlstudent.html#1c063ad6cb6e079ee11bc4128c2c9fe8" title="Variable .">Re</a> = R0;
514	<a name="l00669"></a>00669 <a class="code" href="classbdm_1_1mlstudent.html#41595144a79594acbe288c6b59412657" title="Variable from theory.">Lambda</a> = Lambda0;
515	<a name="l00670"></a>00670 }
516	<a name="l00671"></a><a class="code" href="classbdm_1_1mlstudent.html#efd37560585c8613897f30d3c2f58d0d">00671</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1mlstudent.html#efd37560585c8613897f30d3c2f58d0d">condition</a> (<span class="keyword">const</span> vec &cond) {
517	<a name="l00672"></a>00672 <a class="code" href="classbdm_1_1mpdf__internal.html#47bab632af15120c88aad647ae129468" title="Internal epdf used for sampling.">iepdf</a>.<a class="code" href="classbdm_1_1enorm.html#766127847e9482aea9226ea157295ea2">_mu</a>() = <a class="code" href="classbdm_1_1mlnorm.html#c71bbf59fc732beb2b459d7117bd6e42" title="Internal epdf that arise by conditioning on rvc.">A</a> * cond + <a class="code" href="classbdm_1_1mlnorm.html#831b50121cad10aa03a16682bd0c3ed6" title="Constant additive term.">mu_const</a>;
518	<a name="l00673"></a>00673 <span class="keywordtype">double</span> zeta;
519	<a name="l00674"></a>00674 <span class="comment">//ugly hack!</span>
520	<a name="l00675"></a>00675 <span class="keywordflow">if</span> ( (cond.length() + 1) == <a class="code" href="classbdm_1_1mlstudent.html#41595144a79594acbe288c6b59412657" title="Variable from theory.">Lambda</a>.<a class="code" href="classbdm_1_1sqmat.html#73e639221343dcce76c3305524d67590" title="Reimplementing common functions of mat: rows().">rows</a>()) {
521	<a name="l00676"></a>00676 zeta = <a class="code" href="classbdm_1_1mlstudent.html#41595144a79594acbe288c6b59412657" title="Variable from theory.">Lambda</a>.<a class="code" href="classbdm_1_1ldmat.html#f743de194aadb8515cf18226fadf365f" title="Evaluates quadratic form ;.">invqform</a> (concat (cond, vec_1 (1.0)));
522	<a name="l00677"></a>00677 } <span class="keywordflow">else</span> {
523	<a name="l00678"></a>00678 zeta = <a class="code" href="classbdm_1_1mlstudent.html#41595144a79594acbe288c6b59412657" title="Variable from theory.">Lambda</a>.<a class="code" href="classbdm_1_1ldmat.html#f743de194aadb8515cf18226fadf365f" title="Evaluates quadratic form ;.">invqform</a> (cond);
524	<a name="l00679"></a>00679 }
525	<a name="l00680"></a>00680 <a class="code" href="classbdm_1_1mlnorm.html#564715dea56f7bbff0083aec295ce97e" title="access function">_R</a> = <a class="code" href="classbdm_1_1mlstudent.html#1c063ad6cb6e079ee11bc4128c2c9fe8" title="Variable .">Re</a>;
526	<a name="l00681"></a>00681 <a class="code" href="classbdm_1_1mlnorm.html#564715dea56f7bbff0083aec295ce97e" title="access function">_R</a> *= (1 + zeta);<span class="comment">// / ( nu ); << nu is in Re!!!!!!</span>
527	<a name="l00682"></a>00682 };
528	<a name="l00683"></a>00683
529	<a name="l00684"></a>00684 };
530	<a name="l00694"></a><a class="code" href="classbdm_1_1mgamma.html">00694</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_1mpdf__internal.html" title="Mpdf with internal epdf that is modified by function condition.">mpdf_internal</a><egamma>
531	<a name="l00695"></a>00695 {
532	<a name="l00696"></a>00696 <span class="keyword">protected</span>:
533	<a name="l00697"></a>00697
534	<a name="l00699"></a><a class="code" href="classbdm_1_1mgamma.html#b20cf88cca1fe9b0b8f2a412608bfd09">00699</a> <span class="keywordtype">double</span> <a class="code" href="classbdm_1_1mgamma.html#b20cf88cca1fe9b0b8f2a412608bfd09" title="Constant .">k</a>;
535	<a name="l00700"></a>00700
536	<a name="l00702"></a><a class="code" href="classbdm_1_1mgamma.html#3d95f4dde9214ff6dba265e18af60312">00702</a> vec &<a class="code" href="classbdm_1_1mgamma.html#3d95f4dde9214ff6dba265e18af60312" title="cache of iepdf.beta">_beta</a>;
537	<a name="l00703"></a>00703
538	<a name="l00704"></a>00704 <span class="keyword">public</span>:
539	<a name="l00706"></a><a class="code" href="classbdm_1_1mgamma.html#1a9dc8661e5b214a8185d6e6b9956eb1">00706</a> <a class="code" href="classbdm_1_1mgamma.html#1a9dc8661e5b214a8185d6e6b9956eb1" title="Constructor.">mgamma</a>() : <a class="code" href="classbdm_1_1mpdf__internal.html" title="Mpdf with internal epdf that is modified by function condition.">mpdf_internal</a><<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),
540	<a name="l00707"></a>00707 <a class="code" href="classbdm_1_1mgamma.html#3d95f4dde9214ff6dba265e18af60312" title="cache of iepdf.beta">_beta</a> (<a class="code" href="classbdm_1_1mpdf__internal.html#47bab632af15120c88aad647ae129468" title="Internal epdf used for sampling.">iepdf</a>.<a class="code" href="classbdm_1_1mgamma.html#3d95f4dde9214ff6dba265e18af60312" title="cache of iepdf.beta">_beta</a>()) {
541	<a name="l00708"></a>00708 }
542	<a name="l00709"></a>00709
543	<a name="l00711"></a>00711 <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);
544	<a name="l00712"></a>00712
545	<a name="l00713"></a><a class="code" href="classbdm_1_1mgamma.html#8996500f1885e39cde30221b20900bff">00713</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1mgamma.html#8996500f1885e39cde30221b20900bff">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;};
546	<a name="l00723"></a><a class="code" href="classbdm_1_1mgamma.html#da2af0f327e5452bee71d1bf97452ae4">00723</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>) {
547	<a name="l00724"></a>00724 <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>
548	<a name="l00725"></a>00725 vec betatmp; <span class="comment">// ugly but necessary</span>
549	<a name="l00726"></a>00726 <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);
550	<a name="l00727"></a>00727 <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);
551	<a name="l00728"></a>00728 <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);
552	<a name="l00729"></a>00729 }
553	<a name="l00730"></a>00730 };
554	<a name="l00731"></a>00731 <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);
555	<a name="l00732"></a>00732 SHAREDPTR (mgamma);
556	<a name="l00733"></a>00733
557	<a name="l00743"></a><a class="code" href="classbdm_1_1migamma.html">00743</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_1mpdf__internal.html" title="Mpdf with internal epdf that is modified by function condition.">mpdf_internal</a><eigamma>
558	<a name="l00744"></a>00744 {
559	<a name="l00745"></a>00745 <span class="keyword">protected</span>:
560	<a name="l00747"></a><a class="code" href="classbdm_1_1migamma.html#dc56bc9da542e0103ec16b9be8e5e38c">00747</a> <span class="keywordtype">double</span> <a class="code" href="classbdm_1_1migamma.html#dc56bc9da542e0103ec16b9be8e5e38c" title="Constant .">k</a>;
561	<a name="l00748"></a>00748
562	<a name="l00750"></a><a class="code" href="classbdm_1_1migamma.html#c9847093da59a9ba0ebb68d2c592f5dc">00750</a> vec &<a class="code" href="classbdm_1_1migamma.html#c9847093da59a9ba0ebb68d2c592f5dc" title="cache of iepdf.alpha">_alpha</a>;
563	<a name="l00751"></a>00751
564	<a name="l00753"></a><a class="code" href="classbdm_1_1migamma.html#0d854c047001b5465cf1ba21f52904b5">00753</a> vec &<a class="code" href="classbdm_1_1migamma.html#0d854c047001b5465cf1ba21f52904b5" title="cache of iepdf.beta">_beta</a>;
565	<a name="l00754"></a>00754
566	<a name="l00755"></a>00755 <span class="keyword">public</span>:
567	<a name="l00758"></a>00758 <a class="code" href="classbdm_1_1migamma.html" title="Inverse-Gamma random walk.">migamma</a>() : <a class="code" href="classbdm_1_1mpdf__internal.html" title="Mpdf with internal epdf that is modified by function condition.">mpdf_internal</a><<a class="code" href="classbdm_1_1eigamma.html" title="Inverse-Gamma posterior density.">eigamma</a>>(),
568	<a name="l00759"></a>00759 <a class="code" href="classbdm_1_1migamma.html#dc56bc9da542e0103ec16b9be8e5e38c" title="Constant .">k</a> (0),
569	<a name="l00760"></a>00760 <a class="code" href="classbdm_1_1migamma.html#c9847093da59a9ba0ebb68d2c592f5dc" title="cache of iepdf.alpha">_alpha</a> (<a class="code" href="classbdm_1_1mpdf__internal.html#47bab632af15120c88aad647ae129468" title="Internal epdf used for sampling.">iepdf</a>.<a class="code" href="classbdm_1_1migamma.html#c9847093da59a9ba0ebb68d2c592f5dc" title="cache of iepdf.alpha">_alpha</a>()),
