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r401	r538
52	52	<li><a href="main.html"><span>Main Page</span></a></li>
53	53	<li><a href="pages.html"><span>Related Pages</span></a></li>
54		~~<li><a href="modules.html"><span>Modules</span></a></li>~~
55	54	<li><a href="annotated.html"><span>Classes</span></a></li>
56	55	<li class="current"><a href="files.html"><span>Files</span></a></li>
…	…
68	67	<a name="l00015"></a>00015 <span class="preprocessor"></span>
69	68	<a name="l00016"></a>00016
70		<a name="l00017"></a>00017 <span class="preprocessor">#include "../~~base/bdmbase~~.h"</span>
71		<a name="l00018"></a>00018 <span class="preprocessor">#include "../~~math/chmat~~.h"</span>
72		<a name="l00019"></a>00019
73		<a name="l00020"></a>00020 ~~<span class="keyword">namespace </span>bdm~~
74		<a name="l00021"></a>00021 {
75		<a name="l00022"></a>00022
	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 {
76	75	<a name="l00023"></a>00023
77		<a name="l00025"></a>00025 <span class="keyword">extern</span> Uniform_RNG UniRNG;
78		<a name="l00027"></a>00027 <span class="keyword">extern</span> Normal_RNG NorRNG;
79		<a name="l00029"></a>00029 <span class="keyword">extern</span> Gamma_RNG GamRNG;
80		<a name="l00030"></a>00030
81		<a name="l00037"></a><a class="code" href="classbdm_1_1eEF.html">00037</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="l00038"></a>00038 {
83		<a name="l00039"></a>00039 <span class="keyword">public</span>:
84		<a name="l00040"></a>00040 <span class="comment">// eEF() :epdf() {};</span>
85		<a name="l00042"></a><a class="code" href="classbdm_1_1eEF.html#d5459d472d0feca7cf1fb5f65c4b9ef4">00042</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="l00044"></a>00044 <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="l00046"></a><a class="code" href="classbdm_1_1eEF.html#deef7d6273ba4d5a5cf0bbd91ec7277a">00046</a> <span class="keyword">virtual</span> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1eEF.html#deef7d6273ba4d5a5cf0bbd91ec7277a" title="TODO decide if it is really needed.">dupdate</a> ( mat &v ) {it_error ( <span class="stringliteral">"Not implemented"</span> );};
88		<a name="l00048"></a><a class="code" href="classbdm_1_1eEF.html#a4135778ecd9ab774762936c82a097c6">00048</a> <span class="keyword">virtual</span> <span class="keywordtype">double</span> <a class="code" href="classbdm_1_1eEF.html#a4135778ecd9ab774762936c82a097c6" title="Evaluate normalized log-probability.">evallog_nn</a> ( <span class="keyword">const</span> vec &val )<span class="keyword"> const</span>{it_error ( <span class="stringliteral">"Not implemented"</span> );<span class="keywordflow">return</span> 0.0;};
89		<a name="l00050"></a><a class="code" href="classbdm_1_1eEF.html#a36d06ecdd6f4c79dc122510eaccc692">00050</a> <span class="keyword">virtual</span> <span class="keywordtype">double</span> <a class="code" href="classbdm_1_1eEF.html#a36d06ecdd6f4c79dc122510eaccc692" title="Evaluate normalized log-probability.">evallog</a> ( <span class="keyword">const</span> vec &val )<span class="keyword"> const </span>{
90		<a name="l00051"></a>00051 <span class="keywordtype">double</span> tmp;
91		<a name="l00052"></a>00052 tmp= <a class="code" href="classbdm_1_1eEF.html#a4135778ecd9ab774762936c82a097c6" title="Evaluate normalized log-probability.">evallog_nn</a> ( val )-<a class="code" href="classbdm_1_1eEF.html#cd678fc9b02007a4b8d6692e746f1bf8" title="logarithm of the normalizing constant, ">lognc</a>();
92		<a name="l00053"></a>00053 it_assert_debug ( std::isfinite ( tmp ),<span class="stringliteral">"Infinite value"</span> );
93		<a name="l00054"></a>00054 <span class="keywordflow">return</span> tmp;}
94		<a name="l00056"></a><a class="code" href="classbdm_1_1eEF.html#79a7c8ea8c02e45d410bd1d7ffd72b41">00056</a> <span class="keyword">virtual</span> vec <a class="code" href="classbdm_1_1eEF.html#a36d06ecdd6f4c79dc122510eaccc692" title="Evaluate normalized log-probability.">evallog</a> ( <span class="keyword">const</span> mat &Val )<span class="keyword"> const</span>
95		<a name="l00057"></a>00057 <span class="keyword"> </span>{
96		<a name="l00058"></a>00058 vec x ( Val.cols() );
97		<a name="l00059"></a>00059 <span class="keywordflow">for</span> ( <span class="keywordtype">int</span> i=0;i<Val.cols();i++ ) {x ( i ) =<a class="code" href="classbdm_1_1eEF.html#a4135778ecd9ab774762936c82a097c6" title="Evaluate normalized log-probability.">evallog_nn</a> ( Val.get_col ( i ) ) ;}
98		<a name="l00060"></a>00060 <span class="keywordflow">return</span> x-<a class="code" href="classbdm_1_1eEF.html#cd678fc9b02007a4b8d6692e746f1bf8" title="logarithm of the normalizing constant, ">lognc</a>();
99		<a name="l00061"></a>00061 }
100		<a name="l00063"></a><a class="code" href="classbdm_1_1eEF.html#cf38af29e8e3d650c640509a52396053">00063</a> <span class="keyword">virtual</span> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1eEF.html#cf38af29e8e3d650c640509a52396053" title="Power of the density, used e.g. to flatten the density.">pow</a> ( <span class="keywordtype">double</span> p ) {it_error ( <span class="stringliteral">"Not implemented"</span> );};
101		<a name="l00064"></a>00064 };
102		<a name="l00065"></a>00065
103		<a name="l00072"></a><a class="code" href="classbdm_1_1mEF.html">00072</a> <span class="keyword">class </span><a class="code" href="classbdm_1_1mEF.html" title="Exponential family model.">mEF</a> : <span class="keyword">public</span> <a class="code" href="classbdm_1_1mpdf.html" title="Conditional probability density, e.g. modeling some dependencies.">mpdf</a>
104		<a name="l00073"></a>00073 {
105		<a name="l00074"></a>00074
106		<a name="l00075"></a>00075 <span class="keyword">public</span>:
107		<a name="l00077"></a><a class="code" href="classbdm_1_1mEF.html#dd7caad7026b778af66e34480eec6f9e">00077</a> <a class="code" href="classbdm_1_1mEF.html#dd7caad7026b778af66e34480eec6f9e" title="Default constructor.">mEF</a> ( ) :<a class="code" href="classbdm_1_1mpdf.html" title="Conditional probability density, e.g. modeling some dependencies.">mpdf</a> ( ) {};
108		<a name="l00078"></a>00078 };
109		<a name="l00079"></a>00079
110		<a name="l00081"></a><a class="code" href="classbdm_1_1BMEF.html">00081</a> <span class="keyword">class </span><a class="code" href="classbdm_1_1BMEF.html" title="Estimator for Exponential family.">BMEF</a> : <span class="keyword">public</span> <a class="code" href="classbdm_1_1BM.html" title="Bayesian Model of a system, i.e. all uncertainty is modeled by probabilities.">BM</a>
111		<a name="l00082"></a>00082 {
112		<a name="l00083"></a>00083 <span class="keyword">protected</span>:
113		<a name="l00085"></a><a class="code" href="classbdm_1_1BMEF.html#1331865e10fb1ccef65bb4c47fa3be64">00085</a> <span class="keywordtype">double</span> <a class="code" href="classbdm_1_1BMEF.html#1331865e10fb1ccef65bb4c47fa3be64" title="forgetting factor">frg</a>;
114		<a name="l00087"></a><a class="code" href="classbdm_1_1BMEF.html#06e7b3ac03e10017d4288c76888e2865">00087</a> <span class="keywordtype">double</span> <a class="code" href="classbdm_1_1BMEF.html#06e7b3ac03e10017d4288c76888e2865" title="cached value of lognc() in the previous step (used in evaluation of ll )">last_lognc</a>;
115		<a name="l00088"></a>00088 <span class="keyword">public</span>:
116		<a name="l00090"></a><a class="code" href="classbdm_1_1BMEF.html#2def512872ed8a4fc3b702371ec0be55">00090</a> <a class="code" href="classbdm_1_1BMEF.html#2def512872ed8a4fc3b702371ec0be55" title="Default constructor (=empty constructor).">BMEF</a> ( <span class="keywordtype">double</span> frg0=1.0 ) :<a class="code" href="classbdm_1_1BM.html" title="Bayesian Model of a system, i.e. all uncertainty is modeled by probabilities.">BM</a> ( ), <a class="code" href="classbdm_1_1BMEF.html#1331865e10fb1ccef65bb4c47fa3be64" title="forgetting factor">frg</a> ( frg0 ) {}
117		<a name="l00092"></a><a class="code" href="classbdm_1_1BMEF.html#9662379513101405e159e76717104e62">00092</a> <a class="code" href="classbdm_1_1BMEF.html#9662379513101405e159e76717104e62" title="Copy constructor.">BMEF</a> ( <span class="keyword">const</span> <a class="code" href="classbdm_1_1BMEF.html" title="Estimator for Exponential family.">BMEF</a> &B ) :<a class="code" href="classbdm_1_1BM.html" title="Bayesian Model of a system, i.e. all uncertainty is modeled by probabilities.">BM</a> ( B ), <a class="code" href="classbdm_1_1BMEF.html#1331865e10fb1ccef65bb4c47fa3be64" title="forgetting factor">frg</a> ( B.<a class="code" href="classbdm_1_1BMEF.html#1331865e10fb1ccef65bb4c47fa3be64" title="forgetting factor">frg</a> ), <a class="code" href="classbdm_1_1BMEF.html#06e7b3ac03e10017d4288c76888e2865" title="cached value of lognc() in the previous step (used in evaluation of ll )">last_lognc</a> ( B.<a class="code" href="classbdm_1_1BMEF.html#06e7b3ac03e10017d4288c76888e2865" title="cached value of lognc() in the previous step (used in evaluation of ll )">last_lognc</a> ) {}
118		<a name="l00094"></a><a class="code" href="classbdm_1_1BMEF.html#d2b528b7a41ca67163152142f5404051">00094</a> <span class="keyword">virtual</span> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1BMEF.html#d2b528b7a41ca67163152142f5404051" title="get statistics from another model">set_statistics</a> ( <span class="keyword">const</span> <a class="code" href="classbdm_1_1BMEF.html" title="Estimator for Exponential family.">BMEF</a>* BM0 ) {it_error ( <span class="stringliteral">"Not implemented"</span> );};
119		<a name="l00096"></a><a class="code" href="classbdm_1_1BMEF.html#bf58deb99af2a6cc674f13ff90300de6">00096</a> <span class="keyword">virtual</span> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1BMEF.html#bf58deb99af2a6cc674f13ff90300de6" title="Weighted update of sufficient statistics (Bayes rule).">bayes</a> ( <span class="keyword">const</span> vec &data, <span class="keyword">const</span> <span class="keywordtype">double</span> w ) {};
120		<a name="l00097"></a>00097 <span class="comment">//original Bayes</span>
121		<a name="l00098"></a>00098 <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1BMEF.html#bf58deb99af2a6cc674f13ff90300de6" title="Weighted update of sufficient statistics (Bayes rule).">bayes</a> ( <span class="keyword">const</span> vec &dt );
122		<a name="l00100"></a><a class="code" href="classbdm_1_1BMEF.html#b2916a2e71a958665054473124d5e749">00100</a> <span class="keyword">virtual</span> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1BMEF.html#b2916a2e71a958665054473124d5e749" title="Flatten the posterior according to the given BMEF (of the same type!).">flatten</a> ( <span class="keyword">const</span> <a class="code" href="classbdm_1_1BMEF.html" title="Estimator for Exponential family.">BMEF</a> * B ) {it_error ( <span class="stringliteral">"Not implemented"</span> );}
123		<a name="l00102"></a>00102 <span class="comment">// virtual void flatten ( double nu0 ) {it_error ( "Not implemented" );}</span>
124		<a name="l00103"></a>00103
125		<a name="l00104"></a><a class="code" href="classbdm_1_1BMEF.html#62d2e4691bed41a1efa6b9c2e35e5c67">00104</a> <a class="code" href="classbdm_1_1BMEF.html" title="Estimator for Exponential family.">BMEF</a>* <a class="code" href="classbdm_1_1BMEF.html#62d2e4691bed41a1efa6b9c2e35e5c67" title="Flatten the posterior as if to keep nu0 data.">_copy_</a> ()<span class="keyword"> const </span>{it_error ( <span class="stringliteral">"function _copy_ not implemented for this BM"</span> ); <span class="keywordflow">return</span> NULL;};
126		<a name="l00105"></a>00105 };
127		<a name="l00106"></a>00106
128		<a name="l00107"></a>00107 <span class="keyword">template</span><<span class="keyword">class</span> sq_T>
129		<a name="l00108"></a>00108 <span class="keyword">class </span>mlnorm;
130		<a name="l00109"></a>00109
131		<a name="l00115"></a>00115 <span class="keyword">template</span><<span class="keyword">class</span> sq_T>
132		<a name="l00116"></a><a class="code" href="classbdm_1_1enorm.html">00116</a> <span class="keyword">class </span><a class="code" href="classbdm_1_1enorm.html" title="Gaussian density with positive definite (decomposed) covariance matrix.">enorm</a> : <span class="keyword">public</span> <a class="code" href="classbdm_1_1eEF.html" title="General conjugate exponential family posterior density.">eEF</a>
133		<a name="l00117"></a>00117 {
134		<a name="l00118"></a>00118 <span class="keyword">protected</span>:
135		<a name="l00120"></a><a class="code" href="classbdm_1_1enorm.html#c702a194720853570d08b65482f842c7">00120</a> vec <a class="code" href="classbdm_1_1enorm.html#c702a194720853570d08b65482f842c7" title="mean value">mu</a>;
136		<a name="l00122"></a><a class="code" href="classbdm_1_1enorm.html#2d92dde696b2a7a5b10ddef5d22ba2c2">00122</a> sq_T <a class="code" href="classbdm_1_1enorm.html#2d92dde696b2a7a5b10ddef5d22ba2c2" title="Covariance matrix in decomposed form.">R</a>;
137		<a name="l00123"></a>00123 <span class="keyword">public</span>:
138		<a name="l00126"></a>00126
139		<a name="l00127"></a>00127 <a class="code" href="classbdm_1_1enorm.html" title="Gaussian density with positive definite (decomposed) covariance matrix.">enorm</a> ( ) :<a class="code" href="classbdm_1_1eEF.html" title="General conjugate exponential family posterior density.">eEF</a> ( ), <a class="code" href="classbdm_1_1enorm.html#c702a194720853570d08b65482f842c7" title="mean value">mu</a> ( ),<a class="code" href="classbdm_1_1enorm.html#2d92dde696b2a7a5b10ddef5d22ba2c2" title="Covariance matrix in decomposed form.">R</a> ( ) {};
140		<a name="l00128"></a>00128 <a class="code" href="classbdm_1_1enorm.html" title="Gaussian density with positive definite (decomposed) covariance matrix.">enorm</a> ( <span class="keyword">const</span> vec &<a class="code" href="classbdm_1_1enorm.html#c702a194720853570d08b65482f842c7" title="mean value">mu</a>,<span class="keyword">const</span> sq_T &<a class="code" href="classbdm_1_1enorm.html#2d92dde696b2a7a5b10ddef5d22ba2c2" title="Covariance matrix in decomposed form.">R</a> ) {set_parameters ( mu,R );}
141		<a name="l00129"></a>00129 <span class="keywordtype">void</span> set_parameters ( <span class="keyword">const</span> vec &<a class="code" href="classbdm_1_1enorm.html#c702a194720853570d08b65482f842c7" title="mean value">mu</a>,<span class="keyword">const</span> sq_T &<a class="code" href="classbdm_1_1enorm.html#2d92dde696b2a7a5b10ddef5d22ba2c2" title="Covariance matrix in decomposed form.">R</a> );
142		<a name="l00130"></a>00130 <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1enorm.html#61bd470764020bea6e1ed35000f259e6">from_setting</a>(<span class="keyword">const</span> Setting &root);
143		<a name="l00131"></a><a class="code" href="classbdm_1_1enorm.html#38eb17ecb75d94a50b6782fcf735cfea">00131</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1enorm.html#38eb17ecb75d94a50b6782fcf735cfea" title="This method TODO.">validate</a>() {
144		<a name="l00132"></a>00132 it_assert(<a class="code" href="classbdm_1_1enorm.html#c702a194720853570d08b65482f842c7" title="mean value">mu</a>.length()==<a class="code" href="classbdm_1_1enorm.html#2d92dde696b2a7a5b10ddef5d22ba2c2" title="Covariance matrix in decomposed form.">R</a>.rows(),<span class="stringliteral">"parameters mismatch"</span>);
145		<a name="l00133"></a>00133 <a class="code" href="classbdm_1_1epdf.html#16adac20ec7fe07e1ea0b27d917788ce" title="dimension of the random variable">dim</a> = <a class="code" href="classbdm_1_1enorm.html#c702a194720853570d08b65482f842c7" title="mean value">mu</a>.length();
146		<a name="l00134"></a>00134 }
	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>;
147	150	<a name="l00136"></a>00136
148		<a name="l00139"></a>00139
149		<a name="l00141"></a>00141 <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1enorm.html#d2e0d3a1e30ab3ab04df2d0c43ae74a2" title="dupdate in exponential form (not really handy)">dupdate</a> ( mat &v,<span class="keywordtype">double</span> nu=1.0 );
