Changeset 590 for library/doc/html/exp__family_8h-source.html

Timestamp:

08/29/09 20:54:10 (15 years ago)

Author:

smidl

Message:

doc

Files:

• library/doc/html/exp__family_8h-source.html (modified) (1 diff)

library/doc/html/exp__family_8h-source.html

@@ -85 +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> () {};
 <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;
-<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 &amp;val)<span class="keyword"> const</span>{it_error (<span class="stringliteral">"Not implemented"</span>);<span class="keywordflow">return</span> 0.0;};
-<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 &amp;val)<span class="keyword"> const </span>{
-<a name="l00050"></a>00050                         <span class="keywordtype">double</span> tmp;
-<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>();
-<a name="l00052"></a>00052 <span class="comment">//                              it_assert_debug ( std::isfinite ( tmp ),"Infinite value" );</span>
-<a name="l00053"></a>00053                         <span class="keywordflow">return</span> tmp;
-<a name="l00054"></a>00054                 }
-<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 &amp;Val)<span class="keyword"> const </span>{
-<a name="l00057"></a>00057                         vec x (Val.cols());
-<a name="l00058"></a>00058                         <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0;i &lt; 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)) ;}
-<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>();
-<a name="l00060"></a>00060                 }
-<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&lt;vec&gt; &amp;Val)<span class="keyword"> const </span>{
-<a name="l00063"></a>00063                         vec x (Val.length());
-<a name="l00064"></a>00064                         <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0;i &lt; Val.length();i++) {x (i) = <a class="code" href="classbdm_1_1eEF.html#a4135778ecd9ab774762936c82a097c6" title="Evaluate normalized log-probability.">evallog_nn</a> (Val (i)) ;}
-<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>();
-<a name="l00066"></a>00066                 }
-<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>);};
-<a name="l00069"></a>00069 };
-<a name="l00070"></a>00070 
+<a name="l00046"></a>00046 
+<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 &amp;val)<span class="keyword"> const </span>{
+<a name="l00049"></a>00049                         <a class="code" href="bdmerror_8h.html#7c43f3a72afe68ab0c85663a1bb3521a" title="Unconditionally throw std::runtime_error.">bdm_error</a> (<span class="stringliteral">"Not implemented"</span>);
+<a name="l00050"></a>00050                         <span class="keywordflow">return</span> 0.0;
+<a name="l00051"></a>00051                 }
+<a name="l00052"></a>00052 
+<a name="l00054"></a><a class="code" href="classbdm_1_1eEF.html#a36d06ecdd6f4c79dc122510eaccc692">00054</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 &amp;val)<span class="keyword"> const </span>{
+<a name="l00055"></a>00055                         <span class="keywordtype">double</span> tmp;
+<a name="l00056"></a>00056                         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>();
+<a name="l00057"></a>00057                         <span class="keywordflow">return</span> tmp;
+<a name="l00058"></a>00058                 }
+<a name="l00060"></a><a class="code" href="classbdm_1_1eEF.html#6886c60b6b690e503913240db5de0c6f">00060</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 &amp;Val)<span class="keyword"> const </span>{
+<a name="l00061"></a>00061                         vec x (Val.cols());
+<a name="l00062"></a>00062                         <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0;i &lt; 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)) ;}
+<a name="l00063"></a>00063                         <span class="keywordflow">return</span> x -<a class="code" href="classbdm_1_1eEF.html#cd678fc9b02007a4b8d6692e746f1bf8" title="logarithm of the normalizing constant, ">lognc</a>();
+<a name="l00064"></a>00064                 }
+<a name="l00066"></a><a class="code" href="classbdm_1_1eEF.html#d793f4fd6d0dcec5f16bff0ae45fc7d5">00066</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&lt;vec&gt; &amp;Val)<span class="keyword"> const </span>{
+<a name="l00067"></a>00067                         vec x (Val.length());
+<a name="l00068"></a>00068                         <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0;i &lt; Val.length();i++) {x (i) = <a class="code" href="classbdm_1_1eEF.html#a4135778ecd9ab774762936c82a097c6" title="Evaluate normalized log-probability.">evallog_nn</a> (Val (i)) ;}
+<a name="l00069"></a>00069                         <span class="keywordflow">return</span> x -<a class="code" href="classbdm_1_1eEF.html#cd678fc9b02007a4b8d6692e746f1bf8" title="logarithm of the normalizing constant, ">lognc</a>();
+<a name="l00070"></a>00070                 }
 <a name="l00071"></a>00071 
-<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>
-<a name="l00074"></a>00074 {
-<a name="l00075"></a>00075         <span class="keyword">protected</span>:
-<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>;
-<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>;
-<a name="l00080"></a>00080         <span class="keyword">public</span>:
-<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) {}
-<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> &amp;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>) {}
-<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>);};
-<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 &amp;data, <span class="keyword">const</span> <span class="keywordtype">double</span> w) {};
-<a name="l00089"></a>00089                 <span class="comment">//original Bayes</span>
-<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 &amp;dt);
-<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>);}