570	<a name="l00761"></a>00761 <a class="code" href="classbdm_1_1migamma.html#0d854c047001b5465cf1ba21f52904b5" title="cache of iepdf.beta">_beta</a> (<a class="code" href="classbdm_1_1mpdf__internal.html#47bab632af15120c88aad647ae129468" title="Internal epdf used for sampling.">iepdf</a>.<a class="code" href="classbdm_1_1migamma.html#0d854c047001b5465cf1ba21f52904b5" title="cache of iepdf.beta">_beta</a>()) {
571	<a name="l00762"></a>00762 }
572	<a name="l00763"></a>00763
573	<a name="l00764"></a>00764 <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_1mpdf__internal.html" title="Mpdf with internal epdf that is modified by function condition.">mpdf_internal</a><<a class="code" href="classbdm_1_1eigamma.html" title="Inverse-Gamma posterior density.">eigamma</a>>(),
574	<a name="l00765"></a>00765 <a class="code" href="classbdm_1_1migamma.html#dc56bc9da542e0103ec16b9be8e5e38c" title="Constant .">k</a> (0),
575	<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_1mpdf__internal.html#47bab632af15120c88aad647ae129468" title="Internal epdf used for sampling.">iepdf</a>.<a class="code" href="classbdm_1_1migamma.html#c9847093da59a9ba0ebb68d2c592f5dc" title="cache of iepdf.alpha">_alpha</a>()),
576	<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_1mpdf__internal.html#47bab632af15120c88aad647ae129468" title="Internal epdf used for sampling.">iepdf</a>.<a class="code" href="classbdm_1_1migamma.html#0d854c047001b5465cf1ba21f52904b5" title="cache of iepdf.beta">_beta</a>()) {
577	<a name="l00768"></a>00768 }
578	<a name="l00770"></a>00770
579	<a name="l00772"></a><a class="code" href="classbdm_1_1migamma.html#8b10ab922e2a7bae2fb6bb3efc7b6151">00772</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) {
580	<a name="l00773"></a>00773 <a class="code" href="classbdm_1_1migamma.html#dc56bc9da542e0103ec16b9be8e5e38c" title="Constant .">k</a> = k0;
581	<a name="l00774"></a>00774 <a class="code" href="classbdm_1_1mpdf__internal.html#47bab632af15120c88aad647ae129468" title="Internal epdf used for sampling.">iepdf</a>.<a class="code" href="classbdm_1_1egamma.html#749f82293ff23a8319c1bf52489d2ed2">set_parameters</a> ( (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>);
582	<a name="l00775"></a>00775 <a class="code" href="classbdm_1_1mpdf.html#7c1900976ff13dbc09c9729b3bbff9e6" title="dimension of the condition">dimc</a> = dimension();
583	<a name="l00776"></a>00776 };
584	<a name="l00777"></a><a class="code" href="classbdm_1_1migamma.html#7a34b1e2e3aa2250d7c0ed7df1665b8c">00777</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1migamma.html#7a34b1e2e3aa2250d7c0ed7df1665b8c">condition</a> (<span class="keyword">const</span> vec &val) {
585	<a name="l00778"></a>00778 <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));
586	<a name="l00779"></a>00779 };
587	<a name="l00780"></a>00780 };
588	<a name="l00781"></a>00781
589	<a name="l00782"></a>00782
590	<a name="l00794"></a><a class="code" href="classbdm_1_1mgamma__fix.html">00794</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>
591	<a name="l00795"></a>00795 {
592	<a name="l00796"></a>00796 <span class="keyword">protected</span>:
593	<a name="l00798"></a><a class="code" href="classbdm_1_1mgamma__fix.html#1eb701506aabb2e6af007e487212d6fa">00798</a> <span class="keywordtype">double</span> <a class="code" href="classbdm_1_1mgamma__fix.html#1eb701506aabb2e6af007e487212d6fa" title="parameter l">l</a>;
594	<a name="l00800"></a><a class="code" href="classbdm_1_1mgamma__fix.html#018c6f901a04e419455308a07eb3b0b2">00800</a> vec <a class="code" href="classbdm_1_1mgamma__fix.html#018c6f901a04e419455308a07eb3b0b2" title="reference vector">refl</a>;
595	<a name="l00801"></a>00801 <span class="keyword">public</span>:
596	<a name="l00803"></a><a class="code" href="classbdm_1_1mgamma__fix.html#9a31bc9b4b60188a18a2a6b588dc4b2d">00803</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> () {};
597	<a name="l00805"></a><a class="code" href="classbdm_1_1mgamma__fix.html#1bfd30e90db9dc1fbda4a9fbb0b716b2">00805</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) {
598	<a name="l00806"></a>00806 <a class="code" href="classbdm_1_1mgamma__fix.html#1bfd30e90db9dc1fbda4a9fbb0b716b2" title="Set value of k.">mgamma::set_parameters</a> (k0, ref0);
599	<a name="l00807"></a>00807 <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;
600	<a name="l00808"></a>00808 <a class="code" href="classbdm_1_1mpdf.html#7c1900976ff13dbc09c9729b3bbff9e6" title="dimension of the condition">dimc</a> = dimension();
601	<a name="l00809"></a>00809 };
602	<a name="l00810"></a>00810
603	<a name="l00811"></a><a class="code" href="classbdm_1_1mgamma__fix.html#1d539591deb7a38bb3403c2b396c8ff7">00811</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1mgamma__fix.html#1d539591deb7a38bb3403c2b396c8ff7">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;};
604	<a name="l00812"></a>00812 };
605	<a name="l00813"></a>00813
606	<a name="l00814"></a>00814
607	<a name="l00827"></a><a class="code" href="classbdm_1_1migamma__ref.html">00827</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>
608	<a name="l00828"></a>00828 {
609	<a name="l00829"></a>00829 <span class="keyword">protected</span>:
610	<a name="l00831"></a><a class="code" href="classbdm_1_1migamma__ref.html#cdc1345ba8375fbdb18a69322d2f841d">00831</a> <span class="keywordtype">double</span> <a class="code" href="classbdm_1_1migamma__ref.html#cdc1345ba8375fbdb18a69322d2f841d" title="parameter l">l</a>;
611	<a name="l00833"></a><a class="code" href="classbdm_1_1migamma__ref.html#3692dc67caf4367e15564d37f45476f6">00833</a> vec <a class="code" href="classbdm_1_1migamma__ref.html#3692dc67caf4367e15564d37f45476f6" title="reference vector">refl</a>;
612	<a name="l00834"></a>00834 <span class="keyword">public</span>:
613	<a name="l00836"></a><a class="code" href="classbdm_1_1migamma__ref.html#f45b15a10f084991ba6b48295f10421f">00836</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> () {};
614	<a name="l00838"></a><a class="code" href="classbdm_1_1migamma__ref.html#b0b4eb278ef5d0831ec4954ba7bd2800">00838</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) {
615	<a name="l00839"></a>00839 <a class="code" href="classbdm_1_1migamma__ref.html#b0b4eb278ef5d0831ec4954ba7bd2800" title="Set value of k.">migamma::set_parameters</a> (ref0.length(), k0);
616	<a name="l00840"></a>00840 <a class="code" href="classbdm_1_1migamma__ref.html#3692dc67caf4367e15564d37f45476f6" title="reference vector">refl</a> = pow (ref0, 1.0 - l0);
617	<a name="l00841"></a>00841 <a class="code" href="classbdm_1_1migamma__ref.html#cdc1345ba8375fbdb18a69322d2f841d" title="parameter l">l</a> = l0;
618	<a name="l00842"></a>00842 <a class="code" href="classbdm_1_1mpdf.html#7c1900976ff13dbc09c9729b3bbff9e6" title="dimension of the condition">dimc</a> = dimension();
619	<a name="l00843"></a>00843 };
620	<a name="l00844"></a>00844
621	<a name="l00845"></a><a class="code" href="classbdm_1_1migamma__ref.html#ae86b2e4ff963d62e05d4e130514634a">00845</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1migamma__ref.html#ae86b2e4ff963d62e05d4e130514634a">condition</a> (<span class="keyword">const</span> vec &val) {
622	<a name="l00846"></a>00846 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>));
623	<a name="l00847"></a>00847 <a class="code" href="classbdm_1_1migamma__ref.html#ae86b2e4ff963d62e05d4e130514634a">migamma::condition</a> (mean);
624	<a name="l00848"></a>00848 };
625	<a name="l00849"></a>00849
626	<a name="l00870"></a>00870 <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>);
627	<a name="l00871"></a>00871
628	<a name="l00872"></a>00872 <span class="comment">// TODO dodelat void to_setting( Setting &set ) const;</span>
629	<a name="l00873"></a>00873 };
630	<a name="l00874"></a>00874
631	<a name="l00875"></a>00875
632	<a name="l00876"></a>00876 <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);
633	<a name="l00877"></a>00877 SHAREDPTR (migamma_ref);