150		<a name="l00142"></a>00142
151		<a name="l00143"></a>00143 vec <a class="code" href="classbdm_1_1enorm.html#e1a48f52351ec3a349bd443b713b1766" title="Returns a sample, from density .">sample</a>() <span class="keyword">const</span>;
152		<a name="l00144"></a>00144 mat <a class="code" href="classbdm_1_1enorm.html#e1a48f52351ec3a349bd443b713b1766" title="Returns a sample, from density .">sample</a> ( <span class="keywordtype">int</span> N ) <span class="keyword">const</span>;
153		<a name="l00145"></a>00145 <span class="keywordtype">double</span> <a class="code" href="classbdm_1_1enorm.html#e13aeed5b543b2179bacdc4fa2ae47a3" title="Evaluate normalized log-probability.">evallog_nn</a> ( <span class="keyword">const</span> vec &val ) <span class="keyword">const</span>;
154		<a name="l00146"></a>00146 <span class="keywordtype">double</span> <a class="code" href="classbdm_1_1enorm.html#25785343aff102cc5df1cab08ba16d32" title="logarithm of the normalizing constant, ">lognc</a> () <span class="keyword">const</span>;
155		<a name="l00147"></a><a class="code" href="classbdm_1_1enorm.html#b2fa2915c35366392fe9bb022ca1a600">00147</a> vec <a class="code" href="classbdm_1_1enorm.html#b2fa2915c35366392fe9bb022ca1a600" title="return expected value">mean</a>()<span class="keyword"> const </span>{<span class="keywordflow">return</span> <a class="code" href="classbdm_1_1enorm.html#c702a194720853570d08b65482f842c7" title="mean value">mu</a>;}
156		<a name="l00148"></a><a class="code" href="classbdm_1_1enorm.html#729c75ef0fa8abae03d58ad1f81e6773">00148</a> vec <a class="code" href="classbdm_1_1enorm.html#729c75ef0fa8abae03d58ad1f81e6773" title="return expected variance (not covariance!)">variance</a>()<span class="keyword"> const </span>{<span class="keywordflow">return</span> diag ( <a class="code" href="classbdm_1_1enorm.html#2d92dde696b2a7a5b10ddef5d22ba2c2" title="Covariance matrix in decomposed form.">R</a>.to_mat() );}
157		<a name="l00149"></a>00149 <span class="comment">// mlnorm<sq_T>* condition ( const RV &rvn ) const ; <=========== fails to cmpile. Why?</span>
158		<a name="l00150"></a>00150 <a class="code" href="classbdm_1_1mpdf.html" title="Conditional probability density, e.g. modeling some dependencies.">mpdf</a>* <a class="code" href="classbdm_1_1enorm.html#baea4d49c657342b58297d68cda16d26" title="Return conditional density on the given RV, the remaining rvs will be in conditioning...">condition</a> ( <span class="keyword">const</span> <a class="code" href="classbdm_1_1RV.html" title="Class representing variables, most often random variables.">RV</a> &rvn ) <span class="keyword">const</span> ;
159		<a name="l00151"></a>00151 <a class="code" href="classbdm_1_1enorm.html" title="Gaussian density with positive definite (decomposed) covariance matrix.">enorm<sq_T></a>* <a class="code" href="classbdm_1_1enorm.html#c2996bdaffad38fbe0fc776db54c9d80" title="Return marginal density on the given RV, the remainig rvs are intergrated out.">marginal</a> ( <span class="keyword">const</span> <a class="code" href="classbdm_1_1RV.html" title="Class representing variables, most often random variables.">RV</a> &<a class="code" href="classbdm_1_1epdf.html#62c5b8ff71d9ebe6cd58d3c342eb1dc8" title="Description of the random variable.">rv</a> ) <span class="keyword">const</span>;
160		<a name="l00152"></a>00152 <span class="comment">// epdf* marginal ( const RV &rv ) const;</span>
161		<a name="l00154"></a>00154 <span class="comment"></span>
162		<a name="l00157"></a>00157
163		<a name="l00158"></a>00158 vec& _mu() {<span class="keywordflow">return</span> <a class="code" href="classbdm_1_1enorm.html#c702a194720853570d08b65482f842c7" title="mean value">mu</a>;}
164		<a name="l00159"></a>00159 <span class="keywordtype">void</span> set_mu ( <span class="keyword">const</span> vec mu0 ) { <a class="code" href="classbdm_1_1enorm.html#c702a194720853570d08b65482f842c7" title="mean value">mu</a>=mu0;}
165		<a name="l00160"></a>00160 sq_T& _R() {<span class="keywordflow">return</span> <a class="code" href="classbdm_1_1enorm.html#2d92dde696b2a7a5b10ddef5d22ba2c2" title="Covariance matrix in decomposed form.">R</a>;}
166		<a name="l00161"></a>00161 <span class="keyword">const</span> sq_T& _R()<span class="keyword"> const </span>{<span class="keywordflow">return</span> <a class="code" href="classbdm_1_1enorm.html#2d92dde696b2a7a5b10ddef5d22ba2c2" title="Covariance matrix in decomposed form.">R</a>;}
167		<a name="l00163"></a>00163
168		<a name="l00164"></a>00164 };
169		<a name="l00165"></a>00165 <a class="code" href="user__info_8h.html#4f9de2f17e844047726487b99def99c6" title="Macro for registration of class into map of user-infos, registered class is scriptable...">UIREGISTER</a>(enorm<chmat>);
170		<a name="l00166"></a>00166 <a class="code" href="user__info_8h.html#4f9de2f17e844047726487b99def99c6" title="Macro for registration of class into map of user-infos, registered class is scriptable...">UIREGISTER</a>(enorm<ldmat>);
171		<a name="l00167"></a>00167 <a class="code" href="user__info_8h.html#4f9de2f17e844047726487b99def99c6" title="Macro for registration of class into map of user-infos, registered class is scriptable...">UIREGISTER</a>(enorm<fsqmat>);
172		<a name="l00168"></a>00168
173		<a name="l00169"></a>00169
174		<a name="l00176"></a><a class="code" href="classbdm_1_1egiw.html">00176</a> <span class="keyword">class </span><a class="code" href="classbdm_1_1egiw.html" title="Gauss-inverse-Wishart density stored in LD form.">egiw</a> : <span class="keyword">public</span> <a class="code" href="classbdm_1_1eEF.html" title="General conjugate exponential family posterior density.">eEF</a>
175		<a name="l00177"></a>00177 {
176		<a name="l00178"></a>00178 <span class="keyword">protected</span>:
177		<a name="l00180"></a><a class="code" href="classbdm_1_1egiw.html#ae56852845c6af176fd9017dbebbbd52">00180</a> <a class="code" href="classldmat.html" title="Matrix stored in LD form, (commonly known as UD).">ldmat</a> <a class="code" href="classbdm_1_1egiw.html#ae56852845c6af176fd9017dbebbbd52" title="Extended information matrix of sufficient statistics.">V</a>;
178		<a name="l00182"></a><a class="code" href="classbdm_1_1egiw.html#447eacf19d4f4083872686f044814dc4">00182</a> <span class="keywordtype">double</span> <a class="code" href="classbdm_1_1egiw.html#447eacf19d4f4083872686f044814dc4" title="Number of data records (degrees of freedom) of sufficient statistics.">nu</a>;
179		<a name="l00184"></a><a class="code" href="classbdm_1_1egiw.html#23e4d78bea7e98840f3da30e76a2b57a">00184</a> <span class="keywordtype">int</span> <a class="code" href="classbdm_1_1egiw.html#23e4d78bea7e98840f3da30e76a2b57a" title="Dimension of the output.">dimx</a>;
180		<a name="l00186"></a><a class="code" href="classbdm_1_1egiw.html#322414c32d9a21a006a5aab0311f64fd">00186</a> <span class="keywordtype">int</span> <a class="code" href="classbdm_1_1egiw.html#322414c32d9a21a006a5aab0311f64fd" title="Dimension of the regressor.">nPsi</a>;
181		<a name="l00187"></a>00187 <span class="keyword">public</span>:
182		<a name="l00190"></a>00190 <a class="code" href="classbdm_1_1egiw.html" title="Gauss-inverse-Wishart density stored in LD form.">egiw</a>() :<a class="code" href="classbdm_1_1eEF.html" title="General conjugate exponential family posterior density.">eEF</a>() {};
183		<a name="l00191"></a>00191 <a class="code" href="classbdm_1_1egiw.html" title="Gauss-inverse-Wishart density stored in LD form.">egiw</a> ( <span class="keywordtype">int</span> dimx0, <a class="code" href="classldmat.html" title="Matrix stored in LD form, (commonly known as UD).">ldmat</a> V0, <span class="keywordtype">double</span> nu0=-1.0 ) :<a class="code" href="classbdm_1_1eEF.html" title="General conjugate exponential family posterior density.">eEF</a>() {set_parameters ( dimx0,V0, nu0 );};
184		<a name="l00192"></a>00192
185		<a name="l00193"></a>00193 <span class="keywordtype">void</span> set_parameters ( <span class="keywordtype">int</span> dimx0, <a class="code" href="classldmat.html" title="Matrix stored in LD form, (commonly known as UD).">ldmat</a> V0, <span class="keywordtype">double</span> nu0=-1.0 )
186		<a name="l00194"></a>00194 {
187		<a name="l00195"></a>00195 <a class="code" href="classbdm_1_1egiw.html#23e4d78bea7e98840f3da30e76a2b57a" title="Dimension of the output.">dimx</a>=dimx0;
188		<a name="l00196"></a>00196 <a class="code" href="classbdm_1_1egiw.html#322414c32d9a21a006a5aab0311f64fd" title="Dimension of the regressor.">nPsi</a> = V0.<a class="code" href="group__math.html#g96dfb21865db4f5bd36fa70f9b0b1163" title="access function">rows</a>()-<a class="code" href="classbdm_1_1egiw.html#23e4d78bea7e98840f3da30e76a2b57a" title="Dimension of the output.">dimx</a>;
189		<a name="l00197"></a>00197 <a class="code" href="classbdm_1_1epdf.html#16adac20ec7fe07e1ea0b27d917788ce" title="dimension of the random variable">dim</a> = <a class="code" href="classbdm_1_1egiw.html#23e4d78bea7e98840f3da30e76a2b57a" title="Dimension of the output.">dimx</a>* ( <a class="code" href="classbdm_1_1egiw.html#23e4d78bea7e98840f3da30e76a2b57a" title="Dimension of the output.">dimx</a>+<a class="code" href="classbdm_1_1egiw.html#322414c32d9a21a006a5aab0311f64fd" title="Dimension of the regressor.">nPsi</a> ); <span class="comment">// size(R) + size(Theta)</span>
190		<a name="l00198"></a>00198
191		<a name="l00199"></a>00199 <a class="code" href="classbdm_1_1egiw.html#ae56852845c6af176fd9017dbebbbd52" title="Extended information matrix of sufficient statistics.">V</a>=V0;
192		<a name="l00200"></a>00200 <span class="keywordflow">if</span> ( nu0<0 )
193		<a name="l00201"></a>00201 {
194		<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>
195		<a name="l00203"></a>00203 <span class="comment">// terms before that are sufficient for finite normalization</span>
196		<a name="l00204"></a>00204 }
197		<a name="l00205"></a>00205 <span class="keywordflow">else</span>
198		<a name="l00206"></a>00206 {
199		<a name="l00207"></a>00207 <a class="code" href="classbdm_1_1egiw.html#447eacf19d4f4083872686f044814dc4" title="Number of data records (degrees of freedom) of sufficient statistics.">nu</a>=nu0;
200		<a name="l00208"></a>00208 }
201		<a name="l00209"></a>00209 }
202		<a name="l00211"></a>00211
203		<a name="l00212"></a>00212 vec <a class="code" href="classbdm_1_1egiw.html#920f21548b7a3723923dd108fe514c61" title="Returns a sample, from density .">sample</a>() <span class="keyword">const</span>;
204		<a name="l00213"></a>00213 vec <a class="code" href="classbdm_1_1egiw.html#df70c05f918c3a6f86d60f10c1fd6ba2" title="return expected value">mean</a>() <span class="keyword">const</span>;
205		<a name="l00214"></a>00214 vec <a class="code" href="classbdm_1_1egiw.html#c1ecc406613cc2341225dc10c3d3b46a" title="return expected variance (not covariance!)">variance</a>() <span class="keyword">const</span>;
206		<a name="l00215"></a>00215
207		<a name="l00217"></a>00217 vec <a class="code" href="classbdm_1_1egiw.html#66d2ba9295c306012b309efcc9e516f0" title="LS estimate of .">est_theta</a>() <span class="keyword">const</span>;
208		<a name="l00218"></a>00218
209		<a name="l00220"></a>00220 <a class="code" href="classldmat.html" title="Matrix stored in LD form, (commonly known as UD).">ldmat</a> <a class="code" href="classbdm_1_1egiw.html#88c321a2051d1afdbb31a098896a717b" title="Covariance of the LS estimate.">est_theta_cov</a>() <span class="keyword">const</span>;
210		<a name="l00221"></a>00221
211		<a name="l00222"></a>00222 <span class="keywordtype">void</span> mean_mat ( mat &M, mat&R ) <span class="keyword">const</span>;
212		<a name="l00224"></a>00224 <span class="keywordtype">double</span> <a class="code" href="classbdm_1_1egiw.html#bfb8e7c619b34ad804a73bff71742b5e" title="In this instance, val= [theta, r]. For multivariate instances, it is stored columnwise...">evallog_nn</a> ( <span class="keyword">const</span> vec &val ) <span class="keyword">const</span>;
213		<a name="l00225"></a>00225 <span class="keywordtype">double</span> <a class="code" href="classbdm_1_1egiw.html#41d72ba7b2abc8a9a4209ffa98ed5633" title="logarithm of the normalizing constant, ">lognc</a> () <span class="keyword">const</span>;
214		<a name="l00226"></a><a class="code" href="classbdm_1_1egiw.html#8e610e95401a11baf34f65e16ecd87be">00226</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1egiw.html#8e610e95401a11baf34f65e16ecd87be" title="Power of the density, used e.g. to flatten the density.">pow</a> ( <span class="keywordtype">double</span> p ) {V=p;<a class="code" href="classbdm_1_1egiw.html#447eacf19d4f4083872686f044814dc4" title="Number of data records (degrees of freedom) of sufficient statistics.">nu</a>=p;};
215		<a name="l00227"></a>00227
216		<a name="l00230"></a>00230
217		<a name="l00231"></a>00231 <a class="code" href="classldmat.html" title="Matrix stored in LD form, (commonly known as UD).">ldmat</a>& _V() {<span class="keywordflow">return</span> V;}
218		<a name="l00232"></a>00232 <span class="keyword">const</span> <a class="code" href="classldmat.html" title="Matrix stored in LD form, (commonly known as UD).">ldmat</a>& _V()<span class="keyword"> const </span>{<span class="keywordflow">return</span> V;}
219		<a name="l00233"></a>00233 <span class="keywordtype">double</span>& _nu() {<span class="keywordflow">return</span> <a class="code" href="classbdm_1_1egiw.html#447eacf19d4f4083872686f044814dc4" title="Number of data records (degrees of freedom) of sufficient statistics.">nu</a>;}
220		<a name="l00234"></a>00234 <span class="keyword">const</span> <span class="keywordtype">double</span>& _nu()<span class="keyword"> const </span>{<span class="keywordflow">return</span> <a class="code" href="classbdm_1_1egiw.html#447eacf19d4f4083872686f044814dc4" title="Number of data records (degrees of freedom) of sufficient statistics.">nu</a>;}
221		<a name="l00235"></a><a class="code" href="classbdm_1_1egiw.html#55b76ec75bd2df5ef9cab3be20a33bbb">00235</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1egiw.html#55b76ec75bd2df5ef9cab3be20a33bbb">from_setting</a>(<span class="keyword">const</span> Setting &<span class="keyword">set</span>){
222		<a name="l00236"></a>00236 <span class="keyword">set</span>.lookupValue(<span class="stringliteral">"nu"</span>,<a class="code" href="classbdm_1_1egiw.html#447eacf19d4f4083872686f044814dc4" title="Number of data records (degrees of freedom) of sufficient statistics.">nu</a>);
223		<a name="l00237"></a>00237 <span class="keyword">set</span>.lookupValue(<span class="stringliteral">"dimx"</span>,<a class="code" href="classbdm_1_1egiw.html#23e4d78bea7e98840f3da30e76a2b57a" title="Dimension of the output.">dimx</a>);
224		<a name="l00238"></a>00238 mat V;
225		<a name="l00239"></a>00239 <a class="code" href="classbdm_1_1UI.html#652bfd23f5052e4f1cb317057d74a3e2" title="The existing instance of type T is initialized with values stored in the Setting...">UI::get</a>(V,<span class="keyword">set</span>,<span class="stringliteral">"V"</span>);
226		<a name="l00240"></a>00240 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>);
227		<a name="l00241"></a>00241 <a class="code" href="classbdm_1_1RV.html" title="Class representing variables, most often random variables.">RV</a>* <a class="code" href="classbdm_1_1epdf.html#62c5b8ff71d9ebe6cd58d3c342eb1dc8" title="Description of the random variable.">rv</a>=UI::build<RV>(<span class="keyword">set</span>,<span class="stringliteral">"rv"</span>);
228		<a name="l00242"></a>00242 <a class="code" href="classbdm_1_1epdf.html#f423e28448dbb69ef4905295ec8de8ff" title="Name its rv.">set_rv</a>(*rv);
229		<a name="l00243"></a>00243 <span class="keyword">delete</span> rv;
230		<a name="l00244"></a>00244 }
231		<a name="l00246"></a>00246 };
232		<a name="l00247"></a>00247 <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);
233		<a name="l00248"></a>00248
234		<a name="l00257"></a><a class="code" href="classbdm_1_1eDirich.html">00257</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>