-<a name="l00094"></a>00094 <span class="comment">//      virtual void flatten ( double nu0 ) {it_error ( "Not implemented" );}</span>
-<a name="l00095"></a>00095 
-<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;};
-<a name="l00097"></a>00097 };
-<a name="l00098"></a>00098 
-<a name="l00099"></a>00099 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T, <span class="keyword">template</span> &lt;<span class="keyword">typename</span>&gt; <span class="keyword">class </span>TEpdf&gt;
-<a name="l00100"></a>00100 <span class="keyword">class </span>mlnorm;
+<a name="l00073"></a><a class="code" href="classbdm_1_1eEF.html#cf38af29e8e3d650c640509a52396053">00073</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) {
+<a name="l00074"></a>00074                         <a class="code" href="bdmerror_8h.html#7c43f3a72afe68ab0c85663a1bb3521a" title="Unconditionally throw std::runtime_error.">bdm_error</a> (<span class="stringliteral">"Not implemented"</span>);
+<a name="l00075"></a>00075                 }
+<a name="l00076"></a>00076 };
+<a name="l00077"></a>00077 
+<a name="l00078"></a>00078 
+<a name="l00080"></a><a class="code" href="classbdm_1_1BMEF.html">00080</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>
+<a name="l00081"></a>00081 {
+<a name="l00082"></a>00082         <span class="keyword">protected</span>:
+<a name="l00084"></a><a class="code" href="classbdm_1_1BMEF.html#1331865e10fb1ccef65bb4c47fa3be64">00084</a>                 <span class="keywordtype">double</span> <a class="code" href="classbdm_1_1BMEF.html#1331865e10fb1ccef65bb4c47fa3be64" title="forgetting factor">frg</a>;
+<a name="l00086"></a><a class="code" href="classbdm_1_1BMEF.html#06e7b3ac03e10017d4288c76888e2865">00086</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>;
+<a name="l00087"></a>00087         <span class="keyword">public</span>:
+<a name="l00089"></a><a class="code" href="classbdm_1_1BMEF.html#2def512872ed8a4fc3b702371ec0be55">00089</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) {}
+<a name="l00091"></a><a class="code" href="classbdm_1_1BMEF.html#9662379513101405e159e76717104e62">00091</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> &amp;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>) {}
+<a name="l00093"></a><a class="code" href="classbdm_1_1BMEF.html#d2b528b7a41ca67163152142f5404051">00093</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) {
+<a name="l00094"></a>00094                         <a class="code" href="bdmerror_8h.html#7c43f3a72afe68ab0c85663a1bb3521a" title="Unconditionally throw std::runtime_error.">bdm_error</a> (<span class="stringliteral">"Not implemented"</span>);
+<a name="l00095"></a>00095                 }
+<a name="l00096"></a>00096 
+<a name="l00098"></a><a class="code" href="classbdm_1_1BMEF.html#bf58deb99af2a6cc674f13ff90300de6">00098</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 &amp;data, <span class="keyword">const</span> <span class="keywordtype">double</span> w) {};
+<a name="l00099"></a>00099                 <span class="comment">//original Bayes</span>
+<a name="l00100"></a>00100                 <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 &amp;dt);
 <a name="l00101"></a>00101 
-<a name="l00107"></a>00107 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt;
-<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>
-<a name="l00109"></a>00109 {
-<a name="l00110"></a>00110         <span class="keyword">protected</span>:
-<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>;
-<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>;
-<a name="l00115"></a>00115         <span class="keyword">public</span>:
-<a name="l00118"></a>00118 
-<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> () {};
-<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 &amp;<a class="code" href="classbdm_1_1enorm.html#c702a194720853570d08b65482f842c7" title="mean value">mu</a>, <span class="keyword">const</span> sq_T &amp;<a class="code" href="classbdm_1_1enorm.html#2d92dde696b2a7a5b10ddef5d22ba2c2" title="Covariance matrix in decomposed form.">R</a>) {set_parameters (mu, R);}
-<a name="l00121"></a>00121                 <span class="keywordtype">void</span> set_parameters (<span class="keyword">const</span> vec &amp;<a class="code" href="classbdm_1_1enorm.html#c702a194720853570d08b65482f842c7" title="mean value">mu</a>, <span class="keyword">const</span> sq_T &amp;<a class="code" href="classbdm_1_1enorm.html#2d92dde696b2a7a5b10ddef5d22ba2c2" title="Covariance matrix in decomposed form.">R</a>);
-<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 &amp;root);
-<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>() {
-<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>);
-<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();
-<a name="l00126"></a>00126                 }
-<a name="l00128"></a>00128 
-<a name="l00131"></a>00131 
-<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 &amp;v, <span class="keywordtype">double</span> nu = 1.0);
-<a name="l00134"></a>00134 
-<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>;
-<a name="l00136"></a>00136 
-<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 &amp;val) <span class="keyword">const</span>;
-<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>;
-<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>;}
-<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());}
-<a name="l00141"></a>00141 <span class="comment">//      mlnorm&lt;sq_T&gt;* condition ( const RV &amp;rvn ) const ; &lt;=========== fails to cmpile. Why?</span>
-<a name="l00142"></a>00142                 <a class="code" href="classbdm_1_1shared__ptr.html">shared_ptr&lt;mpdf&gt;</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> &amp;rvn ) <span class="keyword">const</span>;
-<a name="l00143"></a>00143 
-<a name="l00144"></a>00144                 <span class="comment">// target not typed to mlnorm&lt;sq_T, enorm&lt;sq_T&gt; &gt; &amp;</span>
-<a name="l00145"></a>00145                 <span class="comment">// because that doesn't compile (perhaps because we</span>