634	<a name="l00878"></a>00878
635	<a name="l00888"></a><a class="code" href="classbdm_1_1elognorm.html">00888</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>
636	<a name="l00889"></a>00889 {
637	<a name="l00890"></a>00890 <span class="keyword">public</span>:
638	<a name="l00891"></a><a class="code" href="classbdm_1_1elognorm.html#8b948e2bce1253765a2542199913aaba">00891</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>());};
639	<a name="l00892"></a><a class="code" href="classbdm_1_1elognorm.html#adb41e4f4d6600dec6f8c1dbc5ed9eea">00892</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);};
640	<a name="l00893"></a>00893
641	<a name="l00894"></a>00894 };
642	<a name="l00895"></a>00895
643	<a name="l00907"></a><a class="code" href="classbdm_1_1mlognorm.html">00907</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__internal.html" title="Mpdf with internal epdf that is modified by function condition.">mpdf_internal</a><elognorm>
644	<a name="l00908"></a>00908 {
645	<a name="l00909"></a>00909 <span class="keyword">protected</span>:
646	<a name="l00911"></a><a class="code" href="classbdm_1_1mlognorm.html#a51128a2e503b8b2ce698244b9e0db1a">00911</a> <span class="keywordtype">double</span> <a class="code" href="classbdm_1_1mlognorm.html#a51128a2e503b8b2ce698244b9e0db1a" title="parameter 1/2*sigma^2">sig2</a>;
647	<a name="l00912"></a>00912
648	<a name="l00914"></a><a class="code" href="classbdm_1_1mlognorm.html#7d0063f77d899ef22e8c5edd642176d2">00914</a> vec &<a class="code" href="classbdm_1_1mlognorm.html#7d0063f77d899ef22e8c5edd642176d2" title="access">mu</a>;
649	<a name="l00915"></a>00915 <span class="keyword">public</span>:
650	<a name="l00917"></a><a class="code" href="classbdm_1_1mlognorm.html#a5d6eb2688d02e0348b96c4fbd7bde41">00917</a> <a class="code" href="classbdm_1_1mlognorm.html#a5d6eb2688d02e0348b96c4fbd7bde41" title="Constructor.">mlognorm</a>() : <a class="code" href="classbdm_1_1mpdf__internal.html" title="Mpdf with internal epdf that is modified by function condition.">mpdf_internal</a><<a class="code" href="classbdm_1_1elognorm.html">elognorm</a>>(),
651	<a name="l00918"></a>00918 <a class="code" href="classbdm_1_1mlognorm.html#a51128a2e503b8b2ce698244b9e0db1a" title="parameter 1/2*sigma^2">sig2</a> (0),
652	<a name="l00919"></a>00919 <a class="code" href="classbdm_1_1mlognorm.html#7d0063f77d899ef22e8c5edd642176d2" title="access">mu</a> (<a class="code" href="classbdm_1_1mpdf__internal.html#47bab632af15120c88aad647ae129468" title="Internal epdf used for sampling.">iepdf</a>._mu()) {
653	<a name="l00920"></a>00920 }
654	<a name="l00921"></a>00921
655	<a name="l00923"></a><a class="code" href="classbdm_1_1mlognorm.html#604cab0e8a76f9041dc3c606043bb39f">00923</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) {
656	<a name="l00924"></a>00924 <a class="code" href="classbdm_1_1mlognorm.html#a51128a2e503b8b2ce698244b9e0db1a" title="parameter 1/2sigma^2">sig2</a> = 0.5 log (k * k + 1);
657	<a name="l00925"></a>00925 <a class="code" href="classbdm_1_1mpdf__internal.html#47bab632af15120c88aad647ae129468" title="Internal epdf used for sampling.">iepdf</a>.<a class="code" href="classbdm_1_1enorm.html#b8322f2c11560871dd922c660f4771bb">set_parameters</a> (zeros (size), 2<a class="code" href="classbdm_1_1mlognorm.html#a51128a2e503b8b2ce698244b9e0db1a" title="parameter 1/2sigma^2">sig2</a>*eye (size));
658	<a name="l00926"></a>00926
659	<a name="l00927"></a>00927 <a class="code" href="classbdm_1_1mpdf.html#7c1900976ff13dbc09c9729b3bbff9e6" title="dimension of the condition">dimc</a> = size;
660	<a name="l00928"></a>00928 };
661	<a name="l00929"></a>00929
662	<a name="l00930"></a><a class="code" href="classbdm_1_1mlognorm.html#9106d8fd8bdf2b6be675ffd8f3ca584e">00930</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1mlognorm.html#9106d8fd8bdf2b6be675ffd8f3ca584e">condition</a> (<span class="keyword">const</span> vec &val) {
663	<a name="l00931"></a>00931 <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>
664	<a name="l00932"></a>00932 };
665	<a name="l00933"></a>00933
666	<a name="l00952"></a>00952 <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>);
667	<a name="l00953"></a>00953
668	<a name="l00954"></a>00954 <span class="comment">// TODO dodelat void to_setting( Setting &set ) const;</span>
669	<a name="l00955"></a>00955
670	<a name="l00956"></a>00956 };
671	<a name="l00957"></a>00957
672	<a name="l00958"></a>00958 <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);
673	<a name="l00959"></a>00959 SHAREDPTR (mlognorm);
674	<a name="l00960"></a>00960
675	<a name="l00964"></a><a class="code" href="classbdm_1_1eWishartCh.html">00964</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>
676	<a name="l00965"></a>00965 {
677	<a name="l00966"></a>00966 <span class="keyword">protected</span>:
678	<a name="l00968"></a><a class="code" href="classbdm_1_1eWishartCh.html#1b42f9284a32f23b0b253a628cda7490">00968</a> <a class="code" href="classbdm_1_1chmat.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>;
679	<a name="l00970"></a><a class="code" href="classbdm_1_1eWishartCh.html#b745c73faef785009484180582050a1f">00970</a> <span class="keywordtype">int</span> <a class="code" href="classbdm_1_1eWishartCh.html#b745c73faef785009484180582050a1f" title="dimension of matrix ">p</a>;
680	<a name="l00972"></a><a class="code" href="classbdm_1_1eWishartCh.html#1879a14d7d2bb05062523b189baa11c3">00972</a> <span class="keywordtype">double</span> <a class="code" href="classbdm_1_1eWishartCh.html#1879a14d7d2bb05062523b189baa11c3" title="degrees of freedom ">delta</a>;
681	<a name="l00973"></a>00973 <span class="keyword">public</span>:
682	<a name="l00975"></a><a class="code" href="classbdm_1_1eWishartCh.html#183d961532ee97b7dc5ec81701aa59a0">00975</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1eWishartCh.html#183d961532ee97b7dc5ec81701aa59a0" title="Set internal structures.">set_parameters</a> (<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="classbdm_1_1chmat.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="classbdm_1_1sqmat.html#73e639221343dcce76c3305524d67590" 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>; }
683	<a name="l00977"></a><a class="code" href="classbdm_1_1eWishartCh.html#cc664035d70d2622bf264a29270f8339">00977</a> mat <a class="code" href="classbdm_1_1eWishartCh.html#cc664035d70d2622bf264a29270f8339" title="Sample matrix argument.">sample_mat</a>()<span class="keyword"> const </span>{
684	<a name="l00978"></a>00978 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>);
685	<a name="l00979"></a>00979
686	<a name="l00980"></a>00980 <span class="comment">//sample diagonal</span>
687	<a name="l00981"></a>00981 <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++) {
688	<a name="l00982"></a>00982 GamRNG.setup (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>
689	<a name="l00983"></a>00983 <span class="preprocessor">#pragma omp critical</span>
690	<a name="l00984"></a>00984 <span class="preprocessor"></span> X (i, i) = sqrt (GamRNG());
691	<a name="l00985"></a>00985 }
692	<a name="l00986"></a>00986 <span class="comment">//do the rest</span>
693	<a name="l00987"></a>00987 <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0;i < p;i++) {
694	<a name="l00988"></a>00988 <span class="keywordflow">for</span> (<span class="keywordtype">int</span> j = i + 1;j < p;j++) {
695	<a name="l00989"></a>00989 <span class="preprocessor">#pragma omp critical</span>
696	<a name="l00990"></a>00990 <span class="preprocessor"></span> X (i, j) = NorRNG.sample();
697	<a name="l00991"></a>00991 }
698	<a name="l00992"></a>00992 }
699	<a name="l00993"></a>00993 <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="classbdm_1_1chmat.html#17daa8c5c5914bd3194cb3053c5793a5" title="Access function.">_Ch</a>();<span class="comment">// return upper triangular part of the decomposition</span>
700	<a name="l00994"></a>00994 }
701	<a name="l00995"></a><a class="code" href="classbdm_1_1eWishartCh.html#8f2154b8b5be8f4c5788f261b6d57b9a">00995</a> vec <a class="code" href="classbdm_1_1eWishartCh.html#8f2154b8b5be8f4c5788f261b6d57b9a" title="Returns a sample, from density .">sample</a> ()<span class="keyword"> const </span>{