235		<a name="l00258"></a>00258 {
236		<a name="l00259"></a>00259 <span class="keyword">protected</span>:
237		<a name="l00261"></a><a class="code" href="classbdm_1_1eDirich.html#f25886a49b4667af61245de81c83b5d2">00261</a> vec <a class="code" href="classbdm_1_1eDirich.html#f25886a49b4667af61245de81c83b5d2" title="sufficient statistics">beta</a>;
238		<a name="l00262"></a>00262 <span class="keyword">public</span>:
239		<a name="l00265"></a>00265
240		<a name="l00266"></a>00266 <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> ( ) {};
241		<a name="l00267"></a>00267 <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> );};
242		<a name="l00268"></a>00268 eDirich ( <span class="keyword">const</span> vec &beta0 ) {set_parameters ( beta0 );};
243		<a name="l00269"></a>00269 <span class="keywordtype">void</span> set_parameters ( <span class="keyword">const</span> vec &beta0 )
244		<a name="l00270"></a>00270 {
245		<a name="l00271"></a>00271 <a class="code" href="classbdm_1_1eDirich.html#f25886a49b4667af61245de81c83b5d2" title="sufficient statistics">beta</a>= beta0;
246		<a name="l00272"></a>00272 <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();
247		<a name="l00273"></a>00273 }
248		<a name="l00275"></a>00275
249		<a name="l00276"></a><a class="code" href="classbdm_1_1eDirich.html#3290613d31d58daa8a45a54b003871fc">00276</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 );};
250		<a name="l00277"></a><a class="code" href="classbdm_1_1eDirich.html#cb343355ec791298bb5a3404cd482fb6">00277</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>);};
251		<a name="l00278"></a><a class="code" href="classbdm_1_1eDirich.html#43c547a2507e233706f92712d8c2aacc">00278</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 ) );}
252		<a name="l00280"></a><a class="code" href="classbdm_1_1eDirich.html#e09a24938e80c3d94b0ee842d1552318">00280</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>
253		<a name="l00281"></a>00281 <span class="keyword"> </span>{
254		<a name="l00282"></a>00282 <span class="keywordtype">double</span> tmp; tmp= ( <a class="code" href="classbdm_1_1eDirich.html#f25886a49b4667af61245de81c83b5d2" title="sufficient statistics">beta</a>-1 ) *log ( val ); it_assert_debug ( std::isfinite ( tmp ),<span class="stringliteral">"Infinite value"</span> );
255		<a name="l00283"></a>00283 <span class="keywordflow">return</span> tmp;
256		<a name="l00284"></a>00284 };
257		<a name="l00285"></a><a class="code" href="classbdm_1_1eDirich.html#279a99f6266c82fe2273e83841f19eb2">00285</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>
258		<a name="l00286"></a>00286 <span class="keyword"> </span>{
259		<a name="l00287"></a>00287 <span class="keywordtype">double</span> tmp;
260		<a name="l00288"></a>00288 <span class="keywordtype">double</span> gam=sum ( <a class="code" href="classbdm_1_1eDirich.html#f25886a49b4667af61245de81c83b5d2" title="sufficient statistics">beta</a> );
261		<a name="l00289"></a>00289 <span class="keywordtype">double</span> lgb=0.0;
262		<a name="l00290"></a>00290 <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 ) );}
263		<a name="l00291"></a>00291 tmp= lgb-lgamma ( gam );
264		<a name="l00292"></a>00292 it_assert_debug ( std::isfinite ( tmp ),<span class="stringliteral">"Infinite value"</span> );
265		<a name="l00293"></a>00293 <span class="keywordflow">return</span> tmp;
266		<a name="l00294"></a>00294 };
267		<a name="l00296"></a><a class="code" href="classbdm_1_1eDirich.html#175e0add26d2105c28d8121eefb9e324">00296</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>;}
268		<a name="l00298"></a>00298 };
269		<a name="l00299"></a>00299
270		<a name="l00301"></a><a class="code" href="classbdm_1_1multiBM.html">00301</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>
271		<a name="l00302"></a>00302 {
272		<a name="l00303"></a>00303 <span class="keyword">protected</span>:
273		<a name="l00305"></a><a class="code" href="classbdm_1_1multiBM.html#9ecc6878abbd20eb8d8e43b6ab3f941a">00305</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>;
274		<a name="l00307"></a><a class="code" href="classbdm_1_1multiBM.html#044263356944c92209eecd39a5187d25">00307</a> vec &<a class="code" href="classbdm_1_1multiBM.html#044263356944c92209eecd39a5187d25" title="Pointer inside est to sufficient statistics.">beta</a>;
275		<a name="l00308"></a>00308 <span class="keyword">public</span>:
276		<a name="l00310"></a><a class="code" href="classbdm_1_1multiBM.html#c4dd6d9522a8a605776d21bac9bd9daf">00310</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() )
277		<a name="l00311"></a>00311 {
278		<a name="l00312"></a>00312 <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>();}
279		<a name="l00313"></a>00313 <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;}
280		<a name="l00314"></a>00314 }
281		<a name="l00316"></a><a class="code" href="classbdm_1_1multiBM.html#c4378cf8037f6bed29c74eea63344b31">00316</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() ) {}
282		<a name="l00318"></a><a class="code" href="classbdm_1_1multiBM.html#dbe6b90d410dc062a233d1dc09eeba52">00318</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>;}
283		<a name="l00319"></a><a class="code" href="classbdm_1_1multiBM.html#1e4bf41b61937fd80f34049742e23f95">00319</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 )
284		<a name="l00320"></a>00320 {
285		<a name="l00321"></a>00321 <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="l00322"></a>00322 <a class="code" href="classbdm_1_1multiBM.html#044263356944c92209eecd39a5187d25" title="Pointer inside est to sufficient statistics.">beta</a>+=dt;
287		<a name="l00323"></a>00323 <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="l00324"></a>00324 }
289		<a name="l00325"></a><a class="code" href="classbdm_1_1multiBM.html#e157b607c1e3fa91d42aeea44458e2bf">00325</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="l00326"></a>00326 <span class="keyword"> </span>{
291		<a name="l00327"></a>00327 <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> );
292		<a name="l00328"></a>00328 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>();
293		<a name="l00329"></a>00329
294		<a name="l00330"></a>00330 <span class="keywordtype">double</span> lll;
295		<a name="l00331"></a>00331 <span class="keywordflow">if</span> ( <a class="code" href="classbdm_1_1BMEF.html#1331865e10fb1ccef65bb4c47fa3be64" title="forgetting factor">frg</a><1.0 )
296		<a name="l00332"></a>00332 {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>();}
297		<a name="l00333"></a>00333 <span class="keywordflow">else</span>
298		<a name="l00334"></a>00334 <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>;}
299		<a name="l00335"></a>00335 <span class="keywordflow">else</span>{lll=pred.<a class="code" href="classbdm_1_1eDirich.html#279a99f6266c82fe2273e83841f19eb2" title="logarithm of the normalizing constant, ">lognc</a>();}
300		<a name="l00336"></a>00336
301		<a name="l00337"></a>00337 beta+=dt;
302		<a name="l00338"></a>00338 <span class="keywordflow">return</span> pred.<a class="code" href="classbdm_1_1eDirich.html#279a99f6266c82fe2273e83841f19eb2" title="logarithm of the normalizing constant, ">lognc</a>()-lll;
303		<a name="l00339"></a>00339 }
304		<a name="l00340"></a><a class="code" href="classbdm_1_1multiBM.html#aaeb18c989088feb8d26d300e4971732">00340</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 )
305		<a name="l00341"></a>00341 {
306		<a name="l00342"></a>00342 <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 );
307		<a name="l00343"></a>00343 <span class="comment">// sum(beta) should be equal to sum(B.beta)</span>
308		<a name="l00344"></a>00344 <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>
309		<a name="l00345"></a>00345 <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> ) );
310		<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>();}
311		<a name="l00347"></a>00347 }
312		<a name="l00348"></a>00348 <span class="keyword">const</span> <a class="code" href="classbdm_1_1epdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a>& posterior()<span class="keyword"> const </span>{<span class="keywordflow">return</span> <a class="code" href="classbdm_1_1multiBM.html#9ecc6878abbd20eb8d8e43b6ab3f941a" title="Conjugate prior and posterior.">est</a>;};
313		<a name="l00349"></a>00349 <span class="keyword">const</span> eDirich* _e()<span class="keyword"> const </span>{<span class="keywordflow">return</span> &<a class="code" href="classbdm_1_1multiBM.html#9ecc6878abbd20eb8d8e43b6ab3f941a" title="Conjugate prior and posterior.">est</a>;};
314		<a name="l00350"></a>00350 <span class="keywordtype">void</span> set_parameters ( <span class="keyword">const</span> vec &beta0 )
315		<a name="l00351"></a>00351 {
316		<a name="l00352"></a>00352 <a class="code" href="classbdm_1_1multiBM.html#9ecc6878abbd20eb8d8e43b6ab3f941a" title="Conjugate prior and posterior.">est</a>.set_parameters ( beta0 );
317		<a name="l00353"></a>00353 <span class="keywordflow">if</span> ( <a class="code" href="classbdm_1_1BM.html#faff0ad12556fe7dc0e2807d4fd938ee" title="If true, the filter will compute likelihood of the data record and store it in ll...">evalll</a> ) {<a class="code" href="classbdm_1_1BMEF.html#06e7b3ac03e10017d4288c76888e2865" title="cached value of lognc() in the previous step (used in evaluation of ll )">last_lognc</a>=<a class="code" href="classbdm_1_1multiBM.html#9ecc6878abbd20eb8d8e43b6ab3f941a" title="Conjugate prior and posterior.">est</a>.lognc();}
318		<a name="l00354"></a>00354 }
319		<a name="l00355"></a>00355 };
320		<a name="l00356"></a>00356
321		<a name="l00366"></a><a class="code" href="classbdm_1_1egamma.html">00366</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>
322		<a name="l00367"></a>00367 {
323		<a name="l00368"></a>00368 <span class="keyword">protected</span>:
324		<a name="l00370"></a><a class="code" href="classbdm_1_1egamma.html#0901ec983e66b8337aaa506e13b122fa">00370</a> vec <a class="code" href="classbdm_1_1egamma.html#0901ec983e66b8337aaa506e13b122fa" title="Vector .">alpha</a>;
325		<a name="l00372"></a><a class="code" href="classbdm_1_1egamma.html#457bfb1ccb2057df85073e519a15ccc1">00372</a> vec <a class="code" href="classbdm_1_1egamma.html#457bfb1ccb2057df85073e519a15ccc1" title="Vector .">beta</a>;
326		<a name="l00373"></a>00373 <span class="keyword">public</span> :
327		<a name="l00376"></a>00376 <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 ) {};
328		<a name="l00377"></a>00377 <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 );};
329		<a name="l00378"></a>00378 <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();};
330		<a name="l00380"></a>00380
331		<a name="l00381"></a>00381 vec <a class="code" href="classbdm_1_1egamma.html#6ed82f0fd05f6002487256d8e75a0bbd" title="Returns a sample, from density .">sample</a>() <span class="keyword">const</span>;
332		<a name="l00383"></a>00383 <span class="comment">// mat sample ( int N ) const;</span>
333		<a name="l00384"></a>00384 <span class="keywordtype">double</span> <a class="code" href="classbdm_1_1egamma.html#a8e11e5a580ff42a1b205974c60768c6" title="TODO: is it used anywhere?">evallog</a> ( <span class="keyword">const</span> vec &val ) <span class="keyword">const</span>;
334		<a name="l00385"></a>00385 <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>;
335		<a name="l00387"></a><a class="code" href="classbdm_1_1egamma.html#0865cb3d6339fdc7410806cf70a329ed">00387</a> vec& <a class="code" href="classbdm_1_1egamma.html#0865cb3d6339fdc7410806cf70a329ed" title="Returns poiter to alpha and beta. Potentially dengerous: use with care!">_alpha</a>() {<span class="keywordflow">return</span> <a class="code" href="classbdm_1_1egamma.html#0901ec983e66b8337aaa506e13b122fa" title="Vector .">alpha</a>;}
336		<a name="l00388"></a>00388 vec& _beta() {<span class="keywordflow">return</span> beta;}
337		<a name="l00389"></a><a class="code" href="classbdm_1_1egamma.html#49d256c42cce14c6faa56ec242b57e85">00389</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 );}
338		<a name="l00390"></a><a class="code" href="classbdm_1_1egamma.html#36986cc01917cd0796fadc17125bdec1">00390</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 ) ); }
339		<a name="l00391"></a>00391
340		<a name="l00400"></a><a class="code" href="classbdm_1_1egamma.html#8a6fd1a1c0190f3e0d95a2a1f99aafc1">00400</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>){
341		<a name="l00401"></a>00401 <a class="code" href="classbdm_1_1egamma.html#8a6fd1a1c0190f3e0d95a2a1f99aafc1">epdf::from_setting</a>(<span class="keyword">set</span>); <span class="comment">// reads rv</span>
342		<a name="l00402"></a>00402 <a class="code" href="classbdm_1_1UI.html#652bfd23f5052e4f1cb317057d74a3e2" title="The existing instance of type T is initialized with values stored in the Setting...">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>);
343		<a name="l00403"></a>00403 <a class="code" href="classbdm_1_1UI.html#652bfd23f5052e4f1cb317057d74a3e2" title="The existing instance of type T is initialized with values stored in the Setting...">UI::get</a>(beta,<span class="keyword">set</span>,<span class="stringliteral">"beta"</span>);
344		<a name="l00404"></a>00404 <a class="code" href="classbdm_1_1egamma.html#c3a8d8ae8ba79d0fb35036711fa7d127" title="This method TODO.">validate</a>();
345		<a name="l00405"></a>00405 }
346		<a name="l00406"></a><a class="code" href="classbdm_1_1egamma.html#c3a8d8ae8ba79d0fb35036711fa7d127">00406</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1egamma.html#c3a8d8ae8ba79d0fb35036711fa7d127" title="This method TODO.">validate</a>(){
347		<a name="l00407"></a>00407 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>);
348		<a name="l00408"></a>00408 <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();
349		<a name="l00409"></a>00409 }
350		<a name="l00410"></a>00410 };
351		<a name="l00411"></a>00411 <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);
352		<a name="l00428"></a><a class="code" href="classbdm_1_1eigamma.html">00428</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>
353		<a name="l00429"></a>00429 {
354		<a name="l00430"></a>00430 <span class="keyword">protected</span>:
355		<a name="l00431"></a>00431 <span class="keyword">public</span> :
356		<a name="l00436"></a>00436
357		<a name="l00437"></a><a class="code" href="classbdm_1_1eigamma.html#3aff7bf25ddac27731c60826fcfd878f">00437</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>();};
358		<a name="l00439"></a><a class="code" href="classbdm_1_1eigamma.html#46cecb295edbabd28120cb0f6f572bcb">00439</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 );}
359		<a name="l00440"></a><a class="code" href="classbdm_1_1eigamma.html#c2c696f8c668e9f65392c9449f6a5133">00440</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 );}
360		<a name="l00441"></a>00441 };
361		<a name="l00442"></a>00442 <span class="comment">/*</span>
362		<a name="l00444"></a>00444 <span class="comment"> class emix : public epdf {</span>
363		<a name="l00445"></a>00445 <span class="comment"> protected:</span>
364		<a name="l00446"></a>00446 <span class="comment"> int n;</span>
365		<a name="l00447"></a>00447 <span class="comment"> vec &w;</span>
366		<a name="l00448"></a>00448 <span class="comment"> Array<epdf*> Coms;</span>
367		<a name="l00449"></a>00449 <span class="comment"> public:</span>
368		<a name="l00451"></a>00451 <span class="comment"> emix ( const RV &rv, vec &w0): epdf(rv), n(w0.length()), w(w0), Coms(n) {};</span>
369		<a name="l00452"></a>00452 <span class="comment"> void set_parameters( int &i, double wi, epdf* ep){w(i)=wi;Coms(i)=ep;}</span>
370		<a name="l00453"></a>00453 <span class="comment"> vec mean(){vec pom; for(int i=0;i<n;i++){pom+=Coms(i)->mean()*w(i);} return pom;};</span>
371		<a name="l00454"></a>00454 <span class="comment"> vec sample() {it_error ( "Not implemented" );return 0;}</span>
372		<a name="l00455"></a>00455 <span class="comment"> };</span>