-<a name="l00146"></a>00146                 <span class="comment">// haven't finished defining enorm yet), but the type</span>
-<a name="l00147"></a>00147                 <span class="comment">// is required</span>
-<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> &amp;rvn, <a class="code" href="classbdm_1_1mpdf.html" title="Conditional probability density, e.g. modeling , where  is random variable, rv, and...">mpdf</a> &amp;target ) <span class="keyword">const</span>;
-<a name="l00149"></a>00149 
-<a name="l00150"></a>00150                 <a class="code" href="classbdm_1_1shared__ptr.html">shared_ptr&lt;epdf&gt;</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> &amp;rvn ) <span class="keyword">const</span>;
-<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> &amp;rvn, <a class="code" href="classbdm_1_1enorm.html" title="Gaussian density with positive definite (decomposed) covariance matrix.">enorm&lt;sq_T&gt;</a> &amp;target ) <span class="keyword">const</span>;
-<a name="l00153"></a>00153 
-<a name="l00156"></a>00156 
-<a name="l00157"></a>00157                 vec&amp; _mu() {<span class="keywordflow">return</span> <a class="code" href="classbdm_1_1enorm.html#c702a194720853570d08b65482f842c7" title="mean value">mu</a>;}
-<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;}
-<a name="l00159"></a>00159                 sq_T&amp; _R() {<span class="keywordflow">return</span> <a class="code" href="classbdm_1_1enorm.html#2d92dde696b2a7a5b10ddef5d22ba2c2" title="Covariance matrix in decomposed form.">R</a>;}
-<a name="l00160"></a>00160                 <span class="keyword">const</span> sq_T&amp; _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>;}
-<a name="l00162"></a>00162 
-<a name="l00163"></a>00163 };
-<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);
-<a name="l00165"></a>00165 SHAREDPTR2 ( enorm, chmat );
-<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);
-<a name="l00167"></a>00167 SHAREDPTR2 ( enorm, ldmat );
-<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);
-<a name="l00169"></a>00169 SHAREDPTR2 ( enorm, fsqmat );
+<a name="l00103"></a><a class="code" href="classbdm_1_1BMEF.html#b2916a2e71a958665054473124d5e749">00103</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) {
+<a name="l00104"></a>00104                         <a class="code" href="bdmerror_8h.html#7c43f3a72afe68ab0c85663a1bb3521a" title="Unconditionally throw std::runtime_error.">bdm_error</a> (<span class="stringliteral">"Not implemented"</span>);
+<a name="l00105"></a>00105                 }
+<a name="l00106"></a>00106 
+<a name="l00107"></a><a class="code" href="classbdm_1_1BMEF.html#62d2e4691bed41a1efa6b9c2e35e5c67">00107</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">_copy_</a> ()<span class="keyword"> const </span>{
+<a name="l00108"></a>00108                         <a class="code" href="bdmerror_8h.html#7c43f3a72afe68ab0c85663a1bb3521a" title="Unconditionally throw std::runtime_error.">bdm_error</a> (<span class="stringliteral">"function _copy_ not implemented for this BM"</span>);
+<a name="l00109"></a>00109                         <span class="keywordflow">return</span> NULL;
+<a name="l00110"></a>00110                 }
+<a name="l00111"></a>00111 };
+<a name="l00112"></a>00112 
+<a name="l00113"></a>00113 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T, <span class="keyword">template</span> &lt;<span class="keyword">typename</span>&gt; <span class="keyword">class </span>TEpdf&gt;
+<a name="l00114"></a>00114 <span class="keyword">class </span>mlnorm;
+<a name="l00115"></a>00115 
+<a name="l00121"></a>00121 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt;
+<a name="l00122"></a><a class="code" href="classbdm_1_1enorm.html">00122</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>
+<a name="l00123"></a>00123 {
+<a name="l00124"></a>00124         <span class="keyword">protected</span>:
+<a name="l00126"></a><a class="code" href="classbdm_1_1enorm.html#c702a194720853570d08b65482f842c7">00126</a>                 vec <a class="code" href="classbdm_1_1enorm.html#c702a194720853570d08b65482f842c7" title="mean value">mu</a>;
+<a name="l00128"></a><a class="code" href="classbdm_1_1enorm.html#2d92dde696b2a7a5b10ddef5d22ba2c2">00128</a>                 sq_T <a class="code" href="classbdm_1_1enorm.html#2d92dde696b2a7a5b10ddef5d22ba2c2" title="Covariance matrix in decomposed form.">R</a>;
+<a name="l00129"></a>00129         <span class="keyword">public</span>:
+<a name="l00132"></a>00132 
+<a name="l00133"></a>00133                 <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> () {};
+<a name="l00134"></a>00134                 <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 &amp;<a class="code" href="classbdm_1_1enorm.html#c702a194720853570d08b65482f842c7" title="mean value">mu</a>, <span class="keyword">const</span> sq_T &amp;<a class="code" href="classbdm_1_1enorm.html#2d92dde696b2a7a5b10ddef5d22ba2c2" title="Covariance matrix in decomposed form.">R</a>) {set_parameters (mu, R);}
+<a name="l00135"></a>00135                 <span class="keywordtype">void</span> set_parameters (<span class="keyword">const</span> vec &amp;<a class="code" href="classbdm_1_1enorm.html#c702a194720853570d08b65482f842c7" title="mean value">mu</a>, <span class="keyword">const</span> sq_T &amp;<a class="code" href="classbdm_1_1enorm.html#2d92dde696b2a7a5b10ddef5d22ba2c2" title="Covariance matrix in decomposed form.">R</a>);
+<a name="l00136"></a>00136                 <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1enorm.html#61bd470764020bea6e1ed35000f259e6">from_setting</a> (<span class="keyword">const</span> Setting &amp;root);
+<a name="l00137"></a><a class="code" href="classbdm_1_1enorm.html#38eb17ecb75d94a50b6782fcf735cfea">00137</a>                 <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1enorm.html#38eb17ecb75d94a50b6782fcf735cfea" title="This method TODO.">validate</a>() {