702	<a name="l00996"></a>00996 <span class="keywordflow">return</span> vec (<a class="code" href="classbdm_1_1eWishartCh.html#cc664035d70d2622bf264a29270f8339" title="Sample matrix argument.">sample_mat</a>()._data(), <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>);
703	<a name="l00997"></a>00997 }
704	<a name="l00999"></a><a class="code" href="classbdm_1_1eWishartCh.html#4eee757c0535c2a88bb20f0767c64981">00999</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="classbdm_1_1chmat.html#17daa8c5c5914bd3194cb3053c5793a5" title="Access function.">_Ch</a>()._data());}
705	<a name="l01001"></a><a class="code" href="classbdm_1_1eWishartCh.html#7eac414ec10b85aa5536b0092c57bc4a">01001</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="classbdm_1_1chmat.html#17daa8c5c5914bd3194cb3053c5793a5" title="Access function.">_Ch</a>()._data()); }
706	<a name="l01003"></a><a class="code" href="classbdm_1_1eWishartCh.html#1708cacb5d8cb1b96395d35f5327cb7e">01003</a> <span class="keyword">const</span> <a class="code" href="classbdm_1_1chmat.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>;}
707	<a name="l01004"></a>01004 };
708	<a name="l01005"></a>01005
709	<a name="l01007"></a>01007
710	<a name="l01009"></a><a class="code" href="classbdm_1_1eiWishartCh.html">01009</a> <span class="keyword">class </span><a class="code" href="classbdm_1_1eiWishartCh.html" title="Inverse Wishart on Choleski decomposition.">eiWishartCh</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>
711	<a name="l01010"></a>01010 {
712	<a name="l01011"></a>01011 <span class="keyword">protected</span>:
713	<a name="l01013"></a><a class="code" href="classbdm_1_1eiWishartCh.html#c6b684b52dc62b8d46e67d5992f98b9a">01013</a> <a class="code" href="classbdm_1_1eWishartCh.html">eWishartCh</a> <a class="code" href="classbdm_1_1eiWishartCh.html#c6b684b52dc62b8d46e67d5992f98b9a" title="Internal instance of Wishart density.">W</a>;
714	<a name="l01015"></a><a class="code" href="classbdm_1_1eiWishartCh.html#c11f1c41183f743b97fbb73a4e9ba6cd">01015</a> <span class="keywordtype">int</span> <a class="code" href="classbdm_1_1eiWishartCh.html#c11f1c41183f743b97fbb73a4e9ba6cd" title="size of Ch">p</a>;
715	<a name="l01017"></a><a class="code" href="classbdm_1_1eiWishartCh.html#ca3035f7bd5e4597cc1843cf07af8464">01017</a> <span class="keywordtype">double</span> <a class="code" href="classbdm_1_1eiWishartCh.html#ca3035f7bd5e4597cc1843cf07af8464" title="parameter delta">delta</a>;
716	<a name="l01018"></a>01018 <span class="keyword">public</span>:
717	<a name="l01020"></a><a class="code" href="classbdm_1_1eiWishartCh.html#f463caed9d22d9949f3ee67614e7dcd3">01020</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1eiWishartCh.html#f463caed9d22d9949f3ee67614e7dcd3" title="constructor function">set_parameters</a> (<span class="keyword">const</span> mat &Y0, <span class="keyword">const</span> <span class="keywordtype">double</span> delta0) {
718	<a name="l01021"></a>01021 <a class="code" href="classbdm_1_1eiWishartCh.html#ca3035f7bd5e4597cc1843cf07af8464" title="parameter delta">delta</a> = delta0;
719	<a name="l01022"></a>01022 <a class="code" href="classbdm_1_1eiWishartCh.html#c6b684b52dc62b8d46e67d5992f98b9a" title="Internal instance of Wishart density.">W</a>.<a class="code" href="classbdm_1_1eWishartCh.html#183d961532ee97b7dc5ec81701aa59a0" title="Set internal structures.">set_parameters</a> (inv (Y0), delta0);
720	<a name="l01023"></a>01023 <a class="code" href="classbdm_1_1epdf.html#16adac20ec7fe07e1ea0b27d917788ce" title="dimension of the random variable">dim</a> = <a class="code" href="classbdm_1_1eiWishartCh.html#c6b684b52dc62b8d46e67d5992f98b9a" title="Internal instance of Wishart density.">W</a>.<a class="code" href="classbdm_1_1epdf.html#7083a65f7b7a0d0d13b2c516bd2ec29c" title="Size of the random variable.">dimension</a>(); <a class="code" href="classbdm_1_1eiWishartCh.html#c11f1c41183f743b97fbb73a4e9ba6cd" title="size of Ch">p</a> = Y0.rows();
721	<a name="l01024"></a>01024 }
722	<a name="l01025"></a><a class="code" href="classbdm_1_1eiWishartCh.html#2f668192cc9c2e3a5b7e608164685a3e">01025</a> vec <a class="code" href="classbdm_1_1eiWishartCh.html#2f668192cc9c2e3a5b7e608164685a3e" title="Returns a sample, from density .">sample</a>()<span class="keyword"> const </span>{mat iCh; iCh = inv (<a class="code" href="classbdm_1_1eiWishartCh.html#c6b684b52dc62b8d46e67d5992f98b9a" title="Internal instance of Wishart density.">W</a>.<a class="code" href="classbdm_1_1eWishartCh.html#cc664035d70d2622bf264a29270f8339" title="Sample matrix argument.">sample_mat</a>()); <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>);}
723	<a name="l01027"></a><a class="code" href="classbdm_1_1eiWishartCh.html#d9947933dfc94546cbd6a81f95ec5af5">01027</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1eiWishartCh.html#d9947933dfc94546cbd6a81f95ec5af5" title="access function">_setY</a> (<span class="keyword">const</span> vec &y0) {
724	<a name="l01028"></a>01028 mat Ch (<a class="code" href="classbdm_1_1eiWishartCh.html#c11f1c41183f743b97fbb73a4e9ba6cd" title="size of Ch">p</a>, <a class="code" href="classbdm_1_1eiWishartCh.html#c11f1c41183f743b97fbb73a4e9ba6cd" title="size of Ch">p</a>);
725	<a name="l01029"></a>01029 mat iCh (<a class="code" href="classbdm_1_1eiWishartCh.html#c11f1c41183f743b97fbb73a4e9ba6cd" title="size of Ch">p</a>, <a class="code" href="classbdm_1_1eiWishartCh.html#c11f1c41183f743b97fbb73a4e9ba6cd" title="size of Ch">p</a>);
726	<a name="l01030"></a>01030 copy_vector (<a class="code" href="classbdm_1_1epdf.html#16adac20ec7fe07e1ea0b27d917788ce" title="dimension of the random variable">dim</a>, y0._data(), Ch._data());
727	<a name="l01031"></a>01031
728	<a name="l01032"></a>01032 iCh = inv (Ch);
729	<a name="l01033"></a>01033 <a class="code" href="classbdm_1_1eiWishartCh.html#c6b684b52dc62b8d46e67d5992f98b9a" title="Internal instance of Wishart density.">W</a>.<a class="code" href="classbdm_1_1eWishartCh.html#4eee757c0535c2a88bb20f0767c64981" title="fast access function y0 will be copied into Y.Ch.">setY</a> (iCh);
730	<a name="l01034"></a>01034 }
731	<a name="l01035"></a><a class="code" href="classbdm_1_1eiWishartCh.html#a6ddbd815b8b666dd542e97f009f89bb">01035</a> <span class="keyword">virtual</span> <span class="keywordtype">double</span> <a class="code" href="classbdm_1_1eiWishartCh.html#a6ddbd815b8b666dd542e97f009f89bb">evallog</a> (<span class="keyword">const</span> vec &val)<span class="keyword"> const </span>{
732	<a name="l01036"></a>01036 <a class="code" href="classbdm_1_1chmat.html" title="Symmetric matrix stored in square root decomposition using upper cholesky.">chmat</a> X (<a class="code" href="classbdm_1_1eiWishartCh.html#c11f1c41183f743b97fbb73a4e9ba6cd" title="size of Ch">p</a>);
733	<a name="l01037"></a>01037 <span class="keyword">const</span> <a class="code" href="classbdm_1_1chmat.html" title="Symmetric matrix stored in square root decomposition using upper cholesky.">chmat</a>& Y = <a class="code" href="classbdm_1_1eiWishartCh.html#c6b684b52dc62b8d46e67d5992f98b9a" title="Internal instance of Wishart density.">W</a>.<a class="code" href="classbdm_1_1eWishartCh.html#1708cacb5d8cb1b96395d35f5327cb7e" title="access function">getY</a>();
734	<a name="l01038"></a>01038
735	<a name="l01039"></a>01039 copy_vector (<a class="code" href="classbdm_1_1eiWishartCh.html#c11f1c41183f743b97fbb73a4e9ba6cd" title="size of Ch">p</a>*<a class="code" href="classbdm_1_1eiWishartCh.html#c11f1c41183f743b97fbb73a4e9ba6cd" title="size of Ch">p</a>, val._data(), X.<a class="code" href="classbdm_1_1chmat.html#17daa8c5c5914bd3194cb3053c5793a5" title="Access function.">_Ch</a>()._data());
736	<a name="l01040"></a>01040 <a class="code" href="classbdm_1_1chmat.html" title="Symmetric matrix stored in square root decomposition using upper cholesky.">chmat</a> iX (p);X.<a class="code" href="classbdm_1_1chmat.html#cbf3389db96dff41fb2e9532d59b13c0" title="Inversion in the same form, i.e. cholesky.">inv</a> (iX);