373		<a name="l00456"></a>00456 <span class="comment"> */</span>
374		<a name="l00457"></a>00457
375		<a name="l00459"></a>00459
376		<a name="l00460"></a><a class="code" href="classbdm_1_1euni.html">00460</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>
377		<a name="l00461"></a>00461 {
378		<a name="l00462"></a>00462 <span class="keyword">protected</span>:
379		<a name="l00464"></a><a class="code" href="classbdm_1_1euni.html#ff7ce6a2ef5ef0015bbd1398bed12f32">00464</a> vec <a class="code" href="classbdm_1_1euni.html#ff7ce6a2ef5ef0015bbd1398bed12f32" title="lower bound on support">low</a>;
380		<a name="l00466"></a><a class="code" href="classbdm_1_1euni.html#cfad2dea4a62db6872bda8abd75f0de1">00466</a> vec <a class="code" href="classbdm_1_1euni.html#cfad2dea4a62db6872bda8abd75f0de1" title="upper bound on support">high</a>;
381		<a name="l00468"></a><a class="code" href="classbdm_1_1euni.html#d3c27e331f90c754d80228108de8ed4c">00468</a> vec <a class="code" href="classbdm_1_1euni.html#d3c27e331f90c754d80228108de8ed4c" title="internal">distance</a>;
382		<a name="l00470"></a><a class="code" href="classbdm_1_1euni.html#31bb13e8449a8eff35246d46dae35c20">00470</a> <span class="keywordtype">double</span> <a class="code" href="classbdm_1_1euni.html#31bb13e8449a8eff35246d46dae35c20" title="normalizing coefficients">nk</a>;
383		<a name="l00472"></a><a class="code" href="classbdm_1_1euni.html#3e63be48dd58659663ca60cd18700476">00472</a> <span class="keywordtype">double</span> <a class="code" href="classbdm_1_1euni.html#3e63be48dd58659663ca60cd18700476" title="cache of log( nk )">lnk</a>;
384		<a name="l00473"></a>00473 <span class="keyword">public</span>:
385		<a name="l00476"></a>00476 <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> ( ) {}
386		<a name="l00477"></a>00477 <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 );}
387		<a name="l00478"></a>00478 <span class="keywordtype">void</span> set_parameters ( <span class="keyword">const</span> vec &low0, <span class="keyword">const</span> vec &high0 )
388		<a name="l00479"></a>00479 {
389		<a name="l00480"></a>00480 <a class="code" href="classbdm_1_1euni.html#d3c27e331f90c754d80228108de8ed4c" title="internal">distance</a> = high0-low0;
390		<a name="l00481"></a>00481 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> );
391		<a name="l00482"></a>00482 <a class="code" href="classbdm_1_1euni.html#ff7ce6a2ef5ef0015bbd1398bed12f32" title="lower bound on support">low</a> = low0;
392		<a name="l00483"></a>00483 <a class="code" href="classbdm_1_1euni.html#cfad2dea4a62db6872bda8abd75f0de1" title="upper bound on support">high</a> = high0;
393		<a name="l00484"></a>00484 <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> );
394		<a name="l00485"></a>00485 <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> );
395		<a name="l00486"></a>00486 <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();
396		<a name="l00487"></a>00487 }
397		<a name="l00489"></a>00489
398		<a name="l00490"></a>00490 <span class="keywordtype">double</span> eval ( <span class="keyword">const</span> vec &val )<span class="keyword"> const </span>{<span class="keywordflow">return</span> <a class="code" href="classbdm_1_1euni.html#31bb13e8449a8eff35246d46dae35c20" title="normalizing coefficients">nk</a>;}
399		<a name="l00491"></a><a class="code" href="classbdm_1_1euni.html#caa07b8307bd793d5339d6583e0aba81">00491</a> <span class="keywordtype">double</span> <a class="code" href="classbdm_1_1euni.html#caa07b8307bd793d5339d6583e0aba81" title="Compute log-probability of argument val.">evallog</a> ( <span class="keyword">const</span> vec &val )<span class="keyword"> const </span>{<span class="keywordflow">return</span> <a class="code" href="classbdm_1_1euni.html#3e63be48dd58659663ca60cd18700476" title="cache of log( nk )">lnk</a>;}
400		<a name="l00492"></a><a class="code" href="classbdm_1_1euni.html#fc5df80359ead2918384b2004ce67194">00492</a> vec <a class="code" href="classbdm_1_1euni.html#fc5df80359ead2918384b2004ce67194" title="Returns a sample, from density .">sample</a>()<span class="keyword"> const</span>
401		<a name="l00493"></a>00493 <span class="keyword"> </span>{
402		<a name="l00494"></a>00494 vec smp ( <a class="code" href="classbdm_1_1epdf.html#16adac20ec7fe07e1ea0b27d917788ce" title="dimension of the random variable">dim</a> );
403		<a name="l00495"></a>00495 <span class="preprocessor">#pragma omp critical</span>
404		<a name="l00496"></a>00496 <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 );
405		<a name="l00497"></a>00497 <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 );
406		<a name="l00498"></a>00498 }
407		<a name="l00500"></a><a class="code" href="classbdm_1_1euni.html#46caa8c13aba2e6228f964208918b226">00500</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;}
408		<a name="l00501"></a><a class="code" href="classbdm_1_1euni.html#951f932155111f6053c980f672b4c22c">00501</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;}
409		<a name="l00510"></a><a class="code" href="classbdm_1_1euni.html#77f5fef1f006fe056066da23b9e5f042">00510</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>){
410		<a name="l00511"></a>00511 <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>
411		<a name="l00512"></a>00512 <a class="code" href="classbdm_1_1UI.html#652bfd23f5052e4f1cb317057d74a3e2" title="The existing instance of type T is initialized with values stored in the Setting...">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>);
412		<a name="l00513"></a>00513 <a class="code" href="classbdm_1_1UI.html#652bfd23f5052e4f1cb317057d74a3e2" title="The existing instance of type T is initialized with values stored in the Setting...">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>);
413		<a name="l00514"></a>00514 }
414		<a name="l00515"></a>00515 };
415		<a name="l00516"></a>00516
416		<a name="l00517"></a>00517
417		<a name="l00523"></a>00523 <span class="keyword">template</span><<span class="keyword">class</span> sq_T>
418		<a name="l00524"></a><a class="code" href="classbdm_1_1mlnorm.html">00524</a> <span class="keyword">class </span><a class="code" href="classbdm_1_1mlnorm.html" title="Normal distributed linear function with linear function of mean value;.">mlnorm</a> : <span class="keyword">public</span> <a class="code" href="classbdm_1_1mEF.html" title="Exponential family model.">mEF</a>
419		<a name="l00525"></a>00525 {
420		<a name="l00526"></a>00526 <span class="keyword">protected</span>:
421		<a name="l00528"></a><a class="code" href="classbdm_1_1mlnorm.html#150ad6acb223b0a0abeaf92346686dcd">00528</a> <a class="code" href="classbdm_1_1enorm.html" title="Gaussian density with positive definite (decomposed) covariance matrix.">enorm<sq_T></a> <a class="code" href="classbdm_1_1epdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a>;
422		<a name="l00529"></a>00529 mat A;
423		<a name="l00530"></a>00530 vec mu_const;
424		<a name="l00531"></a>00531 vec& _mu; <span class="comment">//cached epdf.mu;</span>
425		<a name="l00532"></a>00532 <span class="keyword">public</span>:
426		<a name="l00535"></a>00535 <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_1mEF.html" title="Exponential family model.">mEF</a> (),<a class="code" href="classbdm_1_1epdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a> ( ),A ( ),_mu ( <a class="code" href="classbdm_1_1epdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a>._mu() ) {<a class="code" href="classbdm_1_1mpdf.html#5eea43c56d38e4441bfb30270db949c0" title="pointer to internal epdf">ep</a> =&<a class="code" href="classbdm_1_1epdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a>; };
427		<a name="l00536"></a>00536 <a class="code" href="classbdm_1_1mlnorm.html" title="Normal distributed linear function with linear function of mean value;.">mlnorm</a> ( <span class="keyword">const</span> mat &A, <span class="keyword">const</span> vec &mu0, <span class="keyword">const</span> sq_T &R ) :<a class="code" href="classbdm_1_1epdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a> ( ),_mu ( <a class="code" href="classbdm_1_1epdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a>._mu() )
428		<a name="l00537"></a>00537 {
429		<a name="l00538"></a>00538 <a class="code" href="classbdm_1_1mpdf.html#5eea43c56d38e4441bfb30270db949c0" title="pointer to internal epdf">ep</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_1mlnorm.html#5d18dec3167584338a4775c1d165d96f" title="Set A and R.">set_parameters</a> ( A,mu0,R );
430		<a name="l00539"></a>00539 };
431		<a name="l00541"></a>00541 <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1mlnorm.html#5d18dec3167584338a4775c1d165d96f" title="Set A and R.">set_parameters</a> ( <span class="keyword">const</span> mat &A, <span class="keyword">const</span> vec &mu0, <span class="keyword">const</span> sq_T &R );
432		<a name="l00544"></a>00544 <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1mlnorm.html#0dafc0196e7e07fd06dc6716e0e18bc2">condition</a> ( <span class="keyword">const</span> vec &cond );
433		<a name="l00545"></a>00545
434		<a name="l00547"></a><a class="code" href="classbdm_1_1mlnorm.html#56e587952f94fcac6cfc999eae6dbced">00547</a> vec& <a class="code" href="classbdm_1_1mlnorm.html#56e587952f94fcac6cfc999eae6dbced" title="access function">_mu_const</a>() {<span class="keywordflow">return</span> mu_const;}
435		<a name="l00549"></a><a class="code" href="classbdm_1_1mlnorm.html#262a2a486bff585f34bb6a5005b02614">00549</a> mat& <a class="code" href="classbdm_1_1mlnorm.html#262a2a486bff585f34bb6a5005b02614" title="access function">_A</a>() {<span class="keywordflow">return</span> A;}
436		<a name="l00551"></a><a class="code" href="classbdm_1_1mlnorm.html#78120ecd1c2b1d7e80124b4603504604">00551</a> mat <a class="code" href="classbdm_1_1mlnorm.html#78120ecd1c2b1d7e80124b4603504604" title="access function">_R</a>() {<span class="keywordflow">return</span> <a class="code" href="classbdm_1_1epdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a>._R().to_mat();}
437		<a name="l00552"></a>00552
438		<a name="l00553"></a>00553 <span class="keyword">template</span><<span class="keyword">class</span> sq_M>
439		<a name="l00554"></a>00554 <span class="keyword">friend</span> std::ostream &operator<< ( std::ostream &os, mlnorm<sq_M> &ml );
440		<a name="l00555"></a>00555 };
441		<a name="l00556"></a>00556
442		<a name="l00558"></a>00558 <span class="keyword">template</span><<span class="keyword">class</span> sq_T>
443		<a name="l00559"></a><a class="code" href="classbdm_1_1mgnorm.html">00559</a> <span class="keyword">class </span><a class="code" href="classbdm_1_1mgnorm.html" title="Mpdf with general function for mean value.">mgnorm</a> : <span class="keyword">public</span> <a class="code" href="classbdm_1_1mEF.html" title="Exponential family model.">mEF</a>
444		<a name="l00560"></a>00560 {
445		<a name="l00561"></a>00561 <span class="keyword">protected</span>:
446		<a name="l00563"></a><a class="code" href="classbdm_1_1mgnorm.html#8f7a376a1d2197e0634557e88e03104a">00563</a> <a class="code" href="classbdm_1_1enorm.html" title="Gaussian density with positive definite (decomposed) covariance matrix.">enorm<sq_T></a> <a class="code" href="classbdm_1_1epdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a>;
447		<a name="l00564"></a>00564 vec &mu;
448		<a name="l00565"></a>00565 <a class="code" href="classbdm_1_1fnc.html" title="Class representing function of variable represented by rv.">fnc</a>* g;
449		<a name="l00566"></a>00566 <span class="keyword">public</span>:
450		<a name="l00568"></a><a class="code" href="classbdm_1_1mgnorm.html#1b014915d74470d3efab74e07cacb97d">00568</a> <a class="code" href="classbdm_1_1mgnorm.html#1b014915d74470d3efab74e07cacb97d" title="default constructor">mgnorm</a>() :mu ( <a class="code" href="classbdm_1_1epdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a>._mu() ) {<a class="code" href="classbdm_1_1mpdf.html#5eea43c56d38e4441bfb30270db949c0" title="pointer to internal epdf">ep</a>=&<a class="code" href="classbdm_1_1epdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a>;}
451		<a name="l00570"></a><a class="code" href="classbdm_1_1mgnorm.html#578e02458e2a0d17f3864826b6ebd564">00570</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1mgnorm.html#578e02458e2a0d17f3864826b6ebd564" title="set mean function">set_parameters</a> ( <a class="code" href="classbdm_1_1fnc.html" title="Class representing function of variable represented by rv.">fnc</a>* g0, <span class="keyword">const</span> sq_T &R0 ) {g=g0; <a class="code" href="classbdm_1_1epdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a>.set_parameters ( zeros ( g-><a class="code" href="classbdm_1_1fnc.html#083832294da9d1e40804158b979c4341" title="access function">dimension</a>() ), R0 );}
452		<a name="l00571"></a><a class="code" href="classbdm_1_1mgnorm.html#b31d63472cf6a1030cd8dbd8094c1f6d">00571</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1mgnorm.html#b31d63472cf6a1030cd8dbd8094c1f6d" title="Update ep so that it represents this mpdf conditioned on rvc = cond.">condition</a> ( <span class="keyword">const</span> vec &cond ) {mu=g-><a class="code" href="classbdm_1_1fnc.html#6277b11d7fffc7ef8a2fa3e84ae5bad4" title="function evaluates numerical value of at cond ">eval</a> ( cond );};
453		<a name="l00572"></a>00572
454		<a name="l00573"></a>00573
455		<a name="l00601"></a><a class="code" href="classbdm_1_1mgnorm.html#d717dacc6a9eb967f8410994dc6dc6f9">00601</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> )
456		<a name="l00602"></a>00602 {
457		<a name="l00603"></a>00603 <a class="code" href="classbdm_1_1fnc.html" title="Class representing function of variable represented by rv.">fnc</a>* g = UI::build<fnc>( <span class="keyword">set</span>, <span class="stringliteral">"g"</span> );
458		<a name="l00604"></a>00604
459		<a name="l00605"></a>00605 mat R;
460		<a name="l00606"></a>00606 <span class="keywordflow">if</span> ( <span class="keyword">set</span>.exists( <span class="stringliteral">"dR"</span> ) )
461		<a name="l00607"></a>00607 {
462		<a name="l00608"></a>00608 vec dR;
463		<a name="l00609"></a>00609 <a class="code" href="classbdm_1_1UI.html#652bfd23f5052e4f1cb317057d74a3e2" title="The existing instance of type T is initialized with values stored in the Setting...">UI::get</a>( dR, <span class="keyword">set</span>, <span class="stringliteral">"dR"</span> );
464		<a name="l00610"></a>00610 R=diag(dR);
465		<a name="l00611"></a>00611 }
466		<a name="l00612"></a>00612 <span class="keywordflow">else</span>
467		<a name="l00613"></a>00613 <a class="code" href="classbdm_1_1UI.html#652bfd23f5052e4f1cb317057d74a3e2" title="The existing instance of type T is initialized with values stored in the Setting...">UI::get</a>( R, <span class="keyword">set</span>, <span class="stringliteral">"R"</span>);
468		<a name="l00614"></a>00614
469		<a name="l00615"></a>00615 <a class="code" href="classbdm_1_1mgnorm.html#578e02458e2a0d17f3864826b6ebd564" title="set mean function">set_parameters</a>(g,R);
470		<a name="l00616"></a>00616 }
471		<a name="l00617"></a>00617
472		<a name="l00618"></a>00618 <span class="comment">/*void mgnorm::to_setting( Setting &set ) const</span>
473		<a name="l00619"></a>00619 <span class="comment"> { </span>
474		<a name="l00620"></a>00620 <span class="comment"> Transport::to_setting( set );</span>
475		<a name="l00621"></a>00621 <span class="comment"></span>
476		<a name="l00622"></a>00622 <span class="comment"> Setting &kilometers_setting = set.add("kilometers", Setting::TypeInt );</span>
477		<a name="l00623"></a>00623 <span class="comment"> kilometers_setting = kilometers;</span>
478		<a name="l00624"></a>00624 <span class="comment"></span>
479		<a name="l00625"></a>00625 <span class="comment"> UI::save( passengers, set, "passengers" );</span>
480		<a name="l00626"></a>00626 <span class="comment"> }*/</span>
481		<a name="l00627"></a>00627