+<a name="l00138"></a>00138                         <a class="code" href="bdmerror_8h.html#89a0f906b242b79c5d3d342291b2cab4" title="Throw std::runtime_exception if t is not true and NDEBUG is not defined.">bdm_assert_debug</a> (<a class="code" href="classbdm_1_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>);
+<a name="l00139"></a>00139                         <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();
+<a name="l00140"></a>00140                 }
+<a name="l00142"></a>00142 
+<a name="l00145"></a>00145 
+<a name="l00147"></a>00147                 <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 &amp;v, <span class="keywordtype">double</span> nu = 1.0);
+<a name="l00148"></a>00148 
+<a name="l00149"></a>00149                 vec <a class="code" href="classbdm_1_1enorm.html#e1a48f52351ec3a349bd443b713b1766" title="Returns a sample,  from density .">sample</a>() <span class="keyword">const</span>;
+<a name="l00150"></a>00150 
+<a name="l00151"></a>00151                 <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 &amp;val) <span class="keyword">const</span>;
+<a name="l00152"></a>00152                 <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>;
+<a name="l00153"></a><a class="code" href="classbdm_1_1enorm.html#b2fa2915c35366392fe9bb022ca1a600">00153</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>;}
+<a name="l00154"></a><a class="code" href="classbdm_1_1enorm.html#729c75ef0fa8abae03d58ad1f81e6773">00154</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());}
+<a name="l00155"></a>00155 <span class="comment">//      mlnorm&lt;sq_T&gt;* condition ( const RV &amp;rvn ) const ; &lt;=========== fails to cmpile. Why?</span>
+<a name="l00156"></a>00156                 <a class="code" href="classbdm_1_1shared__ptr.html">shared_ptr&lt;mpdf&gt;</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> &amp;rvn ) <span class="keyword">const</span>;
+<a name="l00157"></a>00157 
+<a name="l00158"></a>00158                 <span class="comment">// target not typed to mlnorm&lt;sq_T, enorm&lt;sq_T&gt; &gt; &amp;</span>
+<a name="l00159"></a>00159                 <span class="comment">// because that doesn't compile (perhaps because we</span>
+<a name="l00160"></a>00160                 <span class="comment">// haven't finished defining enorm yet), but the type</span>
+<a name="l00161"></a>00161                 <span class="comment">// is required</span>
+<a name="l00162"></a>00162                 <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> &amp;rvn, <a class="code" href="classbdm_1_1mpdf.html" title="Conditional probability density, e.g. modeling , where  is random variable, rv, and...">mpdf</a> &amp;target ) <span class="keyword">const</span>;
+<a name="l00163"></a>00163 
+<a name="l00164"></a>00164                 <a class="code" href="classbdm_1_1shared__ptr.html">shared_ptr&lt;epdf&gt;</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> &amp;rvn ) <span class="keyword">const</span>;
+<a name="l00165"></a>00165                 <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> &amp;rvn, <a class="code" href="classbdm_1_1enorm.html" title="Gaussian density with positive definite (decomposed) covariance matrix.">enorm&lt;sq_T&gt;</a> &amp;target ) <span class="keyword">const</span>;
+<a name="l00167"></a>00167 
 <a name="l00170"></a>00170 
-<a name="l00171"></a>00171 
-<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>
-<a name="l00179"></a>00179 {
-<a name="l00180"></a>00180         <span class="keyword">protected</span>:
-<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>;
-<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>;
-<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>;
-<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>;
-<a name="l00189"></a>00189         <span class="keyword">public</span>:
-<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>() {};
-<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);};
-<a name="l00194"></a>00194 
-<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) {
-<a name="l00196"></a>00196                         <a class="code" href="classbdm_1_1egiw.html#23e4d78bea7e98840f3da30e76a2b57a" title="Dimension of the output.">dimx</a> = dimx0;
-<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>;
-<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>
-<a name="l00199"></a>00199 
-<a name="l00200"></a>00200                         <a class="code" href="classbdm_1_1egiw.html#ae56852845c6af176fd9017dbebbbd52" title="Extended information matrix of sufficient statistics.">V</a> = V0;
-<a name="l00201"></a>00201                         <span class="keywordflow">if</span> (nu0 &lt; 0) {
-<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>
-<a name="l00203"></a>00203                                 <span class="comment">// terms before that are sufficient for finite normalization</span>
-<a name="l00204"></a>00204                         } <span class="keywordflow">else</span> {
-<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;
-<a name="l00206"></a>00206                         }
-<a name="l00207"></a>00207                 }
+<a name="l00171"></a>00171                 vec&amp; _mu() {<span class="keywordflow">return</span> <a class="code" href="classbdm_1_1enorm.html#c702a194720853570d08b65482f842c7" title="mean value">mu</a>;}
+<a name="l00172"></a>00172                 <span class="keyword">const</span> vec&amp; _mu()<span class="keyword"> const </span>{<span class="keywordflow">return</span> <a class="code" href="classbdm_1_1enorm.html#c702a194720853570d08b65482f842c7" title="mean value">mu</a>;}
+<a name="l00173"></a>00173                 <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;}
+<a name="l00174"></a>00174                 sq_T&amp; _R() {<span class="keywordflow">return</span> <a class="code" href="classbdm_1_1enorm.html#2d92dde696b2a7a5b10ddef5d22ba2c2" title="Covariance matrix in decomposed form.">R</a>;}
+<a name="l00175"></a>00175                 <span class="keyword">const</span> sq_T&amp; _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>;}
+<a name="l00177"></a>00177 
+<a name="l00178"></a>00178 };