737	<a name="l01041"></a>01041 <span class="comment">// compute</span>
738	<a name="l01042"></a>01042 <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>
739	<a name="l01043"></a>01043 mat M = Y.<a class="code" href="classbdm_1_1chmat.html#4b4c5d4dbb8a3d585b68d936cb6df31b" title="Conversion to full matrix.">to_mat</a>() * iX.to_mat();
740	<a name="l01044"></a>01044
741	<a name="l01045"></a>01045 <span class="keywordtype">double</span> log1 = 0.5 * p * (2 * Y.<a class="code" href="classbdm_1_1chmat.html#949ccd174ed19f9cfe36366cbd5c56a4" title="Logarithm of a determinant.">logdet</a>()) - 0.5 * (<a class="code" href="classbdm_1_1eiWishartCh.html#ca3035f7bd5e4597cc1843cf07af8464" title="parameter delta">delta</a> + p + 1) * (2 * X.<a class="code" href="classbdm_1_1chmat.html#949ccd174ed19f9cfe36366cbd5c56a4" title="Logarithm of a determinant.">logdet</a>()) - 0.5 * trace (M);
742	<a name="l01046"></a>01046 <span class="comment">//Fixme! Multivariate gamma omitted!! it is ok for sampling, but not otherwise!!</span>
743	<a name="l01047"></a>01047
744	<a name="l01048"></a>01048 <span class="comment">/* if (0) {</span>
745	<a name="l01049"></a>01049 <span class="comment"> mat XX=X.to_mat();</span>
746	<a name="l01050"></a>01050 <span class="comment"> mat YY=Y.to_mat();</span>
747	<a name="l01051"></a>01051 <span class="comment"></span>
748	<a name="l01052"></a>01052 <span class="comment"> double log2 = 0.5plog(det(YY))-0.5(delta+p+1)log(det(XX))-0.5trace(YYinv(XX));</span>
749	<a name="l01053"></a>01053 <span class="comment"> cout << log1 << "," << log2 << endl;</span>
750	<a name="l01054"></a>01054 <span class="comment"> }*/</span>
751	<a name="l01055"></a>01055 <span class="keywordflow">return</span> log1;
752	<a name="l01056"></a>01056 };
753	<a name="l01057"></a>01057
754	<a name="l01058"></a>01058 };
755	<a name="l01059"></a>01059
756	<a name="l01061"></a><a class="code" href="classbdm_1_1rwiWishartCh.html">01061</a> <span class="keyword">class </span><a class="code" href="classbdm_1_1rwiWishartCh.html" title="Random Walk on inverse Wishart.">rwiWishartCh</a> : <span class="keyword">public</span> <a class="code" href="classbdm_1_1mpdf__internal.html" title="Mpdf with internal epdf that is modified by function condition.">mpdf_internal</a><eiWishartCh>
757	<a name="l01062"></a>01062 {
758	<a name="l01063"></a>01063 <span class="keyword">protected</span>:
759	<a name="l01065"></a><a class="code" href="classbdm_1_1rwiWishartCh.html#2004675b37f712abe3913057bae97cfb">01065</a> <span class="keywordtype">double</span> <a class="code" href="classbdm_1_1rwiWishartCh.html#2004675b37f712abe3913057bae97cfb" title="square root of - needed for computation of from conditions">sqd</a>;
760	<a name="l01067"></a><a class="code" href="classbdm_1_1rwiWishartCh.html#239b26c71ebcc118ba6925dfb6efc50a">01067</a> vec <a class="code" href="classbdm_1_1rwiWishartCh.html#239b26c71ebcc118ba6925dfb6efc50a" title="reference point for diagonal">refl</a>;
761	<a name="l01069"></a><a class="code" href="classbdm_1_1rwiWishartCh.html#758cd05efa67c60b4bf4f7554b9ba861">01069</a> <span class="keywordtype">double</span> <a class="code" href="classbdm_1_1rwiWishartCh.html#758cd05efa67c60b4bf4f7554b9ba861" title="power of the reference">l</a>;
762	<a name="l01071"></a><a class="code" href="classbdm_1_1rwiWishartCh.html#7ba06d431995c347d2fce30a59c20663">01071</a> <span class="keywordtype">int</span> <a class="code" href="classbdm_1_1rwiWishartCh.html#7ba06d431995c347d2fce30a59c20663" title="dimension">p</a>;
763	<a name="l01072"></a>01072
764	<a name="l01073"></a>01073 <span class="keyword">public</span>:
765	<a name="l01074"></a>01074 <a class="code" href="classbdm_1_1rwiWishartCh.html" title="Random Walk on inverse Wishart.">rwiWishartCh</a>() : <a class="code" href="classbdm_1_1rwiWishartCh.html#2004675b37f712abe3913057bae97cfb" title="square root of - needed for computation of from conditions">sqd</a> (0), <a class="code" href="classbdm_1_1rwiWishartCh.html#758cd05efa67c60b4bf4f7554b9ba861" title="power of the reference">l</a> (0), <a class="code" href="classbdm_1_1rwiWishartCh.html#7ba06d431995c347d2fce30a59c20663" title="dimension">p</a> (0) {}
766	<a name="l01076"></a><a class="code" href="classbdm_1_1rwiWishartCh.html#28549ee3ce1ff8509360171ea3cf717c">01076</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1rwiWishartCh.html#28549ee3ce1ff8509360171ea3cf717c" title="constructor function">set_parameters</a> (<span class="keywordtype">int</span> p0, <span class="keywordtype">double</span> k, vec ref0, <span class="keywordtype">double</span> l0) {
767	<a name="l01077"></a>01077 <a class="code" href="classbdm_1_1rwiWishartCh.html#7ba06d431995c347d2fce30a59c20663" title="dimension">p</a> = p0;
768	<a name="l01078"></a>01078 <span class="keywordtype">double</span> delta = 2 / (k * k) + <a class="code" href="classbdm_1_1rwiWishartCh.html#7ba06d431995c347d2fce30a59c20663" title="dimension">p</a> + 3;
769	<a name="l01079"></a>01079 <a class="code" href="classbdm_1_1rwiWishartCh.html#2004675b37f712abe3913057bae97cfb" title="square root of - needed for computation of from conditions">sqd</a> = sqrt (delta - <a class="code" href="classbdm_1_1rwiWishartCh.html#7ba06d431995c347d2fce30a59c20663" title="dimension">p</a> - 1);
770	<a name="l01080"></a>01080 <a class="code" href="classbdm_1_1rwiWishartCh.html#758cd05efa67c60b4bf4f7554b9ba861" title="power of the reference">l</a> = l0;
771	<a name="l01081"></a>01081 <a class="code" href="classbdm_1_1rwiWishartCh.html#239b26c71ebcc118ba6925dfb6efc50a" title="reference point for diagonal">refl</a> = pow (ref0, 1 - <a class="code" href="classbdm_1_1rwiWishartCh.html#758cd05efa67c60b4bf4f7554b9ba861" title="power of the reference">l</a>);
772	<a name="l01082"></a>01082
773	<a name="l01083"></a>01083 <a class="code" href="classbdm_1_1mpdf__internal.html#47bab632af15120c88aad647ae129468" title="Internal epdf used for sampling.">iepdf</a>.<a class="code" href="classbdm_1_1eiWishartCh.html#f463caed9d22d9949f3ee67614e7dcd3" title="constructor function">set_parameters</a> (eye (<a class="code" href="classbdm_1_1rwiWishartCh.html#7ba06d431995c347d2fce30a59c20663" title="dimension">p</a>), delta);
774	<a name="l01084"></a>01084 <a class="code" href="classbdm_1_1mpdf.html#7c1900976ff13dbc09c9729b3bbff9e6" title="dimension of the condition">dimc</a> = <a class="code" href="classbdm_1_1mpdf__internal.html#47bab632af15120c88aad647ae129468" title="Internal epdf used for sampling.">iepdf</a>.<a class="code" href="classbdm_1_1epdf.html#7083a65f7b7a0d0d13b2c516bd2ec29c" title="Size of the random variable.">dimension</a>();
775	<a name="l01085"></a>01085 }
776	<a name="l01086"></a><a class="code" href="classbdm_1_1rwiWishartCh.html#ac087ba6c885d3faeda9171229f9b4e6">01086</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1rwiWishartCh.html#ac087ba6c885d3faeda9171229f9b4e6">condition</a> (<span class="keyword">const</span> vec &c) {
777	<a name="l01087"></a>01087 vec z = c;
778	<a name="l01088"></a>01088 <span class="keywordtype">int</span> ri = 0;
779	<a name="l01089"></a>01089 <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0;i < <a class="code" href="classbdm_1_1rwiWishartCh.html#7ba06d431995c347d2fce30a59c20663" title="dimension">p</a>*<a class="code" href="classbdm_1_1rwiWishartCh.html#7ba06d431995c347d2fce30a59c20663" title="dimension">p</a>;i += (p + 1)) {<span class="comment">//trace diagonal element</span>
780	<a name="l01090"></a>01090 z (i) = pow (z (i), <a class="code" href="classbdm_1_1rwiWishartCh.html#758cd05efa67c60b4bf4f7554b9ba861" title="power of the reference">l</a>) * <a class="code" href="classbdm_1_1rwiWishartCh.html#239b26c71ebcc118ba6925dfb6efc50a" title="reference point for diagonal">refl</a> (ri);
781	<a name="l01091"></a>01091 ri++;
782	<a name="l01092"></a>01092 }
783	<a name="l01093"></a>01093