482		<a name="l00628"></a>00628 };
483		<a name="l00629"></a>00629
484		<a name="l00630"></a>00630 <a class="code" href="user__info_8h.html#4f9de2f17e844047726487b99def99c6" title="Macro for registration of class into map of user-infos, registered class is scriptable...">UIREGISTER</a>(mgnorm<chmat>);
485		<a name="l00631"></a>00631
	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);
486	488	<a name="l00632"></a>00632
487		<a name="l00640"></a><a class="code" href="classbdm_1_1mlstudent.html">00640</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>
488		<a name="l006~~41"></a>00641 {~~
489		<a name="l006~~42"></a>00642 <span class="keyword">protected</span>:~~
490		<a name="l006~~43"></a>00643 <a class="code" href="classldmat.html" title="Matrix stored in LD form, (commonly known as UD).">ldmat</a> Lambda;~~
491		<a name="l00644"></a>00644 <a class="code" href="classldmat.html" title="Matrix stored in LD form, (commonly known as UD).">ldmat</a> &<a class="code" href="classbdm_1_1mlnorm.html#78120ecd1c2b1d7e80124b4603504604" title="access function">_R</a>;
492		<a name="l006~~45"></a>00645 <a class="code" href="classldmat.html" title="Matrix stored in LD form, (commonly known as UD).">ldmat</a> Re~~;
493		<a name="l006~~46"></a>00646 <span class="keyword">public</span>:~~
494		<a name="l0064~~7"></a>00647 <a class="code" href="classbdm_1_1mlstudent.html">mlstudent</a> ( ) :<a class="code" href="classbdm_1_1mlnorm.html">mlnorm<ldmat></a> (),~~
495		<a name="l00648"></a>00648 Lambda (), <a class="code" href="classbdm_1_1mlnorm.html#78120ecd1c2b1d7e80124b4603504604" title="access function">_R</a> ( <a class="code" href="classbdm_1_1epdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a>._R() ) {}
496		<a name="l00649"></a>00649 <span class="keywordtype">void</span> set_parameters ( <span class="keyword">const</span> mat &A0, <span class="keyword">const</span> vec &mu0, <span class="keyword">const</span> <a class="code" href="classldmat.html" title="Matrix stored in LD form, (commonly known as UD).">ldmat</a> &R0, <span class="keyword">const</span> <a class="code" href="classldmat.html" title="Matrix stored in LD form, (commonly known as UD).">ldmat</a>& Lambda0 )
497		<a name="l00650"></a>00650 {
498		<a name="l0065~~1"></a>00651 it_assert_debug ( A0.rows() ==mu0.length(),<span class="stringliteral">""</span> )~~;
499		<a name="l00652"></a>00652 it_assert_debug ( R0.<a class="code" href="group__math.html#g96dfb21865db4f5bd36fa70f9b0b1163" title="access function">rows</a>() ==A0.rows(),<span class="stringliteral">""</span> );
500		<a name="l0065~~3"></a>00653~~
501		<a name="l00654"></a>00654 <a class="code" href="classbdm_1_1epdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a>.set_parameters ( mu0,Lambda ); <span class="comment">//</span>
502		<a name="l0065~~5"></a>00655 A = A0;~~
503		<a name="l0065~~6"></a>00656 mu_const = mu0;~~
504		<a name="l006~~57"></a>00657 Re=R0;~~
505		<a name="l006~~58"></a>00658 Lambda = Lambda0~~;
506		<a name="l006~~59"></a>00659 }~~
507		<a name="l00660"></a><a class="code" href="classbdm_1_1mlstudent.html#efd37560585c8613897f30d3c2f58d0d">00660</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1mlstudent.html#efd37560585c8613897f30d3c2f58d0d">condition</a> ( <span class="keyword">const</span> vec &cond )
508		<a name="l0066~~1"></a>00661 {~~
509		<a name="l0066~~2"></a>00662 _mu = A*cond + mu_const~~;
510		<a name="l0066~~3"></a>00663 <span class="keywordtype">double</span> zeta~~;
511		<a name="l0066~~4"></a>00664 <span class="comment">//ugly hack!</span>~~
512		<a name="l00665"></a>00665 <span class="keywordflow">if</span> ( ( cond.length() +1 ) ==Lambda.<a class="code" href="group__math.html#g96dfb21865db4f5bd36fa70f9b0b1163" title="access function">rows</a>() )
513		<a name="l006~~66"></a>00666 {~~
514		<a name="l00667"></a>00667 zeta = Lambda.<a class="code" href="classldmat.html#d876c5f83e02b3e809b35c9de5068f14" title="Evaluates quadratic form ;.">invqform</a> ( concat ( cond, vec_1 ( 1.0 ) ) );
515		<a name="l006~~68"></a>00668 }~~
516		<a name="l006~~69"></a>00669 <span class="keywordflow">else</span>~~
517		<a name="l0067~~0"></a>00670 {~~
518		<a name="l00671"></a>00671 zeta = Lambda.<a class="code" href="classldmat.html#d876c5f83e02b3e809b35c9de5068f14" title="Evaluates quadratic form ;.">invqform</a> ( cond );
519		<a name="l0067~~2"></a>00672 }~~
520		<a name="l0067~~3"></a>00673 <a class="code" href="classbdm_1_1mlnorm.html#78120ecd1c2b1d7e80124b4603504604" title="access function">_R</a> = Re;~~
521		<a name="l00674"></a>00674 <a class="code" href="classbdm_1_1mlnorm.html#78120ecd1c2b1d7e80124b4603504604" title="access function">_R</a>*= ( 1+zeta );<span class="comment">// / ( nu ); << nu is in Re!!!!!!</span>
522		<a name="l0067~~5"></a>00675 };~~
523		<a name="l006~~76"></a>00676~~
524		<a name="l006~~77"></a>00677 };~~
525		<a name="l00687"></a><a class="code" href="classbdm_1_1mgamma.html">00687</a> <span class="keyword">class </span><a class="code" href="classbdm_1_1mgamma.html" title="Gamma random walk.">mgamma</a> : <span class="keyword">public</span> <a class="code" href="classbdm_1_1mEF.html" title="Exponential family model.">mEF</a>
526		<a name="l0068~~8"></a>00688 {~~
527		<a name="l0068~~9"></a>00689 <span class="keyword">protected</span>:~~
528		<a name="l00691"></a><a class="code" href="classbdm_1_1mgamma.html#bdc9f1e9e03c09e91103fee269864438">00691</a> <a class="code" href="classbdm_1_1egamma.html" title="Gamma posterior density.">egamma</a> <a class="code" href="classbdm_1_1epdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a>;
529		<a name="l00693"></a><a class="code" href="classbdm_1_1mgamma.html#b20cf88cca1fe9b0b8f2a412608bfd09">00693</a> <span class="keywordtype">double</span> <a class="code" href="classbdm_1_1mgamma.html#b20cf88cca1fe9b0b8f2a412608bfd09" title="Constant .">k</a>;
530		<a name="l00695"></a><a class="code" href="classbdm_1_1mgamma.html#3d95f4dde9214ff6dba265e18af60312">00695</a> vec &<a class="code" href="classbdm_1_1mgamma.html#3d95f4dde9214ff6dba265e18af60312" title="cache of epdf.beta">_beta</a>;
531		<a name="l0069~~6"></a>00696~~
532		<a name="l0069~~7"></a>00697 <span class="keyword">public</span>:~~
533		<a name="l00699"></a><a class="code" href="classbdm_1_1mgamma.html#1a9dc8661e5b214a8185d6e6b9956eb1">00699</a> <a class="code" href="classbdm_1_1mgamma.html#1a9dc8661e5b214a8185d6e6b9956eb1" title="Constructor.">mgamma</a> ( ) : <a class="code" href="classbdm_1_1mEF.html" title="Exponential family model.">mEF</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_1mgamma.html#3d95f4dde9214ff6dba265e18af60312" title="cache of epdf.beta">_beta</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_1mgamma.html#3d95f4dde9214ff6dba265e18af60312" title="cache of epdf.beta">_beta</a>() ) {<a class="code" href="classbdm_1_1mpdf.html#5eea43c56d38e4441bfb30270db949c0" title="pointer to internal epdf">ep</a>=&<a class="code" href="classbdm_1_1epdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a>;};
534		<a name="l00701"></a>00701 <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 );
535		<a name="l00702"></a><a class="code" href="classbdm_1_1mgamma.html#8996500f1885e39cde30221b20900bff">00702</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1mgamma.html#8996500f1885e39cde30221b20900bff" title="Update ep so that it represents this mpdf conditioned on rvc = cond.">condition</a> ( <span class="keyword">const</span> vec &val ) {<a class="code" href="classbdm_1_1mgamma.html#3d95f4dde9214ff6dba265e18af60312" title="cache of epdf.beta">_beta</a>=<a class="code" href="classbdm_1_1mgamma.html#b20cf88cca1fe9b0b8f2a412608bfd09" title="Constant .">k</a>/val;};
536		<a name="l00712"></a><a class="code" href="classbdm_1_1mgamma.html#da2af0f327e5452bee71d1bf97452ae4">00712</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>){
537		<a name="l00713"></a>00713 <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>
538		<a name="l007~~14"></a>00714 vec betatmp; <span class="comment">// ugly but necessary</span>~~
539		<a name="l00715"></a>00715 <a class="code" href="classbdm_1_1UI.html#652bfd23f5052e4f1cb317057d74a3e2" title="The existing instance of type T is initialized with values stored in the Setting...">UI::get</a>(betatmp,<span class="keyword">set</span>,<span class="stringliteral">"beta"</span>);
540		<a name="l00716"></a>00716 <span class="keyword">set</span>.lookupValue(<span class="stringliteral">"k"</span>,<a class="code" href="classbdm_1_1mgamma.html#b20cf88cca1fe9b0b8f2a412608bfd09" title="Constant .">k</a>);
541		<a name="l00717"></a>00717 <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);
542		<a name="l0071~~8"></a>00718 }~~
543		<a name="l0071~~9"></a>00719~~ };
544		<a name="l00720"></a>00720 <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);
545		<a name="l0072~~1"></a>00721~~
546		<a name="l00731"></a><a class="code" href="classbdm_1_1migamma.html">00731</a> <span class="keyword">class </span><a class="code" href="classbdm_1_1migamma.html" title="Inverse-Gamma random walk.">migamma</a> : <span class="keyword">public</span> <a class="code" href="classbdm_1_1mEF.html" title="Exponential family model.">mEF</a>
547		<a name="l007~~32"></a>00732 {~~
548		<a name="l007~~33"></a>00733 <span class="keyword">protected</span>:~~
549		<a name="l00735"></a><a class="code" href="classbdm_1_1migamma.html#a31b39d4179551b593c9e0d7d756783a">00735</a> <a class="code" href="classbdm_1_1eigamma.html" title="Inverse-Gamma posterior density.">eigamma</a> <a class="code" href="classbdm_1_1epdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a>;
550		<a name="l00737"></a><a class="code" href="classbdm_1_1migamma.html#dc56bc9da542e0103ec16b9be8e5e38c">00737</a> <span class="keywordtype">double</span> <a class="code" href="classbdm_1_1migamma.html#dc56bc9da542e0103ec16b9be8e5e38c" title="Constant .">k</a>;
551		<a name="l00739"></a><a class="code" href="classbdm_1_1migamma.html#c9847093da59a9ba0ebb68d2c592f5dc">00739</a> vec &<a class="code" href="classbdm_1_1migamma.html#c9847093da59a9ba0ebb68d2c592f5dc" title="cache of epdf.alpha">_alpha</a>;
552		<a name="l00741"></a><a class="code" href="classbdm_1_1migamma.html#0d854c047001b5465cf1ba21f52904b5">00741</a> vec &<a class="code" href="classbdm_1_1migamma.html#0d854c047001b5465cf1ba21f52904b5" title="cache of epdf.beta">_beta</a>;
553		<a name="l007~~42"></a>00742~~
554		<a name="l007~~43"></a>00743 <span class="keyword">public</span>:~~
555		<a name="l00746"></a>00746 <a class="code" href="classbdm_1_1migamma.html" title="Inverse-Gamma random walk.">migamma</a> ( ) : <a class="code" href="classbdm_1_1mEF.html" title="Exponential family model.">mEF</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_1migamma.html#c9847093da59a9ba0ebb68d2c592f5dc" title="cache of epdf.alpha">_alpha</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_1migamma.html#c9847093da59a9ba0ebb68d2c592f5dc" title="cache of epdf.alpha">_alpha</a>() ), <a class="code" href="classbdm_1_1migamma.html#0d854c047001b5465cf1ba21f52904b5" title="cache of epdf.beta">_beta</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_1migamma.html#0d854c047001b5465cf1ba21f52904b5" title="cache of epdf.beta">_beta</a>() ) {<a class="code" href="classbdm_1_1mpdf.html#5eea43c56d38e4441bfb30270db949c0" title="pointer to internal epdf">ep</a>=&<a class="code" href="classbdm_1_1epdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a>;};
556		<a name="l00747"></a>00747 <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_1mEF.html" title="Exponential family model.">mEF</a> (), <a class="code" href="classbdm_1_1epdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a> ( m.<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_1migamma.html#c9847093da59a9ba0ebb68d2c592f5dc" title="cache of epdf.alpha">_alpha</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_1migamma.html#c9847093da59a9ba0ebb68d2c592f5dc" title="cache of epdf.alpha">_alpha</a>() ), <a class="code" href="classbdm_1_1migamma.html#0d854c047001b5465cf1ba21f52904b5" title="cache of epdf.beta">_beta</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_1migamma.html#0d854c047001b5465cf1ba21f52904b5" title="cache of epdf.beta">_beta</a>() ) {<a class="code" href="classbdm_1_1mpdf.html#5eea43c56d38e4441bfb30270db949c0" title="pointer to internal epdf">ep</a>=&<a class="code" href="classbdm_1_1epdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a>;};
557		<a name="l0074~~9"></a>00749~~
558		<a name="l00751"></a><a class="code" href="classbdm_1_1migamma.html#8b10ab922e2a7bae2fb6bb3efc7b6151">00751</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 )
559		<a name="l007~~52"></a>00752 {~~
560		<a name="l0075~~3"></a>00753 <a class="code" href="classbdm_1_1migamma.html#dc56bc9da542e0103ec16b9be8e5e38c" title="Constant .">k</a>=k0~~;
561		<a name="l00754"></a>00754 <a class="code" href="classbdm_1_1epdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a>.set_parameters ( ( 1.0/ ( <a class="code" href="classbdm_1_1migamma.html#dc56bc9da542e0103ec16b9be8e5e38c" title="Constant .">k</a><a class="code" href="classbdm_1_1migamma.html#dc56bc9da542e0103ec16b9be8e5e38c" title="Constant .">k</a> ) +2.0 ) ones ( len ) <span class="comment">/alpha/</span>, ones ( len ) <span class="comment">/beta/</span> );
562		<a name="l0075~~5"></a>00755 <a class="code" href="classbdm_1_1mpdf.html#7c1900976ff13dbc09c9729b3bbff9e6" title="dimension of the condition">dimc</a> = dimension()~~;
563		<a name="l0075~~6"></a>00756 };~~
564		<a name="l00757"></a><a class="code" href="classbdm_1_1migamma.html#7a34b1e2e3aa2250d7c0ed7df1665b8c">00757</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1migamma.html#7a34b1e2e3aa2250d7c0ed7df1665b8c" title="Update ep so that it represents this mpdf conditioned on rvc = cond.">condition</a> ( <span class="keyword">const</span> vec &val )
565		<a name="l00758"></a>00758 {
566		<a name="l00759"></a>00759 <a class="code" href="classbdm_1_1migamma.html#0d854c047001b5465cf1ba21f52904b5" title="cache of epdf.beta">_beta</a>=elem_mult ( val, ( <a class="code" href="classbdm_1_1migamma.html#c9847093da59a9ba0ebb68d2c592f5dc" title="cache of epdf.alpha">_alpha</a>-1.0 ) );
567		<a name="l00760"></a>00760 };
568		<a name="l00761"></a>00761 };
569		<a name="l00762"></a>00762
	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 }
570	572	<a name="l00763"></a>00763
571		<a name="l00775"></a><a class="code" href="classbdm_1_1mgamma__fix.html">00775</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>
572		<a name="l00776"></a>00776 {
573		<a name="l00777"></a>00777 <span class="keyword">protected</span>:
574		<a name="l00779"></a><a class="code" href="classbdm_1_1mgamma__fix.html#1eb701506aabb2e6af007e487212d6fa">00779</a> <span class="keywordtype">double</span> <a class="code" href="classbdm_1_1mgamma__fix.html#1eb701506aabb2e6af007e487212d6fa" title="parameter l">l</a>;
575		<a name="l00781"></a><a class="code" href="classbdm_1_1mgamma__fix.html#018c6f901a04e419455308a07eb3b0b2">00781</a> vec <a class="code" href="classbdm_1_1mgamma__fix.html#018c6f901a04e419455308a07eb3b0b2" title="reference vector">refl</a>;
576		<a name="l00782"></a>00782 <span class="keyword">public</span>:
577		<a name="l00784"></a><a class="code" href="classbdm_1_1mgamma__fix.html#9a31bc9b4b60188a18a2a6b588dc4b2d">00784</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> () {};
578		<a name="l00786"></a><a class="code" href="classbdm_1_1mgamma__fix.html#1bfd30e90db9dc1fbda4a9fbb0b716b2">00786</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 )
579		<a name="l00787"></a>00787 {
580		<a name="l00788"></a>00788 <a class="code" href="classbdm_1_1mgamma__fix.html#1bfd30e90db9dc1fbda4a9fbb0b716b2" title="Set value of k.">mgamma::set_parameters</a> ( k0, ref0 );
581		<a name="l00789"></a>00789 <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;