+<a name="l00179"></a>00179 <a class="code" href="user__info_8h.html#b06f1e7c44a8306e321f62a0099210b9" title="Variant of UIREGISTER for templated classes.">UIREGISTER2</a> (enorm, chmat);
+<a name="l00180"></a>00180 SHAREDPTR2 ( enorm, chmat );
+<a name="l00181"></a>00181 <a class="code" href="user__info_8h.html#b06f1e7c44a8306e321f62a0099210b9" title="Variant of UIREGISTER for templated classes.">UIREGISTER2</a> (enorm, ldmat);
+<a name="l00182"></a>00182 SHAREDPTR2 ( enorm, ldmat );
+<a name="l00183"></a>00183 <a class="code" href="user__info_8h.html#b06f1e7c44a8306e321f62a0099210b9" title="Variant of UIREGISTER for templated classes.">UIREGISTER2</a> (enorm, fsqmat);
+<a name="l00184"></a>00184 SHAREDPTR2 ( enorm, fsqmat );
+<a name="l00185"></a>00185 
+<a name="l00186"></a>00186 
+<a name="l00193"></a><a class="code" href="classbdm_1_1egiw.html">00193</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>
+<a name="l00194"></a>00194 {
+<a name="l00195"></a>00195         <span class="keyword">protected</span>:
+<a name="l00197"></a><a class="code" href="classbdm_1_1egiw.html#ae56852845c6af176fd9017dbebbbd52">00197</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>;
+<a name="l00199"></a><a class="code" href="classbdm_1_1egiw.html#447eacf19d4f4083872686f044814dc4">00199</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>;
+<a name="l00201"></a><a class="code" href="classbdm_1_1egiw.html#23e4d78bea7e98840f3da30e76a2b57a">00201</a>                 <span class="keywordtype">int</span> <a class="code" href="classbdm_1_1egiw.html#23e4d78bea7e98840f3da30e76a2b57a" title="Dimension of the output.">dimx</a>;
+<a name="l00203"></a><a class="code" href="classbdm_1_1egiw.html#322414c32d9a21a006a5aab0311f64fd">00203</a>                 <span class="keywordtype">int</span> <a class="code" href="classbdm_1_1egiw.html#322414c32d9a21a006a5aab0311f64fd" title="Dimension of the regressor.">nPsi</a>;
+<a name="l00204"></a>00204         <span class="keyword">public</span>:
+<a name="l00207"></a>00207                 <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>() {};
+<a name="l00208"></a>00208                 <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);};
 <a name="l00209"></a>00209 
-<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>;
-<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>;
-<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>;
-<a name="l00213"></a>00213 
-<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>;
-<a name="l00216"></a>00216 
-<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>;
-<a name="l00219"></a>00219 
-<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 &amp;M, mat&amp;R) <span class="keyword">const</span>;
-<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 &amp;val) <span class="keyword">const</span>;
-<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>;
-<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;};
-<a name="l00226"></a>00226 
-<a name="l00229"></a>00229 
-<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>&amp; _V() {<span class="keywordflow">return</span> V;}
-<a name="l00231"></a>00231                 <span class="keyword">const</span> ldmat&amp; _V()<span class="keyword"> const </span>{<span class="keywordflow">return</span> V;}
-<a name="l00232"></a>00232                 <span class="keywordtype">double</span>&amp; _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>;}
-<a name="l00233"></a>00233                 <span class="keyword">const</span> <span class="keywordtype">double</span>&amp; _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>;}
-<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 &amp;<span class="keyword">set</span>) {
-<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);
-<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);
-<a name="l00237"></a>00237                         mat V;
-<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);
-<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>);
-<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&lt;RV&gt;</a> <a class="code" href="classbdm_1_1epdf.html#62c5b8ff71d9ebe6cd58d3c342eb1dc8" title="Description of the random variable.">rv</a> = UI::build&lt;RV&gt; (<span class="keyword">set</span>, <span class="stringliteral">"rv"</span>, UI::compulsory);
-<a name="l00241"></a>00241                         <a class="code" href="classbdm_1_1epdf.html#f423e28448dbb69ef4905295ec8de8ff" title="Name its rv.">set_rv</a> (*rv);
-<a name="l00242"></a>00242                 }
-<a name="l00244"></a>00244 };
-<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 );
-<a name="l00246"></a>00246 SHAREDPTR ( egiw );
-<a name="l00247"></a>00247 
-<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>
-<a name="l00257"></a>00257 {
-<a name="l00258"></a>00258         <span class="keyword">protected</span>:
-<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>;
-<a name="l00261"></a>00261         <span class="keyword">public</span>:
-<a name="l00264"></a>00264 
-<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> () {};
-<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> &amp;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>);};
-<a name="l00267"></a>00267                 eDirich (<span class="keyword">const</span> vec &amp;beta0) {set_parameters (beta0);};
-<a name="l00268"></a>00268                 <span class="keywordtype">void</span> set_parameters (<span class="keyword">const</span> vec &amp;beta0) {
-<a name="l00269"></a>00269                         <a class="code" href="classbdm_1_1eDirich.html#f25886a49b4667af61245de81c83b5d2" title="sufficient statistics">beta</a> = beta0;
-<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();
-<a name="l00271"></a>00271                 }
-<a name="l00273"></a>00273 
-<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);};
-<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>);};
-<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));}
-<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 &amp;val)<span class="keyword"> const </span>{