784	<a name="l01094"></a>01094 <a class="code" href="classbdm_1_1mpdf__internal.html#47bab632af15120c88aad647ae129468" title="Internal epdf used for sampling.">iepdf</a>.<a class="code" href="classbdm_1_1eiWishartCh.html#d9947933dfc94546cbd6a81f95ec5af5" title="access function">_setY</a> (<a class="code" href="classbdm_1_1rwiWishartCh.html#2004675b37f712abe3913057bae97cfb" title="square root of - needed for computation of from conditions">sqd</a>*z);
785	<a name="l01095"></a>01095 }
786	<a name="l01096"></a>01096 };
787	<a name="l01097"></a>01097
788	<a name="l01099"></a>01099 <span class="keyword">enum</span> RESAMPLING_METHOD { MULTINOMIAL = 0, STRATIFIED = 1, SYSTEMATIC = 3 };
789	<a name="l01105"></a><a class="code" href="classbdm_1_1eEmp.html">01105</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>
790	<a name="l01106"></a>01106 {
791	<a name="l01107"></a>01107 <span class="keyword">protected</span> :
792	<a name="l01109"></a><a class="code" href="classbdm_1_1eEmp.html#9798006271ca77629855113f1283a031">01109</a> <span class="keywordtype">int</span> <a class="code" href="classbdm_1_1eEmp.html#9798006271ca77629855113f1283a031" title="Number of particles.">n</a>;
793	<a name="l01111"></a><a class="code" href="classbdm_1_1eEmp.html#9d39241aab7c4bbeb07c6d516421c67d">01111</a> vec <a class="code" href="classbdm_1_1eEmp.html#9d39241aab7c4bbeb07c6d516421c67d" title="Sample weights .">w</a>;
794	<a name="l01113"></a><a class="code" href="classbdm_1_1eEmp.html#73d819553a0f268b055a087d2d4486f3">01113</a> Array<vec> <a class="code" href="classbdm_1_1eEmp.html#73d819553a0f268b055a087d2d4486f3" title="Samples .">samples</a>;
795	<a name="l01114"></a>01114 <span class="keyword">public</span>:
796	<a name="l01117"></a>01117 <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> () {};
797	<a name="l01119"></a><a class="code" href="classbdm_1_1eEmp.html#a3daf6363455af099921715e1233c076">01119</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>) {};
798	<a name="l01121"></a>01121
799	<a name="l01123"></a>01123 <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1eEmp.html#e7f8f98310c1de51bd5c8a1c87528f72" 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);
800	<a name="l01125"></a><a class="code" href="classbdm_1_1eEmp.html#4f7e6ba7183972e3c7ae399613861b95">01125</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1eEmp.html#4f7e6ba7183972e3c7ae399613861b95" 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#4f7e6ba7183972e3c7ae399613861b95" title="Set samples and weights.">set_statistics</a> (ones (n) / n, pdf0);};
801	<a name="l01127"></a>01127 <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);
802	<a name="l01129"></a><a class="code" href="classbdm_1_1eEmp.html#c74c281d652356c19b6b079e42ca7ef1">01129</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);};
803	<a name="l01131"></a><a class="code" href="classbdm_1_1eEmp.html#d7f83cc0415cd44ae7cc8b4bdad93aef">01131</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>;};
804	<a name="l01133"></a><a class="code" href="classbdm_1_1eEmp.html#b7d7106f486e3fad38590914a693d714">01133</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>;};
805	<a name="l01135"></a><a class="code" href="classbdm_1_1eEmp.html#c24966b0aaeb767bc8a6b4fd60931be2">01135</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>;};
806	<a name="l01137"></a><a class="code" href="classbdm_1_1eEmp.html#b59af0efdb009d98ea8ebfa965e74ae2">01137</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>;};
807	<a name="l01139"></a>01139 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);
808	<a name="l01141"></a><a class="code" href="classbdm_1_1eEmp.html#97f1e07b5ae6eebc91c7365f0f88d270">01141</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;}
809	<a name="l01143"></a><a class="code" href="classbdm_1_1eEmp.html#01654c014d3aa068f8d4ecba4be86d09">01143</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;}
810	<a name="l01144"></a><a class="code" href="classbdm_1_1eEmp.html#bbfcb4f868c7381298c281a256d8c4b9">01144</a> vec <a class="code" href="classbdm_1_1eEmp.html#bbfcb4f868c7381298c281a256d8c4b9" title="return expected value">mean</a>()<span class="keyword"> const </span>{
811	<a name="l01145"></a>01145 vec pom = zeros (<a class="code" href="classbdm_1_1epdf.html#16adac20ec7fe07e1ea0b27d917788ce" title="dimension of the random variable">dim</a>);
812	<a name="l01146"></a>01146 <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);}
813	<a name="l01147"></a>01147 <span class="keywordflow">return</span> pom;
814	<a name="l01148"></a>01148 }
815	<a name="l01149"></a><a class="code" href="classbdm_1_1eEmp.html#05e9ebf467ede737cb6a3621d7fd3c87">01149</a> vec <a class="code" href="classbdm_1_1eEmp.html#05e9ebf467ede737cb6a3621d7fd3c87" title="return expected variance (not covariance!)">variance</a>()<span class="keyword"> const </span>{
816	<a name="l01150"></a>01150 vec pom = zeros (<a class="code" href="classbdm_1_1epdf.html#16adac20ec7fe07e1ea0b27d917788ce" title="dimension of the random variable">dim</a>);
817	<a name="l01151"></a>01151 <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);}
818	<a name="l01152"></a>01152 <span class="keywordflow">return</span> pom -pow (<a class="code" href="classbdm_1_1eEmp.html#bbfcb4f868c7381298c281a256d8c4b9" title="return expected value">mean</a>(), 2);
819	<a name="l01153"></a>01153 }
820	<a name="l01155"></a><a class="code" href="classbdm_1_1eEmp.html#b1c9df656144edf79ba2d885613f661f">01155</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>{
821	<a name="l01156"></a>01156 <span class="comment">// lb in inf so than it will be pushed below;</span>
822	<a name="l01157"></a>01157 lb.set_size (<a class="code" href="classbdm_1_1epdf.html#16adac20ec7fe07e1ea0b27d917788ce" title="dimension of the random variable">dim</a>);
823	<a name="l01158"></a>01158 ub.set_size (<a class="code" href="classbdm_1_1epdf.html#16adac20ec7fe07e1ea0b27d917788ce" title="dimension of the random variable">dim</a>);
824	<a name="l01159"></a>01159 lb = std::numeric_limits<double>::infinity();
825	<a name="l01160"></a>01160 ub = -std::numeric_limits<double>::infinity();
826	<a name="l01161"></a>01161 <span class="keywordtype">int</span> j;
827	<a name="l01162"></a>01162 <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++) {
828	<a name="l01163"></a>01163 <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++) {
829	<a name="l01164"></a>01164 <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);}
830	<a name="l01165"></a>01165 <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);}
831	<a name="l01166"></a>01166 }
832	<a name="l01167"></a>01167 }
833	<a name="l01168"></a>01168 }
834	<a name="l01169"></a>01169 };
835	<a name="l01170"></a>01170
836	<a name="l01171"></a>01171
837	<a name="l01173"></a>01173
838	<a name="l01174"></a>01174 <span class="keyword">template</span><<span class="keyword">class</span> sq_T>
839	<a name="l01175"></a>01175 <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)
840	<a name="l01176"></a>01176 {
841	<a name="l01177"></a>01177 <span class="comment">//Fixme test dimensions of mu0 and R0;</span>
842	<a name="l01178"></a>01178 mu = mu0;
843	<a name="l01179"></a>01179 R = R0;
844	<a name="l01180"></a>01180 <a class="code" href="classbdm_1_1root.html#1c314bd6d6dacb8ba78ea5eb88fd9516" title="This method TODO.">validate</a>();
845	<a name="l01181"></a>01181 };
846	<a name="l01182"></a>01182
847	<a name="l01183"></a>01183 <span class="keyword">template</span><<span class="keyword">class</span> sq_T>
848	<a name="l01184"></a><a class="code" href="classbdm_1_1enorm.html#61bd470764020bea6e1ed35000f259e6">01184</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>)
849	<a name="l01185"></a>01185 {
850	<a name="l01186"></a>01186 <a class="code" href="classbdm_1_1enorm.html#61bd470764020bea6e1ed35000f259e6">epdf::from_setting</a> (<span class="keyword">set</span>); <span class="comment">//reads rv</span>
851	<a name="l01187"></a>01187
852	<a name="l01188"></a>01188 <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);
853	<a name="l01189"></a>01189 mat Rtmp;<span class="comment">// necessary for conversion</span>
854	<a name="l01190"></a>01190 <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);