582		<a name="l00790"></a>00790 <a class="code" href="classbdm_1_1mpdf.html#7c1900976ff13dbc09c9729b3bbff9e6" title="dimension of the condition">dimc</a>=dimension();
583		<a name="l00791"></a>00791 };
584		<a name="l00792"></a>00792
585		<a name="l00793"></a><a class="code" href="classbdm_1_1mgamma__fix.html#1d539591deb7a38bb3403c2b396c8ff7">00793</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1mgamma__fix.html#1d539591deb7a38bb3403c2b396c8ff7" title="Update ep so that it represents this mpdf conditioned on rvc = cond.">condition</a> ( <span class="keyword">const</span> vec &val ) {vec mean=elem_mult ( <a class="code" href="classbdm_1_1mgamma__fix.html#018c6f901a04e419455308a07eb3b0b2" title="reference vector">refl</a>,pow ( val,<a class="code" href="classbdm_1_1mgamma__fix.html#1eb701506aabb2e6af007e487212d6fa" title="parameter l">l</a> ) ); <a class="code" href="classbdm_1_1mgamma.html#3d95f4dde9214ff6dba265e18af60312" title="cache of epdf.beta">_beta</a>=<a class="code" href="classbdm_1_1mgamma.html#b20cf88cca1fe9b0b8f2a412608bfd09" title="Constant .">k</a>/mean;};
586		<a name="l00794"></a>00794 };
587		<a name="l00795"></a>00795
588		<a name="l00796"></a>00796
589		<a name="l00809"></a><a class="code" href="classbdm_1_1migamma__ref.html">00809</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>
590		<a name="l00810"></a>00810 {
591		<a name="l00811"></a>00811 <span class="keyword">protected</span>:
592		<a name="l00813"></a><a class="code" href="classbdm_1_1migamma__ref.html#cdc1345ba8375fbdb18a69322d2f841d">00813</a> <span class="keywordtype">double</span> <a class="code" href="classbdm_1_1migamma__ref.html#cdc1345ba8375fbdb18a69322d2f841d" title="parameter l">l</a>;
593		<a name="l00815"></a><a class="code" href="classbdm_1_1migamma__ref.html#3692dc67caf4367e15564d37f45476f6">00815</a> vec <a class="code" href="classbdm_1_1migamma__ref.html#3692dc67caf4367e15564d37f45476f6" title="reference vector">refl</a>;
594		<a name="l00816"></a>00816 <span class="keyword">public</span>:
595		<a name="l00818"></a><a class="code" href="classbdm_1_1migamma__ref.html#f45b15a10f084991ba6b48295f10421f">00818</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> ( ) {};
596		<a name="l00820"></a><a class="code" href="classbdm_1_1migamma__ref.html#b0b4eb278ef5d0831ec4954ba7bd2800">00820</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 )
597		<a name="l00821"></a>00821 {
598		<a name="l00822"></a>00822 <a class="code" href="classbdm_1_1migamma__ref.html#b0b4eb278ef5d0831ec4954ba7bd2800" title="Set value of k.">migamma::set_parameters</a> ( ref0.length(), k0 );
599		<a name="l00823"></a>00823 <a class="code" href="classbdm_1_1migamma__ref.html#3692dc67caf4367e15564d37f45476f6" title="reference vector">refl</a>=pow ( ref0,1.0-l0 );
600		<a name="l00824"></a>00824 <a class="code" href="classbdm_1_1migamma__ref.html#cdc1345ba8375fbdb18a69322d2f841d" title="parameter l">l</a>=l0;
601		<a name="l00825"></a>00825 <a class="code" href="classbdm_1_1mpdf.html#7c1900976ff13dbc09c9729b3bbff9e6" title="dimension of the condition">dimc</a> = dimension();
602		<a name="l00826"></a>00826 };
603		<a name="l00827"></a>00827
604		<a name="l00828"></a><a class="code" href="classbdm_1_1migamma__ref.html#ae86b2e4ff963d62e05d4e130514634a">00828</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1migamma__ref.html#ae86b2e4ff963d62e05d4e130514634a" title="Update ep so that it represents this mpdf conditioned on rvc = cond.">condition</a> ( <span class="keyword">const</span> vec &val )
605		<a name="l00829"></a>00829 {
606		<a name="l00830"></a>00830 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> ) );
607		<a name="l00831"></a>00831 <a class="code" href="classbdm_1_1migamma__ref.html#ae86b2e4ff963d62e05d4e130514634a" title="Update ep so that it represents this mpdf conditioned on rvc = cond.">migamma::condition</a> ( mean );
608		<a name="l00832"></a>00832 };
609		<a name="l00833"></a>00833
610		<a name="l00854"></a>00854 <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> );
611		<a name="l00855"></a>00855
612		<a name="l00856"></a>00856 <span class="comment">// TODO dodelat void to_setting( Setting &set ) const;</span>
613		<a name="l00857"></a>00857 };
614		<a name="l00858"></a>00858
615		<a name="l00859"></a>00859
616		<a name="l00860"></a>00860 <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);
617		<a name="l00861"></a>00861
618		<a name="l00871"></a><a class="code" href="classbdm_1_1elognorm.html">00871</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>
619		<a name="l00872"></a>00872 {
620		<a name="l00873"></a>00873 <span class="keyword">public</span>:
621		<a name="l00874"></a><a class="code" href="classbdm_1_1elognorm.html#8b948e2bce1253765a2542199913aaba">00874</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>() );};
622		<a name="l00875"></a><a class="code" href="classbdm_1_1elognorm.html#adb41e4f4d6600dec6f8c1dbc5ed9eea">00875</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 );};
623		<a name="l00876"></a>00876
624		<a name="l00877"></a>00877 };
	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);
625	634	<a name="l00878"></a>00878
626		<a name="l00890"></a><a class="code" href="classbdm_1_1mlognorm.html">00890</a> <span class="keyword">class </span><a class="code" href="classbdm_1_1mlognorm.html" title="Log-Normal random walk.">mlognorm</a> : <span class="keyword">public</span> <a class="code" href="classbdm_1_1mpdf.html" title="Conditional probability density, e.g. modeling some dependencies.">mpdf</a>
627		<a name="l00891"></a>00891 {
628		<a name="l00892"></a>00892 <span class="keyword">protected</span>:
629		<a name="l00893"></a>00893 <a class="code" href="classbdm_1_1elognorm.html">elognorm</a> eno;
630		<a name="l00895"></a><a class="code" href="classbdm_1_1mlognorm.html#a51128a2e503b8b2ce698244b9e0db1a">00895</a> <span class="keywordtype">double</span> <a class="code" href="classbdm_1_1mlognorm.html#a51128a2e503b8b2ce698244b9e0db1a" title="parameter 1/2*sigma^2">sig2</a>;
631		<a name="l00897"></a><a class="code" href="classbdm_1_1mlognorm.html#7d0063f77d899ef22e8c5edd642176d2">00897</a> vec &<a class="code" href="classbdm_1_1mlognorm.html#7d0063f77d899ef22e8c5edd642176d2" title="access">mu</a>;
632		<a name="l00898"></a>00898 <span class="keyword">public</span>:
633		<a name="l00900"></a><a class="code" href="classbdm_1_1mlognorm.html#a5d6eb2688d02e0348b96c4fbd7bde41">00900</a> <a class="code" href="classbdm_1_1mlognorm.html#a5d6eb2688d02e0348b96c4fbd7bde41" title="Constructor.">mlognorm</a> ( ) : eno (), <a class="code" href="classbdm_1_1mlognorm.html#7d0063f77d899ef22e8c5edd642176d2" title="access">mu</a> ( eno._mu() ) {<a class="code" href="classbdm_1_1mpdf.html#5eea43c56d38e4441bfb30270db949c0" title="pointer to internal epdf">ep</a>=&eno;};
634		<a name="l00902"></a><a class="code" href="classbdm_1_1mlognorm.html#604cab0e8a76f9041dc3c606043bb39f">00902</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 )
635		<a name="l00903"></a>00903 {
636		<a name="l00904"></a>00904 <a class="code" href="classbdm_1_1mlognorm.html#a51128a2e503b8b2ce698244b9e0db1a" title="parameter 1/2sigma^2">sig2</a> = 0.5log ( k*k+1 );
637		<a name="l00905"></a>00905 eno.<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 ) );
638		<a name="l00906"></a>00906
639		<a name="l00907"></a>00907 <a class="code" href="classbdm_1_1mpdf.html#7c1900976ff13dbc09c9729b3bbff9e6" title="dimension of the condition">dimc</a> = size;
640		<a name="l00908"></a>00908 };
641		<a name="l00909"></a>00909
642		<a name="l00910"></a><a class="code" href="classbdm_1_1mlognorm.html#9106d8fd8bdf2b6be675ffd8f3ca584e">00910</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1mlognorm.html#9106d8fd8bdf2b6be675ffd8f3ca584e" title="Update ep so that it represents this mpdf conditioned on rvc = cond.">condition</a> ( <span class="keyword">const</span> vec &val )
643		<a name="l00911"></a>00911 {
644		<a name="l00912"></a>00912 <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>
645		<a name="l00913"></a>00913 };
646		<a name="l00914"></a>00914
647		<a name="l00933"></a>00933 <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> );
648		<a name="l00934"></a>00934
649		<a name="l00935"></a>00935 <span class="comment">// TODO dodelat void to_setting( Setting &set ) const;</span>
650		<a name="l00936"></a>00936
651		<a name="l00937"></a>00937 };
652		<a name="l00938"></a>00938
653		<a name="l00939"></a>00939 <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);
654		<a name="l00940"></a>00940
655		<a name="l00944"></a><a class="code" href="classbdm_1_1eWishartCh.html">00944</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>
656		<a name="l00945"></a>00945 {
657		<a name="l00946"></a>00946 <span class="keyword">protected</span>:
658		<a name="l00948"></a><a class="code" href="classbdm_1_1eWishartCh.html#1b42f9284a32f23b0b253a628cda7490">00948</a> <a class="code" href="classchmat.html" title="Symmetric matrix stored in square root decomposition using upper cholesky.">chmat</a> <a class="code" href="classbdm_1_1eWishartCh.html#1b42f9284a32f23b0b253a628cda7490" title="Upper-Triagle of Choleski decomposition of .">Y</a>;
659		<a name="l00950"></a><a class="code" href="classbdm_1_1eWishartCh.html#b745c73faef785009484180582050a1f">00950</a> <span class="keywordtype">int</span> <a class="code" href="classbdm_1_1eWishartCh.html#b745c73faef785009484180582050a1f" title="dimension of matrix ">p</a>;
660		<a name="l00952"></a><a class="code" href="classbdm_1_1eWishartCh.html#1879a14d7d2bb05062523b189baa11c3">00952</a> <span class="keywordtype">double</span> <a class="code" href="classbdm_1_1eWishartCh.html#1879a14d7d2bb05062523b189baa11c3" title="degrees of freedom ">delta</a>;
661		<a name="l00953"></a>00953 <span class="keyword">public</span>:
662		<a name="l00954"></a>00954 <span class="keywordtype">void</span> set_parameters ( <span class="keyword">const</span> mat &Y0, <span class="keyword">const</span> <span class="keywordtype">double</span> delta0 ) {<a class="code" href="classbdm_1_1eWishartCh.html#1b42f9284a32f23b0b253a628cda7490" title="Upper-Triagle of Choleski decomposition of .">Y</a>=<a class="code" href="classchmat.html" title="Symmetric matrix stored in square root decomposition using upper cholesky.">chmat</a> ( Y0 );<a class="code" href="classbdm_1_1eWishartCh.html#1879a14d7d2bb05062523b189baa11c3" title="degrees of freedom ">delta</a>=delta0; <a class="code" href="classbdm_1_1eWishartCh.html#b745c73faef785009484180582050a1f" title="dimension of matrix ">p</a>=<a class="code" href="classbdm_1_1eWishartCh.html#1b42f9284a32f23b0b253a628cda7490" title="Upper-Triagle of Choleski decomposition of .">Y</a>.<a class="code" href="classsqmat.html#071e80ced9cc3b8cbb360fa7462eb646" title="Reimplementing common functions of mat: cols().">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>; }
663		<a name="l00955"></a>00955 mat sample_mat()<span class="keyword"> const</span>
664		<a name="l00956"></a>00956 <span class="keyword"> </span>{
665		<a name="l00957"></a>00957 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> );
666		<a name="l00958"></a>00958
667		<a name="l00959"></a>00959 <span class="comment">//sample diagonal</span>
668		<a name="l00960"></a>00960 <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++ )
669		<a name="l00961"></a>00961 {
670		<a name="l00962"></a>00962 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>
671		<a name="l00963"></a>00963 <span class="preprocessor">#pragma omp critical</span>
672		<a name="l00964"></a>00964 <span class="preprocessor"></span> X ( i,i ) =sqrt ( GamRNG() );
673		<a name="l00965"></a>00965 }
674		<a name="l00966"></a>00966 <span class="comment">//do the rest</span>
675		<a name="l00967"></a>00967 <span class="keywordflow">for</span> ( <span class="keywordtype">int</span> i=0;i<p;i++ )
676		<a name="l00968"></a>00968 {
677		<a name="l00969"></a>00969 <span class="keywordflow">for</span> ( <span class="keywordtype">int</span> j=i+1;j<p;j++ )
678		<a name="l00970"></a>00970 {
679		<a name="l00971"></a>00971 <span class="preprocessor">#pragma omp critical</span>
680		<a name="l00972"></a>00972 <span class="preprocessor"></span> X ( i,j ) =NorRNG.sample();
681		<a name="l00973"></a>00973 }
682		<a name="l00974"></a>00974 }
683		<a name="l00975"></a>00975 <span class="keywordflow">return</span> X*<a class="code" href="classbdm_1_1eWishartCh.html#1b42f9284a32f23b0b253a628cda7490" title="Upper-Triagle of Choleski decomposition of .">Y</a>.<a class="code" href="classchmat.html#9c50d31c999d85d8e9d8cf2b69b6ac8c" title="Access function.">_Ch</a>();<span class="comment">// return upper triangular part of the decomposition</span>
684		<a name="l00976"></a>00976 }
685		<a name="l00977"></a><a class="code" href="classbdm_1_1eWishartCh.html#8f2154b8b5be8f4c5788f261b6d57b9a">00977</a> vec <a class="code" href="classbdm_1_1eWishartCh.html#8f2154b8b5be8f4c5788f261b6d57b9a" title="Returns a sample, from density .">sample</a> ()<span class="keyword"> const</span>
686		<a name="l00978"></a>00978 <span class="keyword"> </span>{
687		<a name="l00979"></a>00979 <span class="keywordflow">return</span> vec ( sample_mat()._data(),p*p );
688		<a name="l00980"></a>00980 }
689		<a name="l00982"></a><a class="code" href="classbdm_1_1eWishartCh.html#4eee757c0535c2a88bb20f0767c64981">00982</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1eWishartCh.html#4eee757c0535c2a88bb20f0767c64981" title="fast access function y0 will be copied into Y.Ch.">setY</a> ( <span class="keyword">const</span> mat &Ch0 ) {copy_vector ( <a class="code" href="classbdm_1_1epdf.html#16adac20ec7fe07e1ea0b27d917788ce" title="dimension of the random variable">dim</a>,Ch0._data(), <a class="code" href="classbdm_1_1eWishartCh.html#1b42f9284a32f23b0b253a628cda7490" title="Upper-Triagle of Choleski decomposition of .">Y</a>.<a class="code" href="classchmat.html#9c50d31c999d85d8e9d8cf2b69b6ac8c" title="Access function.">_Ch</a>()._data() );}
690		<a name="l00984"></a><a class="code" href="classbdm_1_1eWishartCh.html#7eac414ec10b85aa5536b0092c57bc4a">00984</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1eWishartCh.html#7eac414ec10b85aa5536b0092c57bc4a" title="fast access function y0 will be copied into Y.Ch.">_setY</a> ( <span class="keyword">const</span> vec &ch0 ) {copy_vector ( <a class="code" href="classbdm_1_1epdf.html#16adac20ec7fe07e1ea0b27d917788ce" title="dimension of the random variable">dim</a>, ch0._data(), <a class="code" href="classbdm_1_1eWishartCh.html#1b42f9284a32f23b0b253a628cda7490" title="Upper-Triagle of Choleski decomposition of .">Y</a>.<a class="code" href="classchmat.html#9c50d31c999d85d8e9d8cf2b69b6ac8c" title="Access function.">_Ch</a>()._data() ); }
691		<a name="l00986"></a><a class="code" href="classbdm_1_1eWishartCh.html#1708cacb5d8cb1b96395d35f5327cb7e">00986</a> <span class="keyword">const</span> <a class="code" href="classchmat.html" title="Symmetric matrix stored in square root decomposition using upper cholesky.">chmat</a>& <a class="code" href="classbdm_1_1eWishartCh.html#1708cacb5d8cb1b96395d35f5327cb7e" title="access function">getY</a>()<span class="keyword">const </span>{<span class="keywordflow">return</span> <a class="code" href="classbdm_1_1eWishartCh.html#1b42f9284a32f23b0b253a628cda7490" title="Upper-Triagle of Choleski decomposition of .">Y</a>;}
692		<a name="l00987"></a>00987 };
693		<a name="l00988"></a>00988
694		<a name="l00989"></a>00989 <span class="keyword">class </span>eiWishartCh: <span class="keyword">public</span> epdf
695		<a name="l00990"></a>00990 {
696		<a name="l00991"></a>00991 <span class="keyword">protected</span>:
697		<a name="l00992"></a>00992 eWishartCh W;
698		<a name="l00993"></a>00993 <span class="keywordtype">int</span> p;
699		<a name="l00994"></a>00994 <span class="keywordtype">double</span> delta;
700		<a name="l00995"></a>00995 <span class="keyword">public</span>:
701		<a name="l00996"></a>00996 <span class="keywordtype">void</span> set_parameters ( <span class="keyword">const</span> mat &Y0, <span class="keyword">const</span> <span class="keywordtype">double</span> delta0) {
702		<a name="l00997"></a>00997 delta = delta0;
703		<a name="l00998"></a>00998 W.set_parameters ( inv ( Y0 ),delta0 );
704		<a name="l00999"></a>00999 dim = W.dimension(); p=Y0.rows();
705		<a name="l01000"></a>01000 }
706		<a name="l01001"></a>01001 vec sample()<span class="keyword"> const </span>{mat iCh; iCh=inv ( W.sample_mat() ); <span class="keywordflow">return</span> vec ( iCh._data(),<a class="code" href="classbdm_1_1epdf.html#16adac20ec7fe07e1ea0b27d917788ce" title="dimension of the random variable">dim</a> );}
707		<a name="l01002"></a>01002 <span class="keywordtype">void</span> _setY ( <span class="keyword">const</span> vec &y0 )
708		<a name="l01003"></a>01003 {
709		<a name="l01004"></a>01004 mat Ch ( p,p );
710		<a name="l01005"></a>01005 mat iCh ( p,p );
711		<a name="l01006"></a>01006 copy_vector ( dim, y0._data(), Ch._data() );
712		<a name="l01007"></a>01007
713		<a name="l01008"></a>01008 iCh=inv ( Ch );
714		<a name="l01009"></a>01009 W.setY ( iCh );
715		<a name="l01010"></a>01010 }
716		<a name="l01011"></a>01011 <span class="keyword">virtual</span> <span class="keywordtype">double</span> evallog ( <span class="keyword">const</span> vec &val )<span class="keyword"> const </span>{
717		<a name="l01012"></a>01012 <a class="code" href="classchmat.html" title="Symmetric matrix stored in square root decomposition using upper cholesky.">chmat</a> X(p);
718		<a name="l01013"></a>01013 <span class="keyword">const</span> <a class="code" href="classchmat.html" title="Symmetric matrix stored in square root decomposition using upper cholesky.">chmat</a>& Y=W.getY();
719		<a name="l01014"></a>01014
720		<a name="l01015"></a>01015 copy_vector(p*p,val._data(),X._Ch()._data());
721		<a name="l01016"></a>01016 <a class="code" href="classchmat.html" title="Symmetric matrix stored in square root decomposition using upper cholesky.">chmat</a> iX(p);X.inv(iX);
722		<a name="l01017"></a>01017 <span class="comment">// compute </span>
723		<a name="l01018"></a>01018 <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>
724		<a name="l01019"></a>01019 mat M=Y.<a class="code" href="classchmat.html#045addd685f8d978efda232d7dcb070e" title="Conversion to full matrix.">to_mat</a>()*iX.to_mat();
725		<a name="l01020"></a>01020
726		<a name="l01021"></a>01021 <span class="keywordtype">double</span> log1 = 0.5p(2Y.<a class="code" href="classchmat.html#b504ca818203b13e667cb3c503980382" title="Logarithm of a determinant.">logdet</a>())-0.5(delta+p+1)(2X.logdet())-0.5*trace(M);
727		<a name="l01022"></a>01022 <span class="comment">//Fixme! Multivariate gamma omitted!! it is ok for sampling, but not otherwise!!</span>
728		<a name="l01023"></a>01023
729		<a name="l01024"></a>01024 <span class="comment">/* if (0) {</span>
730		<a name="l01025"></a>01025 <span class="comment"> mat XX=X.to_mat();</span>
731		<a name="l01026"></a>01026 <span class="comment"> mat YY=Y.to_mat();</span>
732		<a name="l01027"></a>01027 <span class="comment"> </span>
733		<a name="l01028"></a>01028 <span class="comment"> double log2 = 0.5plog(det(YY))-0.5(delta+p+1)log(det(XX))-0.5trace(YYinv(XX)); </span>
734		<a name="l01029"></a>01029 <span class="comment"> cout << log1 << "," << log2 << endl;</span>
735		<a name="l01030"></a>01030 <span class="comment"> }*/</span>
736		<a name="l01031"></a>01031 <span class="keywordflow">return</span> log1;
737		<a name="l01032"></a>01032 };
738		<a name="l01033"></a>01033
739		<a name="l01034"></a>01034 };
740		<a name="l01035"></a>01035
741		<a name="l01036"></a>01036 <span class="keyword">class </span>rwiWishartCh : <span class="keyword">public</span> mpdf
742		<a name="l01037"></a>01037 {
743		<a name="l01038"></a>01038 <span class="keyword">protected</span>:
744		<a name="l01039"></a>01039 eiWishartCh eiW;
745		<a name="l01041"></a>01041 <span class="keywordtype">double</span> sqd;
746		<a name="l01042"></a>01042 <span class="comment">//reference point for diagonal</span>
747		<a name="l01043"></a>01043 vec refl;
748		<a name="l01044"></a>01044 <span class="keywordtype">double</span> l;
749		<a name="l01045"></a>01045 <span class="keywordtype">int</span> p;
750		<a name="l01046"></a>01046 <span class="keyword">public</span>:
751		<a name="l01047"></a>01047 <span class="keywordtype">void</span> set_parameters ( <span class="keywordtype">int</span> p0, <span class="keywordtype">double</span> k, vec ref0, <span class="keywordtype">double</span> l0 )
752		<a name="l01048"></a>01048 {
753		<a name="l01049"></a>01049 p=p0;
754		<a name="l01050"></a>01050 <span class="keywordtype">double</span> delta = 2/(k*k)+p+3;
755		<a name="l01051"></a>01051 sqd=sqrt ( delta-p-1 );
756		<a name="l01052"></a>01052 l=l0;
757		<a name="l01053"></a>01053 refl=pow(ref0,1-l);
758		<a name="l01054"></a>01054
759		<a name="l01055"></a>01055 eiW.set_parameters ( eye ( p ),delta );
760		<a name="l01056"></a>01056 <a class="code" href="classbdm_1_1mpdf.html#5eea43c56d38e4441bfb30270db949c0" title="pointer to internal epdf">ep</a>=&eiW;
761		<a name="l01057"></a>01057 <a class="code" href="classbdm_1_1mpdf.html#7c1900976ff13dbc09c9729b3bbff9e6" title="dimension of the condition">dimc</a>=eiW.dimension();
762		<a name="l01058"></a>01058 }
763		<a name="l01059"></a>01059 <span class="keywordtype">void</span> condition ( <span class="keyword">const</span> vec &c ) {
764		<a name="l01060"></a>01060 vec z=c;
765		<a name="l01061"></a>01061 <span class="keywordtype">int</span> ri=0;
766		<a name="l01062"></a>01062 <span class="keywordflow">for</span>(<span class="keywordtype">int</span> i=0;i<p*p;i+=(p+1)){<span class="comment">//trace diagonal element</span>
767		<a name="l01063"></a>01063 z(i) = pow(z(i),l)*refl(ri);
768		<a name="l01064"></a>01064 ri++;
769		<a name="l01065"></a>01065 }
770		<a name="l01066"></a>01066
771		<a name="l01067"></a>01067 eiW._setY ( sqd*z );
772		<a name="l01068"></a>01068 }
773		<a name="l01069"></a>01069 };
774		<a name="l01070"></a>01070
775		<a name="l01072"></a>01072 <span class="keyword">enum</span> RESAMPLING_METHOD { MULTINOMIAL = 0, STRATIFIED = 1, SYSTEMATIC = 3 };
776		<a name="l01078"></a><a class="code" href="classbdm_1_1eEmp.html">01078</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>
777		<a name="l01079"></a>01079 {
778		<a name="l01080"></a>01080 <span class="keyword">protected</span> :
779		<a name="l01082"></a><a class="code" href="classbdm_1_1eEmp.html#9798006271ca77629855113f1283a031">01082</a> <span class="keywordtype">int</span> <a class="code" href="classbdm_1_1eEmp.html#9798006271ca77629855113f1283a031" title="Number of particles.">n</a>;
780		<a name="l01084"></a><a class="code" href="classbdm_1_1eEmp.html#9d39241aab7c4bbeb07c6d516421c67d">01084</a> vec <a class="code" href="classbdm_1_1eEmp.html#9d39241aab7c4bbeb07c6d516421c67d" title="Sample weights .">w</a>;
781		<a name="l01086"></a><a class="code" href="classbdm_1_1eEmp.html#73d819553a0f268b055a087d2d4486f3">01086</a> Array<vec> <a class="code" href="classbdm_1_1eEmp.html#73d819553a0f268b055a087d2d4486f3" title="Samples .">samples</a>;
782		<a name="l01087"></a>01087 <span class="keyword">public</span>:
783		<a name="l01090"></a>01090 <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> ( ) {};
784		<a name="l01092"></a><a class="code" href="classbdm_1_1eEmp.html#a3daf6363455af099921715e1233c076">01092</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> ) {};
785		<a name="l01094"></a>01094
786		<a name="l01096"></a>01096 <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1eEmp.html#7cfd383180b486fe4526bdf0179350c0" title="Set samples and weights.">set_statistics</a> ( <span class="keyword">const</span> vec &w0, <span class="keyword">const</span> <a class="code" href="classbdm_1_1epdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a>* pdf0 );
787		<a name="l01098"></a><a class="code" href="classbdm_1_1eEmp.html#cef74aa5f87d10d440b9b1e8bc78c1e7">01098</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1eEmp.html#cef74aa5f87d10d440b9b1e8bc78c1e7" title="Set samples and weights.">set_statistics</a> ( <span class="keyword">const</span> <a class="code" href="classbdm_1_1epdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a>* pdf0 , <span class="keywordtype">int</span> <a class="code" href="classbdm_1_1eEmp.html#9798006271ca77629855113f1283a031" title="Number of particles.">n</a> ) {<a class="code" href="classbdm_1_1eEmp.html#cef74aa5f87d10d440b9b1e8bc78c1e7" title="Set samples and weights.">set_statistics</a> ( ones ( n ) /n,pdf0 );};
788		<a name="l01100"></a>01100 <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 );
789		<a name="l01102"></a><a class="code" href="classbdm_1_1eEmp.html#c74c281d652356c19b6b079e42ca7ef1">01102</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 );};
790		<a name="l01104"></a><a class="code" href="classbdm_1_1eEmp.html#d7f83cc0415cd44ae7cc8b4bdad93aef">01104</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>;};
791		<a name="l01106"></a><a class="code" href="classbdm_1_1eEmp.html#b7d7106f486e3fad38590914a693d714">01106</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>;};
792		<a name="l01108"></a><a class="code" href="classbdm_1_1eEmp.html#c24966b0aaeb767bc8a6b4fd60931be2">01108</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>;};
793		<a name="l01110"></a><a class="code" href="classbdm_1_1eEmp.html#b59af0efdb009d98ea8ebfa965e74ae2">01110</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>;};
794		<a name="l01112"></a>01112 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 );
795		<a name="l01114"></a><a class="code" href="classbdm_1_1eEmp.html#97f1e07b5ae6eebc91c7365f0f88d270">01114</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;}
796		<a name="l01116"></a><a class="code" href="classbdm_1_1eEmp.html#01654c014d3aa068f8d4ecba4be86d09">01116</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;}
797		<a name="l01117"></a><a class="code" href="classbdm_1_1eEmp.html#bbfcb4f868c7381298c281a256d8c4b9">01117</a> vec <a class="code" href="classbdm_1_1eEmp.html#bbfcb4f868c7381298c281a256d8c4b9" title="return expected value">mean</a>()<span class="keyword"> const</span>
798		<a name="l01118"></a>01118 <span class="keyword"> </span>{
799		<a name="l01119"></a>01119 vec pom=zeros ( <a class="code" href="classbdm_1_1epdf.html#16adac20ec7fe07e1ea0b27d917788ce" title="dimension of the random variable">dim</a> );
800		<a name="l01120"></a>01120 <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 );}
801		<a name="l01121"></a>01121 <span class="keywordflow">return</span> pom;
802		<a name="l01122"></a>01122 }
803		<a name="l01123"></a><a class="code" href="classbdm_1_1eEmp.html#05e9ebf467ede737cb6a3621d7fd3c87">01123</a> vec <a class="code" href="classbdm_1_1eEmp.html#05e9ebf467ede737cb6a3621d7fd3c87" title="return expected variance (not covariance!)">variance</a>()<span class="keyword"> const</span>
804		<a name="l01124"></a>01124 <span class="keyword"> </span>{
805		<a name="l01125"></a>01125 vec pom=zeros ( <a class="code" href="classbdm_1_1epdf.html#16adac20ec7fe07e1ea0b27d917788ce" title="dimension of the random variable">dim</a> );
806		<a name="l01126"></a>01126 <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 );}
807		<a name="l01127"></a>01127 <span class="keywordflow">return</span> pom-pow ( <a class="code" href="classbdm_1_1eEmp.html#bbfcb4f868c7381298c281a256d8c4b9" title="return expected value">mean</a>(),2 );
808		<a name="l01128"></a>01128 }
809		<a name="l01130"></a><a class="code" href="classbdm_1_1eEmp.html#b1c9df656144edf79ba2d885613f661f">01130</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>
810		<a name="l01131"></a>01131 <span class="keyword"> </span>{
811		<a name="l01132"></a>01132 <span class="comment">// lb in inf so than it will be pushed below;</span>
812		<a name="l01133"></a>01133 lb.set_size ( <a class="code" href="classbdm_1_1epdf.html#16adac20ec7fe07e1ea0b27d917788ce" title="dimension of the random variable">dim</a> );
813		<a name="l01134"></a>01134 ub.set_size ( <a class="code" href="classbdm_1_1epdf.html#16adac20ec7fe07e1ea0b27d917788ce" title="dimension of the random variable">dim</a> );
814		<a name="l01135"></a>01135 lb = std::numeric_limits<double>::infinity();
815		<a name="l01136"></a>01136 ub = -std::numeric_limits<double>::infinity();
816		<a name="l01137"></a>01137 <span class="keywordtype">int</span> j;
817		<a name="l01138"></a>01138 <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++ )
818		<a name="l01139"></a>01139 {
819		<a name="l01140"></a>01140 <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++ )
820		<a name="l01141"></a>01141 {
821		<a name="l01142"></a>01142 <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 );}
822		<a name="l01143"></a>01143 <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 );}
823		<a name="l01144"></a>01144 }
824		<a name="l01145"></a>01145 }
825		<a name="l01146"></a>01146 }
826		<a name="l01147"></a>01147 };
827		<a name="l01148"></a>01148
828		<a name="l01149"></a>01149
829		<a name="l01151"></a>01151
830		<a name="l01152"></a>01152 <span class="keyword">template</span><<span class="keyword">class</span> sq_T>
831		<a name="l01153"></a>01153 <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 )
832		<a name="l01154"></a>01154 {
833		<a name="l01155"></a>01155 <span class="comment">//Fixme test dimensions of mu0 and R0;</span>
834		<a name="l01156"></a>01156 mu = mu0;
835		<a name="l01157"></a>01157 R = R0;
836		<a name="l01158"></a>01158 <a class="code" href="classbdm_1_1root.html#1c314bd6d6dacb8ba78ea5eb88fd9516" title="This method TODO.">validate</a>();
837		<a name="l01159"></a>01159 };
838		<a name="l01160"></a>01160
839		<a name="l01161"></a>01161 <span class="keyword">template</span><<span class="keyword">class</span> sq_T>
840		<a name="l01162"></a><a class="code" href="classbdm_1_1enorm.html#61bd470764020bea6e1ed35000f259e6">01162</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>){
841		<a name="l01163"></a>01163 <a class="code" href="classbdm_1_1enorm.html#61bd470764020bea6e1ed35000f259e6">epdf::from_setting</a>(<span class="keyword">set</span>); <span class="comment">//reads rv</span>
842		<a name="l01164"></a>01164
843		<a name="l01165"></a>01165 <a class="code" href="classbdm_1_1UI.html#652bfd23f5052e4f1cb317057d74a3e2" title="The existing instance of type T is initialized with values stored in the Setting...">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>);
844		<a name="l01166"></a>01166 mat Rtmp;<span class="comment">// necessary for conversion</span>
845		<a name="l01167"></a>01167 <a class="code" href="classbdm_1_1UI.html#652bfd23f5052e4f1cb317057d74a3e2" title="The existing instance of type T is initialized with values stored in the Setting...">UI::get</a>(Rtmp,<span class="keyword">set</span>,<span class="stringliteral">"R"</span>);
846		<a name="l01168"></a>01168 <a class="code" href="classbdm_1_1enorm.html#2d92dde696b2a7a5b10ddef5d22ba2c2" title="Covariance matrix in decomposed form.">R</a>=Rtmp; <span class="comment">// conversion</span>
847		<a name="l01169"></a>01169 <a class="code" href="classbdm_1_1enorm.html#38eb17ecb75d94a50b6782fcf735cfea" title="This method TODO.">validate</a>();
848		<a name="l01170"></a>01170 }
	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
849	836	<a name="l01171"></a>01171
850		<a name="l01172"></a>01172 <span class="keyword">template</span><<span class="keyword">class</span> sq_T>
851		<a name="l01173"></a><a class="code" href="classbdm_1_1enorm.html#d2e0d3a1e30ab3ab04df2d0c43ae74a2">01173</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 )
852		<a name="l01174"></a>01174 {
853		<a name="l01175"></a>01175 <span class="comment">//</span>
854		<a name="l01176"></a>01176 };
855		<a name="l01177"></a>01177
856		<a name="l01178"></a>01178 <span class="comment">// template<class sq_T></span>