-<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);
-<a name="l00280"></a>00280 <span class="comment">//                              it_assert_debug ( std::isfinite ( tmp ),"Infinite value" );</span>
-<a name="l00281"></a>00281                         <span class="keywordflow">return</span> tmp;
-<a name="l00282"></a>00282                 };
-<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>{
-<a name="l00284"></a>00284                         <span class="keywordtype">double</span> tmp;
-<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>);
-<a name="l00286"></a>00286                         <span class="keywordtype">double</span> lgb = 0.0;
-<a name="l00287"></a>00287                         <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0;i &lt; <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));}
-<a name="l00288"></a>00288                         tmp = lgb - lgamma (gam);
-<a name="l00289"></a>00289 <span class="comment">//                              it_assert_debug ( std::isfinite ( tmp ),"Infinite value" );</span>
-<a name="l00290"></a>00290                         <span class="keywordflow">return</span> tmp;
-<a name="l00291"></a>00291                 };
-<a name="l00293"></a><a class="code" href="classbdm_1_1eDirich.html#175e0add26d2105c28d8121eefb9e324">00293</a>                 vec&amp; <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>;}
-<a name="l00295"></a>00295 };
-<a name="l00296"></a>00296 
-<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>
-<a name="l00299"></a>00299 {
-<a name="l00300"></a>00300         <span class="keyword">protected</span>:
-<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>;
-<a name="l00304"></a><a class="code" href="classbdm_1_1multiBM.html#044263356944c92209eecd39a5187d25">00304</a>                 vec &amp;<a class="code" href="classbdm_1_1multiBM.html#044263356944c92209eecd39a5187d25" title="Pointer inside est to sufficient statistics.">beta</a>;
-<a name="l00305"></a>00305         <span class="keyword">public</span>:
-<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()) {
-<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() &gt; 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>();}
-<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;}
-<a name="l00310"></a>00310                 }
-<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> &amp;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()) {}
-<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&lt;</span><span class="keyword">const </span><a class="code" href="classbdm_1_1multiBM.html" title="Estimator for Multinomial density.">multiBM</a>*<span class="keyword">&gt;</span> (mB0); <a class="code" href="classbdm_1_1multiBM.html#044263356944c92209eecd39a5187d25" title="Pointer inside est to sufficient statistics.">beta</a> = mB-&gt;<a class="code" href="classbdm_1_1multiBM.html#044263356944c92209eecd39a5187d25" title="Pointer inside est to sufficient statistics.">beta</a>;}
-<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 &amp;dt) {
-<a name="l00316"></a>00316                         <span class="keywordflow">if</span> (<a class="code" href="classbdm_1_1BMEF.html#1331865e10fb1ccef65bb4c47fa3be64" title="forgetting factor">frg</a> &lt; 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>();}
-<a name="l00317"></a>00317                         <a class="code" href="classbdm_1_1multiBM.html#044263356944c92209eecd39a5187d25" title="Pointer inside est to sufficient statistics.">beta</a> += dt;
-<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>;}
-<a name="l00319"></a>00319                 }
-<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 &amp;dt)<span class="keyword"> const </span>{
-<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>);
-<a name="l00322"></a>00322                         vec &amp;<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>();
-<a name="l00323"></a>00323 
-<a name="l00324"></a>00324                         <span class="keywordtype">double</span> lll;
-<a name="l00325"></a>00325                         <span class="keywordflow">if</span> (<a class="code" href="classbdm_1_1BMEF.html#1331865e10fb1ccef65bb4c47fa3be64" title="forgetting factor">frg</a> &lt; 1.0)
-<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>();}
-<a name="l00327"></a>00327                         <span class="keywordflow">else</span>
-<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>;}
-<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>();}
-<a name="l00330"></a>00330 
-<a name="l00331"></a>00331                         beta += dt;
-<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;
-<a name="l00333"></a>00333                 }
-<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) {
-<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&lt;</span><span class="keyword">const </span><a class="code" href="classbdm_1_1multiBM.html" title="Estimator for Multinomial density.">multiBM</a>*<span class="keyword">&gt;</span> (B);
-<a name="l00336"></a>00336                         <span class="comment">// sum(beta) should be equal to sum(B.beta)</span>
-<a name="l00337"></a>00337                         <span class="keyword">const</span> vec &amp;Eb = E-&gt;<a class="code" href="classbdm_1_1multiBM.html#044263356944c92209eecd39a5187d25" title="Pointer inside est to sufficient statistics.">beta</a>;<span class="comment">//const_cast&lt;multiBM*&gt; ( E )-&gt;_beta();</span>
-<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>));
-<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>();}
-<a name="l00340"></a>00340                 }
-<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>&amp; <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>;};
-<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 &amp;beta0) {
-<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);
-<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>();}
-<a name="l00347"></a>00347                 }
-<a name="l00348"></a>00348 };