855	<a name="l01191"></a>01191 <a class="code" href="classbdm_1_1enorm.html#2d92dde696b2a7a5b10ddef5d22ba2c2" title="Covariance matrix in decomposed form.">R</a> = Rtmp; <span class="comment">// conversion</span>
856	<a name="l01192"></a>01192 <a class="code" href="classbdm_1_1enorm.html#38eb17ecb75d94a50b6782fcf735cfea" title="This method TODO.">validate</a>();
857	<a name="l01193"></a>01193 }
858	<a name="l01194"></a>01194
859	<a name="l01195"></a>01195 <span class="keyword">template</span><<span class="keyword">class</span> sq_T>
860	<a name="l01196"></a><a class="code" href="classbdm_1_1enorm.html#d2e0d3a1e30ab3ab04df2d0c43ae74a2">01196</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)
861	<a name="l01197"></a>01197 {
862	<a name="l01198"></a>01198 <span class="comment">//</span>
863	<a name="l01199"></a>01199 };
864	<a name="l01200"></a>01200
865	<a name="l01201"></a>01201 <span class="comment">// template<class sq_T></span>
866	<a name="l01202"></a>01202 <span class="comment">// void enorm<sq_T>::tupdate ( double phi, mat &vbar, double nubar ) {</span>
867	<a name="l01203"></a>01203 <span class="comment">// //</span>
868	<a name="l01204"></a>01204 <span class="comment">// };</span>
869	<a name="l01205"></a>01205
870	<a name="l01206"></a>01206 <span class="keyword">template</span><<span class="keyword">class</span> sq_T>
871	<a name="l01207"></a><a class="code" href="classbdm_1_1enorm.html#e1a48f52351ec3a349bd443b713b1766">01207</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>
872	<a name="l01208"></a>01208 <span class="keyword"></span>{
873	<a name="l01209"></a>01209 vec x (<a class="code" href="classbdm_1_1epdf.html#16adac20ec7fe07e1ea0b27d917788ce" title="dimension of the random variable">dim</a>);
874	<a name="l01210"></a>01210 <span class="preprocessor">#pragma omp critical</span>
875	<a name="l01211"></a>01211 <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);
876	<a name="l01212"></a>01212 vec smp = <a class="code" href="classbdm_1_1enorm.html#2d92dde696b2a7a5b10ddef5d22ba2c2" title="Covariance matrix in decomposed form.">R</a>.sqrt_mult (x);
877	<a name="l01213"></a>01213
878	<a name="l01214"></a>01214 smp += <a class="code" href="classbdm_1_1enorm.html#c702a194720853570d08b65482f842c7" title="mean value">mu</a>;
879	<a name="l01215"></a>01215 <span class="keywordflow">return</span> smp;
880	<a name="l01216"></a>01216 };
881	<a name="l01217"></a>01217
882	<a name="l01218"></a>01218 <span class="comment">// template<class sq_T></span>
883	<a name="l01219"></a>01219 <span class="comment">// double enorm<sq_T>::eval ( const vec &val ) const {</span>
884	<a name="l01220"></a>01220 <span class="comment">// double pdfl,e;</span>
885	<a name="l01221"></a>01221 <span class="comment">// pdfl = evallog ( val );</span>
886	<a name="l01222"></a>01222 <span class="comment">// e = exp ( pdfl );</span>
887	<a name="l01223"></a>01223 <span class="comment">// return e;</span>
888	<a name="l01224"></a>01224 <span class="comment">// };</span>
889	<a name="l01225"></a>01225
890	<a name="l01226"></a>01226 <span class="keyword">template</span><<span class="keyword">class</span> sq_T>
891	<a name="l01227"></a><a class="code" href="classbdm_1_1enorm.html#e13aeed5b543b2179bacdc4fa2ae47a3">01227</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>
892	<a name="l01228"></a>01228 <span class="keyword"></span>{
893	<a name="l01229"></a>01229 <span class="comment">// 1.83787706640935 = log(2pi)</span>
894	<a name="l01230"></a>01230 <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>
895	<a name="l01231"></a>01231 <span class="keywordflow">return</span> tmp;
896	<a name="l01232"></a>01232 };
897	<a name="l01233"></a>01233
898	<a name="l01234"></a>01234 <span class="keyword">template</span><<span class="keyword">class</span> sq_T>
899	<a name="l01235"></a><a class="code" href="classbdm_1_1enorm.html#25785343aff102cc5df1cab08ba16d32">01235</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>
900	<a name="l01236"></a>01236 <span class="keyword"></span>{
901	<a name="l01237"></a>01237 <span class="comment">// 1.83787706640935 = log(2pi)</span>
902	<a name="l01238"></a>01238 <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());
903	<a name="l01239"></a>01239 <span class="keywordflow">return</span> tmp;
904	<a name="l01240"></a>01240 };
905	<a name="l01241"></a>01241
906	<a name="l01242"></a>01242
907	<a name="l01243"></a>01243 <span class="comment">// template<class sq_T></span>
908	<a name="l01244"></a>01244 <span class="comment">// vec mlnorm<sq_T>::samplecond (const vec &cond, double &lik ) {</span>
909	<a name="l01245"></a>01245 <span class="comment">// this->condition ( cond );</span>
910	<a name="l01246"></a>01246 <span class="comment">// vec smp = epdf.sample();</span>
911	<a name="l01247"></a>01247 <span class="comment">// lik = epdf.eval ( smp );</span>
912	<a name="l01248"></a>01248 <span class="comment">// return smp;</span>
913	<a name="l01249"></a>01249 <span class="comment">// }</span>
914	<a name="l01250"></a>01250
915	<a name="l01251"></a>01251 <span class="comment">// template<class sq_T></span>
916	<a name="l01252"></a>01252 <span class="comment">// mat mlnorm<sq_T>::samplecond (const vec &cond, vec &lik, int n ) {</span>
917	<a name="l01253"></a>01253 <span class="comment">// int i;</span>
918	<a name="l01254"></a>01254 <span class="comment">// int dim = rv.count();</span>
919	<a name="l01255"></a>01255 <span class="comment">// mat Smp ( dim,n );</span>
920	<a name="l01256"></a>01256 <span class="comment">// vec smp ( dim );</span>
921	<a name="l01257"></a>01257 <span class="comment">// this->condition ( cond );</span>
922	<a name="l01258"></a>01258 <span class="comment">//</span>
923	<a name="l01259"></a>01259 <span class="comment">// for ( i=0; i<n; i++ ) {</span>
924	<a name="l01260"></a>01260 <span class="comment">// smp = epdf.sample();</span>
925	<a name="l01261"></a>01261 <span class="comment">// lik ( i ) = epdf.eval ( smp );</span>
926	<a name="l01262"></a>01262 <span class="comment">// Smp.set_col ( i ,smp );</span>
927	<a name="l01263"></a>01263 <span class="comment">// }</span>
928	<a name="l01264"></a>01264 <span class="comment">//</span>
929	<a name="l01265"></a>01265 <span class="comment">// return Smp;</span>
930	<a name="l01266"></a>01266 <span class="comment">// }</span>
931	<a name="l01267"></a>01267
932	<a name="l01268"></a>01268
933	<a name="l01269"></a>01269 <span class="keyword">template</span><<span class="keyword">class</span> sq_T>
934	<a name="l01270"></a><a class="code" href="classbdm_1_1enorm.html#dcb739443669ba0a8faf634196284c08">01270</a> <a class="code" href="classbdm_1_1shared__ptr.html">shared_ptr<epdf></a> <a class="code" href="classbdm_1_1enorm.html#dcb739443669ba0a8faf634196284c08" 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>
935	<a name="l01271"></a>01271 <span class="keyword"></span>{
936	<a name="l01272"></a>01272 <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> ();
937	<a name="l01273"></a>01273 <a class="code" href="classbdm_1_1shared__ptr.html">shared_ptr<epdf></a> narrow(tmp);
938	<a name="l01274"></a>01274 <a class="code" href="classbdm_1_1enorm.html#dcb739443669ba0a8faf634196284c08" title="Return marginal density on the given RV, the remainig rvs are intergrated out.">marginal</a> ( rvn, *tmp );
939	<a name="l01275"></a>01275 <span class="keywordflow">return</span> narrow;
940	<a name="l01276"></a>01276 }
941	<a name="l01277"></a>01277
942	<a name="l01278"></a>01278 <span class="keyword">template</span><<span class="keyword">class</span> sq_T>
943	<a name="l01279"></a>01279 <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1enorm.html#dcb739443669ba0a8faf634196284c08" 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, <a class="code" href="classbdm_1_1enorm.html" title="Gaussian density with positive definite (decomposed) covariance matrix.">enorm<sq_T></a> &target )<span class="keyword"> const</span>
944	<a name="l01280"></a>01280 <span class="keyword"></span>{
945	<a name="l01281"></a>01281 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>);
946	<a name="l01282"></a>01282 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>);