857		<a name="l01179"></a>01179 <span class="comment">// void enorm<sq_T>::tupdate ( double phi, mat &vbar, double nubar ) {</span>
858		<a name="l01180"></a>01180 <span class="comment">// //</span>
859		<a name="l01181"></a>01181 <span class="comment">// };</span>
	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 };
860	846	<a name="l01182"></a>01182
861		<a name="l01183"></a>01183 <span class="keyword">template</span><<span class="keyword">class</span> sq_T>
862		<a name="l01184"></a><a class="code" href="classbdm_1_1enorm.html#e1a48f52351ec3a349bd443b713b1766">01184</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>
863		<a name="l01185"></a>01185 ~~<span class="keyword"> </span>~~{
864		<a name="l01186"></a>01186 ~~vec x ( <a class="code" href="classbdm_1_1epdf.html#16adac20ec7fe07e1ea0b27d917788ce" title="dimension of the random variable">dim</a> );~~
865		<a name="l01187"></a>01187 ~~<span class="preprocessor">#pragma omp critical</span>~~
866		<a name="l01188"></a>01188 <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 );
867		<a name="l01189"></a>01189 ~~vec smp = <a class="code" href="classbdm_1_1enorm.html#2d92dde696b2a7a5b10ddef5d22ba2c2" title="Covariance matrix in decomposed form.">R</a>.sqrt_mult ( x );~~
868		<a name="l01190"></a>01190
869		<a name="l01191"></a>01191 ~~smp += <a class="code" href="classbdm_1_1enorm.html#c702a194720853570d08b65482f842c7" title="mean value">mu</a>;~~
870		<a name="l01192"></a>01192 ~~<span class="keywordflow">return</span> smp~~;
871		<a name="l01193"></a>01193 };
	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 }
872	858	<a name="l01194"></a>01194
873		<a name="l01195"></a>01195 <span class="keyword">template</span><<span class="keyword">class</span> sq_T>
874		<a name="l01196"></a>01196 mat <a class="code" href="classbdm_1_1enorm.html#e1a48f52351ec3a349bd443b713b1766" title="Returns a sample, from density .">enorm<sq_T>::sample</a> ( <span class="keywordtype">int</span> N )<span class="keyword"> const</span>
875		<a name="l01197"></a>01197 ~~<span class="keyword"> </span>~~{
876		<a name="l01198"></a>01198 ~~mat X ( <a class="code" href="classbdm_1_1epdf.html#16adac20ec7fe07e1ea0b27d917788ce" title="dimension of the random variable">dim</a>,N );~~
877		<a name="l01199"></a>01199 ~~vec x ( <a class="code" href="classbdm_1_1epdf.html#16adac20ec7fe07e1ea0b27d917788ce" title="dimension of the random variable">dim</a> )~~;
878		<a name="l01200"></a>01200 ~~vec pom;~~
879		<a name="l01201"></a>01201 ~~<span class="keywordtype">int</span> i;~~
880		<a name="l01202"></a>01202
881		<a name="l01203"></a>01203 ~~<span class="keywordflow">for</span> ( i=0;i<N;i++ )~~
882		<a name="l01204"></a>01204 {
883		<a name="l01205"></a>01205 ~~<span class="preprocessor">#pragma omp critical</span>~~
884		<a name="l01206"></a>01206 <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 );
885		<a name="l01207"></a>~~01207 pom = <a class="code" href="classbdm_1_1enorm.html#2d92dde696b2a7a5b10ddef5d22ba2c2" title="Covariance matrix in decomposed form.">R</a>.sqrt_mult ( x );~~
886		<a name="l01208"></a>01208 ~~pom +=<a class="code" href="classbdm_1_1enorm.html#c702a194720853570d08b65482f842c7" title="mean value">mu</a>;~~
887		<a name="l01209"></a>01209 ~~X.set_col ( i, pom~~ );
888		<a name="l01210"></a>01210 }
889		<a name="l01211"></a>01211
890		<a name="l01212"></a>01212 ~~<span class="keywordflow">return</span> X~~;
891		<a name="l01213"></a>01213 };
892		<a name="l01214"></a>01214
893		<a name="l01215"></a>01215 ~~<span class="comment">// template<class sq_T></span>~~
894		<a name="l01216"></a>01216 ~~<span class="comment">// double enorm<sq_T>::eval ( const vec &val ) const {</span>~~
895		<a name="l01217"></a>01217 ~~<span class="comment">// double pdfl,e;</span>~~
896		<a name="l01218"></a>01218 <span class="comment">// ~~pdfl = evallog ( val )~~;</span>
897		<a name="l01219"></a>01219 <span class="comment">// ~~e = exp ( pdfl );~~</span>
898		<a name="l01220"></a>01220 <span class="comment">// ~~return~~ e;</span>
899		<a name="l01221"></a>01221 <span class="comment">// };</span>
900		<a name="l01222"></a>01222
901		<a name="l01223"></a>01223 ~~<span class="keyword">template</span><<span class="keyword">class</span> sq_T>~~
902		<a name="l01224"></a><a class="code" href="classbdm_1_1enorm.html#e13aeed5b543b2179bacdc4fa2ae47a3">01224</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>
903		<a name="l01225"></a>01225 ~~<span class="keyword"> </span>{~~
904		<a name="l01226"></a>01226 ~~<span class="comment">// 1.83787706640935 = log(2pi)</span>~~
905		<a name="l01227"></a>01227 <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>
906		<a name="l01228"></a>01228 ~~<span class="keywordflow">return</span> tmp;~~
907		<a name="l01229"></a>01229 };
908		<a name="l01230"></a>01230
909		<a name="l01231"></a>01231 <span class="keyword~~">template</span><<span class="keyword">class</span> sq_T&gt~~;
910		<a name="l01232"></a><a class="code" href="classbdm_1_1enorm.html#25785343aff102cc5df1cab08ba16d32">01232</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>
911		<a name="l01233"></a>01233 ~~<span class="keyword"> </span>{~~
912		<a name="l01234"></a>01234 ~~<span class="comment">// 1.83787706640935 = log(2pi)</span>~~
913		<a name="l01235"></a>01235 <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() );
914		<a name="l01236"></a>01236 ~~<span class="keywordflow">return</span> tmp;~~
915		<a name="l01237"></a>01237 };
916		<a name="l01238"></a>01238
917		<a name="l01239"></a>01239 <span class="keyword~~">template</span><<span class="keyword">class</span> sq_T&gt~~;
918		<a name="l01240"></a><a class="code" href="classbdm_1_1mlnorm.html#5d18dec3167584338a4775c1d165d96f">01240</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1mlnorm.html#5d18dec3167584338a4775c1d165d96f" title="Set A and R.">mlnorm<sq_T>::set_parameters</a> ( <span class="keyword">const</span> mat &A0, <span class="keyword">const</span> vec &mu0, <span class="keyword">const</span> sq_T &R0 )
919		<a name="l01241"></a>01241 {
920		<a name="l01242"></a>01242 ~~it_assert_debug ( A0.rows() ==mu0.length(),<span class="stringliteral">""</span> );~~
921		<a name="l01243"></a>01243 ~~it_assert_debug ( A0.rows() ==R0.rows(),<span class="stringliteral">""</span> );~~
922		<a name="l01244"></a>01244
923		<a name="l01245"></a>01245 ~~<a class="code" href="classbdm_1_1epdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a>.set_parameters ( zeros ( A0.rows() ),R0 );~~
924		<a name="l01246"></a>01246 ~~A = A0;~~
925		<a name="l01247"></a>01247 ~~mu_const = mu0;~~
926		<a name="l01248"></a>01248 ~~<a class="code" href="classbdm_1_1mpdf.html#7c1900976ff13dbc09c9729b3bbff9e6" title="dimension of the condition">dimc</a>=A0.cols();~~
927		<a name="l01249"></a>01249 }
	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>
928	914	<a name="l01250"></a>01250
929	915	<a name="l01251"></a>01251 <span class="comment">// template<class sq_T></span>
930		<a name="l01252"></a>01252 <span class="comment">// vec mlnorm<sq_T>::samplecond (const vec &cond, double &lik ) {</span>
931		<a name="l01253"></a>01253 <span class="comment">// this->condition ( cond );</span>
932		<a name="l01254"></a>01254 <span class="comment">// vec smp = epdf.sample();</span>
933		<a name="l01255"></a>01255 <span class="comment">// lik = epdf.eval ( smp );</span>
934		<a name="l01256"></a>01256 <span class="comment">// return smp;</span>
935		<a name="l01257"></a>01257 <span class="comment">// }</span>
936		<a name="l01258"></a>01258
937		<a name="l01259"></a>01259 <span class="comment">// template<class sq_T></span>
938		<a name="l01260"></a>01260 <span class="comment">// mat mlnorm<sq_T>::samplecond (const vec &cond, vec &lik, int n ) {</span>
939		<a name="l01261"></a>01261 <span class="comment">// int i;</span>
940		<a name="l01262"></a>01262 <span class="comment">// int dim = rv.count();</span>
941		<a name="l01263"></a>01263 <span class="comment">// mat Smp ( dim,n );</span>
942		<a name="l01264"></a>01264 <span class="comment">// vec smp ( dim );</span>
943		<a name="l01265"></a>01265 <span class="comment">// this->condition ( cond );</span>
944		<a name="l01266"></a>01266 <span class="comment">//</span>
945		<a name="l01267"></a>01267 <span class="comment">// for ( i=0; i<n; i++ ) {</span>
946		<a name="l01268"></a>01268 <span class="comment">// smp = epdf.sample();</span>
947		<a name="l01269"></a>01269 <span class="comment">// lik ( i ) = epdf.eval ( smp );</span>
948		<a name="l01270"></a>01270 <span class="comment">// Smp.set_col ( i ,smp );</span>
949		<a name="l01271"></a>01271 <span class="comment">// }</span>
950		<a name="l01272"></a>01272 <span class="comment">//</span>
951		<a name="l01273"></a>01273 <span class="comment">// return Smp;</span>
952		<a name="l01274"></a>01274 <span class="comment">// }</span>
953		<a name="l01275"></a>01275
954		<a name="l01276"></a>01276 <span class="keyword">template</span><<span class="keyword">class</span> sq_T>
955		<a name="l01277"></a><a class="code" href="classbdm_1_1mlnorm.html#0dafc0196e7e07fd06dc6716e0e18bc2">01277</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1mlnorm.html#0dafc0196e7e07fd06dc6716e0e18bc2">mlnorm<sq_T>::condition</a> ( <span class="keyword">const</span> vec &cond )
956		<a name="l01278"></a>01278 {
957		<a name="l01279"></a>01279 _mu = A*cond + mu_const;
958		<a name="l01280"></a>01280 <span class="comment">//R is already assigned;</span>
959		<a name="l01281"></a>01281 }
960		<a name="l01282"></a>01282
961		<a name="l01283"></a>01283 <span class="keyword">template</span><<span class="keyword">class</span> sq_T>
962		<a name="l01284"></a><a class="code" href="classbdm_1_1enorm.html#c2996bdaffad38fbe0fc776db54c9d80">01284</a> <a class="code" href="classbdm_1_1enorm.html" title="Gaussian density with positive definite (decomposed) covariance matrix.">enorm<sq_T></a>* <a class="code" href="classbdm_1_1enorm.html#c2996bdaffad38fbe0fc776db54c9d80" title="Return marginal density on the given RV, the remainig rvs are intergrated out.">enorm<sq_T>::marginal</a> ( <span class="keyword">const</span> <a class="code" href="classbdm_1_1RV.html" title="Class representing variables, most often random variables.">RV</a> &rvn )<span class="keyword"> const</span>
963		<a name="l01285"></a>01285 <span class="keyword"> </span>{
964		<a name="l01286"></a>01286 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> );
965		<a name="l01287"></a>01287 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> );
966		<a name="l01288"></a>01288
967		<a name="l01289"></a>01289 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>
968		<a name="l01290"></a>01290
969		<a name="l01291"></a>01291 <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>;
970		<a name="l01292"></a>01292 tmp-><a class="code" href="classbdm_1_1epdf.html#f423e28448dbb69ef4905295ec8de8ff" title="Name its rv.">set_rv</a> ( rvn );
971		<a name="l01293"></a>01293 tmp-><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 );
972		<a name="l01294"></a>01294 <span class="keywordflow">return</span> tmp;
973		<a name="l01295"></a>01295 }
974		<a name="l01296"></a>01296
975		<a name="l01297"></a>01297 <span class="keyword">template</span><<span class="keyword">class</span> sq_T>
976		<a name="l01298"></a><a class="code" href="classbdm_1_1enorm.html#baea4d49c657342b58297d68cda16d26">01298</a> <a class="code" href="classbdm_1_1mpdf.html" title="Conditional probability density, e.g. modeling some dependencies.">mpdf</a>* <a class="code" href="classbdm_1_1enorm.html#baea4d49c657342b58297d68cda16d26" title="Return conditional density on the given RV, the remaining rvs will be in conditioning...">enorm<sq_T>::condition</a> ( <span class="keyword">const</span> <a class="code" href="classbdm_1_1RV.html" title="Class representing variables, most often random variables.">RV</a> &rvn )<span class="keyword"> const</span>
977		<a name="l01299"></a>01299 <span class="keyword"> </span>{
978		<a name="l01300"></a>01300
979		<a name="l01301"></a>01301 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> );
980		<a name="l01302"></a>01302
981		<a name="l01303"></a>01303 <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 );
982		<a name="l01304"></a>01304 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> );
983		<a name="l01305"></a>01305 <span class="comment">//Permutation vector of the new R</span>
984		<a name="l01306"></a>01306 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> );
985		<a name="l01307"></a>01307 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> );
986		<a name="l01308"></a>01308 ivec perm=concat ( irvn , irvc );
987		<a name="l01309"></a>01309 sq_T Rn ( <a class="code" href="classbdm_1_1enorm.html#2d92dde696b2a7a5b10ddef5d22ba2c2" title="Covariance matrix in decomposed form.">R</a>,perm );
988		<a name="l01310"></a>01310
989		<a name="l01311"></a>01311 <span class="comment">//fixme - could this be done in general for all sq_T?</span>
990		<a name="l01312"></a>01312 mat S=Rn.to_mat();
991		<a name="l01313"></a>01313 <span class="comment">//fixme</span>
992		<a name="l01314"></a>01314 <span class="keywordtype">int</span> n=rvn.<a class="code" href="classbdm_1_1RV.html#de30156104f61d86c94f758861418089">_dsize</a>()-1;
993		<a name="l01315"></a>01315 <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;
994		<a name="l01316"></a>01316 mat S11 = S.get ( 0,n, 0, n );
995		<a name="l01317"></a>01317 mat S12 = S.get ( 0, n , rvn.<a class="code" href="classbdm_1_1RV.html#de30156104f61d86c94f758861418089">_dsize</a>(), end );
996		<a name="l01318"></a>01318 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 );
997		<a name="l01319"></a>01319
998		<a name="l01320"></a>01320 vec mu1 = <a class="code" href="classbdm_1_1enorm.html#c702a194720853570d08b65482f842c7" title="mean value">mu</a> ( irvn );
999		<a name="l01321"></a>01321 vec mu2 = <a class="code" href="classbdm_1_1enorm.html#c702a194720853570d08b65482f842c7" title="mean value">mu</a> ( irvc );
1000		<a name="l01322"></a>01322 mat A=S12*inv ( S22 );
1001		<a name="l01323"></a>01323 sq_T R_n ( S11 - A *S12.T() );
1002		<a name="l01324"></a>01324
1003		<a name="l01325"></a>01325 <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> ( );
1004		<a name="l01326"></a>01326 tmp->set_rv ( rvn ); tmp->set_rvc ( rvc );
1005		<a name="l01327"></a>01327 tmp->set_parameters ( A,mu1-A*mu2,R_n );
1006		<a name="l01328"></a>01328 <span class="keywordflow">return</span> tmp;
1007		<a name="l01329"></a>01329 }
1008		<a name="l01330"></a>01330
1009		<a name="l01332"></a>01332
1010		<a name="l01333"></a>01333 <span class="keyword">template</span><<span class="keyword">class</span> sq_T>
1011		<a name="l01334"></a>01334 std::ostream &operator<< ( std::ostream &os, mlnorm<sq_T> &ml )
1012		<a name="l01335"></a>01335 {
1013		<a name="l01336"></a>01336 os << <span class="stringliteral">"A:"</span><< ml.A<<endl;
1014		<a name="l01337"></a>01337 os << <span class="stringliteral">"mu:"</span><< ml.mu_const<<endl;
1015		<a name="l01338"></a>01338 os << <span class="stringliteral">"R:"</span> << ml.epdf._R().to_mat() <<endl;
1016		<a name="l01339"></a>01339 <span class="keywordflow">return</span> os;
1017		<a name="l01340"></a>01340 };
	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 }
1018	1003	<a name="l01341"></a>01341
1019		<a name="l01342"></a>01342 }
1020		<a name="l01343"></a>01343 <span class="preprocessor">#endif //EF_H</span>
	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>
1021	1018	</pre></div></div>
1022		<hr size="1"><address style="text-align: right;"><small>Generated on ~~Wed Jul 1 13:05:55~~ 2009 for mixpp by
	1019	<hr size="1"><address style="text-align: right;"><small>Generated on Sun Aug 16 17:58:18 2009 for mixpp by
1023	1020	<a href="http://www.doxygen.org/index.html">
1024	1021	<img src="doxygen.png" alt="doxygen" align="middle" border="0"></a> 1.5.8 </small></address>

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