+<a name="l00210"></a>00210                 <span class="keywordtype">void</span> set_parameters (<span class="keywordtype">int</span> dimx0, ldmat V0, <span class="keywordtype">double</span> nu0 = -1.0) {
+<a name="l00211"></a>00211                         <a class="code" href="classbdm_1_1egiw.html#23e4d78bea7e98840f3da30e76a2b57a" title="Dimension of the output.">dimx</a> = dimx0;
+<a name="l00212"></a>00212                         <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>;
+<a name="l00213"></a>00213                         <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>
+<a name="l00214"></a>00214 
+<a name="l00215"></a>00215                         <a class="code" href="classbdm_1_1egiw.html#ae56852845c6af176fd9017dbebbbd52" title="Extended information matrix of sufficient statistics.">V</a> = V0;
+<a name="l00216"></a>00216                         <span class="keywordflow">if</span> (nu0 &lt; 0) {
+<a name="l00217"></a>00217                                 <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>
+<a name="l00218"></a>00218                                 <span class="comment">// terms before that are sufficient for finite normalization</span>
+<a name="l00219"></a>00219                         } <span class="keywordflow">else</span> {
+<a name="l00220"></a>00220                                 <a class="code" href="classbdm_1_1egiw.html#447eacf19d4f4083872686f044814dc4" title="Number of data records (degrees of freedom) of sufficient statistics.">nu</a> = nu0;
+<a name="l00221"></a>00221                         }
+<a name="l00222"></a>00222                 }
+<a name="l00224"></a>00224 
+<a name="l00225"></a>00225                 vec <a class="code" href="classbdm_1_1egiw.html#920f21548b7a3723923dd108fe514c61" title="Returns a sample,  from density .">sample</a>() <span class="keyword">const</span>;
+<a name="l00226"></a>00226                 vec <a class="code" href="classbdm_1_1egiw.html#df70c05f918c3a6f86d60f10c1fd6ba2" title="return expected value">mean</a>() <span class="keyword">const</span>;
+<a name="l00227"></a>00227                 vec <a class="code" href="classbdm_1_1egiw.html#c1ecc406613cc2341225dc10c3d3b46a" title="return expected variance (not covariance!)">variance</a>() <span class="keyword">const</span>;
+<a name="l00228"></a>00228 
+<a name="l00230"></a>00230                 vec <a class="code" href="classbdm_1_1egiw.html#66d2ba9295c306012b309efcc9e516f0" title="LS estimate of .">est_theta</a>() <span class="keyword">const</span>;
+<a name="l00231"></a>00231 
+<a name="l00233"></a>00233                 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>;
+<a name="l00234"></a>00234 
+<a name="l00236"></a>00236                 <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 &amp;M, mat&amp;R) <span class="keyword">const</span>;
+<a name="l00238"></a>00238                 <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 &amp;val) <span class="keyword">const</span>;
+<a name="l00239"></a>00239                 <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>;
+<a name="l00240"></a><a class="code" href="classbdm_1_1egiw.html#8e610e95401a11baf34f65e16ecd87be">00240</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;};
+<a name="l00241"></a>00241 
+<a name="l00244"></a>00244 
+<a name="l00245"></a>00245                 <a class="code" href="classbdm_1_1ldmat.html" title="Matrix stored in LD form, (commonly known as UD).">ldmat</a>&amp; _V() {<span class="keywordflow">return</span> V;}
+<a name="l00246"></a>00246                 <span class="keyword">const</span> ldmat&amp; _V()<span class="keyword"> const </span>{<span class="keywordflow">return</span> V;}
+<a name="l00247"></a>00247                 <span class="keywordtype">double</span>&amp; _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>;}
+<a name="l00248"></a>00248                 <span class="keyword">const</span> <span class="keywordtype">double</span>&amp; _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>;}
+<a name="l00249"></a><a class="code" href="classbdm_1_1egiw.html#55b76ec75bd2df5ef9cab3be20a33bbb">00249</a>                 <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1egiw.html#55b76ec75bd2df5ef9cab3be20a33bbb">from_setting</a> (<span class="keyword">const</span> Setting &amp;<span class="keyword">set</span>) {
+<a name="l00250"></a>00250                         <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);
+<a name="l00251"></a>00251                         <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);
+<a name="l00252"></a>00252                         mat V;
+<a name="l00253"></a>00253                         <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);
+<a name="l00254"></a>00254                         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>);
+<a name="l00255"></a>00255                         <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&lt;RV&gt;</a> <a class="code" href="classbdm_1_1epdf.html#62c5b8ff71d9ebe6cd58d3c342eb1dc8" title="Description of the random variable.">rv</a> = UI::build&lt;RV&gt; (<span class="keyword">set</span>, <span class="stringliteral">"rv"</span>, UI::compulsory);
+<a name="l00256"></a>00256                         <a class="code" href="classbdm_1_1epdf.html#f423e28448dbb69ef4905295ec8de8ff" title="Name its rv.">set_rv</a> (*rv);
+<a name="l00257"></a>00257                 }
+<a name="l00259"></a>00259 };
+<a name="l00260"></a>00260 <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 );
+<a name="l00261"></a>00261 SHAREDPTR ( egiw );
+<a name="l00262"></a>00262 
+<a name="l00271"></a><a class="code" href="classbdm_1_1eDirich.html">00271</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>
+<a name="l00272"></a>00272 {
+<a name="l00273"></a>00273         <span class="keyword">protected</span>:
+<a name="l00275"></a><a class="code" href="classbdm_1_1eDirich.html#f25886a49b4667af61245de81c83b5d2">00275</a>                 vec <a class="code" href="classbdm_1_1eDirich.html#f25886a49b4667af61245de81c83b5d2" title="sufficient statistics">beta</a>;