947	<a name="l01283"></a>01283
948	<a name="l01284"></a>01284 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>
949	<a name="l01285"></a>01285
950	<a name="l01286"></a>01286 target.<a class="code" href="classbdm_1_1epdf.html#f423e28448dbb69ef4905295ec8de8ff" title="Name its rv.">set_rv</a> ( rvn );
951	<a name="l01287"></a>01287 target.<a class="code" href="classbdm_1_1enorm.html#b8322f2c11560871dd922c660f4771bb">set_parameters</a> (<a class="code" href="classbdm_1_1enorm.html#c702a194720853570d08b65482f842c7" title="mean value">mu</a> (irvn), Rn);
952	<a name="l01288"></a>01288 }
953	<a name="l01289"></a>01289
954	<a name="l01290"></a>01290 <span class="keyword">template</span><<span class="keyword">class</span> sq_T>
955	<a name="l01291"></a><a class="code" href="classbdm_1_1enorm.html#40201ca12c6900f7aeb493bb7c582e20">01291</a> <a class="code" href="classbdm_1_1shared__ptr.html">shared_ptr<mpdf></a> <a class="code" href="classbdm_1_1enorm.html#40201ca12c6900f7aeb493bb7c582e20" 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>
956	<a name="l01292"></a>01292 <span class="keyword"></span>{
957	<a name="l01293"></a>01293 <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> ();
958	<a name="l01294"></a>01294 <a class="code" href="classbdm_1_1shared__ptr.html">shared_ptr<mpdf></a> narrow(tmp);
959	<a name="l01295"></a>01295 <a class="code" href="classbdm_1_1enorm.html#40201ca12c6900f7aeb493bb7c582e20" title="Return conditional density on the given RV, the remaining rvs will be in conditioning...">condition</a> ( rvn, *tmp );
960	<a name="l01296"></a>01296 <span class="keywordflow">return</span> narrow;
961	<a name="l01297"></a>01297 }
962	<a name="l01298"></a>01298
963	<a name="l01299"></a>01299 <span class="keyword">template</span><<span class="keyword">class</span> sq_T>
964	<a name="l01300"></a>01300 <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1enorm.html#40201ca12c6900f7aeb493bb7c582e20" 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, <a class="code" href="classbdm_1_1mpdf.html" title="Conditional probability density, e.g. modeling , where is random variable, rv, and...">mpdf</a> &target )<span class="keyword"> const</span>
965	<a name="l01301"></a>01301 <span class="keyword"></span>{
966	<a name="l01302"></a>01302 <span class="keyword">typedef</span> <a class="code" href="classbdm_1_1mlnorm.html" title="Normal distributed linear function with linear function of mean value;.">mlnorm<sq_T></a> TMlnorm;
967	<a name="l01303"></a>01303
968	<a name="l01304"></a>01304 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>);
969	<a name="l01305"></a>01305 TMlnorm &uptarget = <span class="keyword">dynamic_cast<</span>TMlnorm &<span class="keyword">></span>(target);
970	<a name="l01306"></a>01306
971	<a name="l01307"></a>01307 <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);
972	<a name="l01308"></a>01308 it_assert_debug ( (rvc.<a class="code" href="classbdm_1_1RV.html#de30156104f61d86c94f758861418089">_dsize</a>() + rvn.<a class="code" href="classbdm_1_1RV.html#de30156104f61d86c94f758861418089">_dsize</a>() == <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#de30156104f61d86c94f758861418089">_dsize</a>()), <span class="stringliteral">"wrong rvn"</span>);
973	<a name="l01309"></a>01309 <span class="comment">//Permutation vector of the new R</span>
974	<a name="l01310"></a>01310 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>);
975	<a name="l01311"></a>01311 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>);
976	<a name="l01312"></a>01312 ivec perm = concat (irvn , irvc);
977	<a name="l01313"></a>01313 sq_T Rn (<a class="code" href="classbdm_1_1enorm.html#2d92dde696b2a7a5b10ddef5d22ba2c2" title="Covariance matrix in decomposed form.">R</a>, perm);
978	<a name="l01314"></a>01314
979	<a name="l01315"></a>01315 <span class="comment">//fixme - could this be done in general for all sq_T?</span>
980	<a name="l01316"></a>01316 mat S = Rn.to_mat();
981	<a name="l01317"></a>01317 <span class="comment">//fixme</span>
982	<a name="l01318"></a>01318 <span class="keywordtype">int</span> n = rvn.<a class="code" href="classbdm_1_1RV.html#de30156104f61d86c94f758861418089">_dsize</a>() - 1;
983	<a name="l01319"></a>01319 <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;
984	<a name="l01320"></a>01320 mat S11 = S.get (0, n, 0, n);
985	<a name="l01321"></a>01321 mat S12 = S.get (0, n , rvn.<a class="code" href="classbdm_1_1RV.html#de30156104f61d86c94f758861418089">_dsize</a>(), end);
986	<a name="l01322"></a>01322 mat S22 = S.get (rvn.<a class="code" href="classbdm_1_1RV.html#de30156104f61d86c94f758861418089">_dsize</a>(), end, rvn.<a class="code" href="classbdm_1_1RV.html#de30156104f61d86c94f758861418089">_dsize</a>(), end);
987	<a name="l01323"></a>01323
988	<a name="l01324"></a>01324 vec mu1 = <a class="code" href="classbdm_1_1enorm.html#c702a194720853570d08b65482f842c7" title="mean value">mu</a> (irvn);
989	<a name="l01325"></a>01325 vec mu2 = <a class="code" href="classbdm_1_1enorm.html#c702a194720853570d08b65482f842c7" title="mean value">mu</a> (irvc);
990	<a name="l01326"></a>01326 mat A = S12 * inv (S22);
991	<a name="l01327"></a>01327 sq_T R_n (S11 - A *S12.T());
992	<a name="l01328"></a>01328
993	<a name="l01329"></a>01329 uptarget.set_rv (rvn);
994	<a name="l01330"></a>01330 uptarget.set_rvc (rvc);
995	<a name="l01331"></a>01331 uptarget.set_parameters (A, mu1 - A*mu2, R_n);
996	<a name="l01332"></a>01332 }
997	<a name="l01333"></a>01333
998	<a name="l01336"></a>01336 <span class="keyword">template</span><<span class="keyword">class</span> sq_T>
999	<a name="l01337"></a><a class="code" href="classbdm_1_1mgnorm.html#b736332d20e418bf50d45836e129f339">01337</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1mgnorm.html#b736332d20e418bf50d45836e129f339" title="set mean function">mgnorm<sq_T >::set_parameters</a> (<span class="keyword">const</span> <a class="code" href="classbdm_1_1shared__ptr.html">shared_ptr<fnc></a> &g0, <span class="keyword">const</span> sq_T &R0) {
1000	<a name="l01338"></a>01338 g = g0;
1001	<a name="l01339"></a>01339 this-><a class="code" href="classbdm_1_1mpdf__internal.html#47bab632af15120c88aad647ae129468" title="Internal epdf used for sampling.">iepdf</a>.set_parameters (zeros (g->dimension()), R0);
1002	<a name="l01340"></a>01340 }
1003	<a name="l01341"></a>01341
1004	<a name="l01342"></a>01342 <span class="keyword">template</span><<span class="keyword">class</span> sq_T>
1005	<a name="l01343"></a><a class="code" href="classbdm_1_1mgnorm.html#b31d63472cf6a1030cd8dbd8094c1f6d">01343</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1mgnorm.html#b31d63472cf6a1030cd8dbd8094c1f6d">mgnorm<sq_T >::condition</a> (<span class="keyword">const</span> vec &cond) {this-><a class="code" href="classbdm_1_1mpdf__internal.html#47bab632af15120c88aad647ae129468" title="Internal epdf used for sampling.">iepdf</a>._mu() = g->eval (cond);};
1006	<a name="l01344"></a>01344
1007	<a name="l01346"></a>01346 <span class="keyword">template</span><<span class="keyword">class</span> sq_T>
1008	<a name="l01347"></a>01347 std::ostream &operator<< (std::ostream &os, mlnorm<sq_T> &ml)
1009	<a name="l01348"></a>01348 {
1010	<a name="l01349"></a>01349 os << <span class="stringliteral">"A:"</span> << ml.A << endl;
1011	<a name="l01350"></a>01350 os << <span class="stringliteral">"mu:"</span> << ml.mu_const << endl;
1012	<a name="l01351"></a>01351 os << <span class="stringliteral">"R:"</span> << ml._R() << endl;
1013	<a name="l01352"></a>01352 <span class="keywordflow">return</span> os;
1014	<a name="l01353"></a>01353 };
1015	<a name="l01354"></a>01354
1016	<a name="l01355"></a>01355 }
1017	<a name="l01356"></a>01356 <span class="preprocessor">#endif //EF_H</span>
1018	</pre></div></div>
1019	<hr size="1"><address style="text-align: right;"><small>Generated on Sun Aug 16 17:58:18 2009 for mixpp by
1020	<a href="http://www.doxygen.org/index.html">
1021	<img src="doxygen.png" alt="doxygen" align="middle" border="0"></a> 1.5.8 </small></address>
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