+<a name="l00276"></a>00276         <span class="keyword">public</span>:
+<a name="l00279"></a>00279 
+<a name="l00280"></a>00280                 <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> () {};
+<a name="l00281"></a>00281                 <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> &amp;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>);};
+<a name="l00282"></a>00282                 eDirich (<span class="keyword">const</span> vec &amp;beta0) {set_parameters (beta0);};
+<a name="l00283"></a>00283                 <span class="keywordtype">void</span> set_parameters (<span class="keyword">const</span> vec &amp;beta0) {
+<a name="l00284"></a>00284                         <a class="code" href="classbdm_1_1eDirich.html#f25886a49b4667af61245de81c83b5d2" title="sufficient statistics">beta</a> = beta0;
+<a name="l00285"></a>00285                         <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();
+<a name="l00286"></a>00286                 }
+<a name="l00288"></a>00288 
+<a name="l00289"></a><a class="code" href="classbdm_1_1eDirich.html#3290613d31d58daa8a45a54b003871fc">00289</a>                 vec <a class="code" href="classbdm_1_1eDirich.html#3290613d31d58daa8a45a54b003871fc" title="Returns a sample,  from density .">sample</a>()<span class="keyword"> const </span>{
+<a name="l00290"></a>00290                         <a class="code" href="bdmerror_8h.html#7c43f3a72afe68ab0c85663a1bb3521a" title="Unconditionally throw std::runtime_error.">bdm_error</a> (<span class="stringliteral">"Not implemented"</span>);
+<a name="l00291"></a>00291                         <span class="keywordflow">return</span> vec();
+<a name="l00292"></a>00292                 }
+<a name="l00293"></a>00293 
+<a name="l00294"></a><a class="code" href="classbdm_1_1eDirich.html#cb343355ec791298bb5a3404cd482fb6">00294</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>);};
+<a name="l00295"></a><a class="code" href="classbdm_1_1eDirich.html#43c547a2507e233706f92712d8c2aacc">00295</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));}
+<a name="l00297"></a><a class="code" href="classbdm_1_1eDirich.html#e09a24938e80c3d94b0ee842d1552318">00297</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 &amp;val)<span class="keyword"> const </span>{
+<a name="l00298"></a>00298                         <span class="keywordtype">double</span> tmp; tmp = (<a class="code" href="classbdm_1_1eDirich.html#f25886a49b4667af61245de81c83b5d2" title="sufficient statistics">beta</a> - 1) * log (val);
+<a name="l00299"></a>00299                         <span class="keywordflow">return</span> tmp;
+<a name="l00300"></a>00300                 }
+<a name="l00301"></a>00301 
+<a name="l00302"></a><a class="code" href="classbdm_1_1eDirich.html#279a99f6266c82fe2273e83841f19eb2">00302</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>{
+<a name="l00303"></a>00303                         <span class="keywordtype">double</span> tmp;
+<a name="l00304"></a>00304                         <span class="keywordtype">double</span> gam = sum (<a class="code" href="classbdm_1_1eDirich.html#f25886a49b4667af61245de81c83b5d2" title="sufficient statistics">beta</a>);
+<a name="l00305"></a>00305                         <span class="keywordtype">double</span> lgb = 0.0;
+<a name="l00306"></a>00306                         <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0;i &lt; <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));}
+<a name="l00307"></a>00307                         tmp = lgb - lgamma (gam);
+<a name="l00308"></a>00308                         <span class="keywordflow">return</span> tmp;
+<a name="l00309"></a>00309                 }
+<a name="l00310"></a>00310 
+<a name="l00312"></a><a class="code" href="classbdm_1_1eDirich.html#175e0add26d2105c28d8121eefb9e324">00312</a>                 vec&amp; <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>;}
+<a name="l00314"></a>00314 };
+<a name="l00315"></a>00315 
+<a name="l00317"></a><a class="code" href="classbdm_1_1multiBM.html">00317</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>
+<a name="l00318"></a>00318 {
+<a name="l00319"></a>00319         <span class="keyword">protected</span>:
+<a name="l00321"></a><a class="code" href="classbdm_1_1multiBM.html#9ecc6878abbd20eb8d8e43b6ab3f941a">00321</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>;
+<a name="l00323"></a><a class="code" href="classbdm_1_1multiBM.html#044263356944c92209eecd39a5187d25">00323</a>                 vec &amp;<a class="code" href="classbdm_1_1multiBM.html#044263356944c92209eecd39a5187d25" title="Pointer inside est to sufficient statistics.">beta</a>;
+<a name="l00324"></a>00324         <span class="keyword">public</span>:
+<a name="l00326"></a><a class="code" href="classbdm_1_1multiBM.html#c4dd6d9522a8a605776d21bac9bd9daf">00326</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()) {
+<a name="l00327"></a>00327                         <span class="keywordflow">if</span> (<a class="code" href="classbdm_1_1multiBM.html#044263356944c92209eecd39a5187d25" title="Pointer inside est to sufficient statistics.">beta</a>.length() &gt; 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>();}
+<a name="l00328"></a>00328                         <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;}
+<a name="l00329"></a>00329                 }
+<a name="l00331"></a><a class="code" href="classbdm_1_1multiBM.html#c4378cf8037f6bed29c74eea63344b31">00331</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> &amp;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()) {}
+<a name="l00333"></a><a class="code" href="classbdm_1_1multiBM.html#dbe6b90d410dc062a233d1dc09eeba52">00333</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&lt;</span><span class="keyword">const </span><a class="code" href="classbdm_1_1multiBM.html" title="Estimator for Multinomial density.">multiBM</a>*<span class="keyword">&gt;</span> (mB0); <a class="code" href="classbdm_1_1multiBM.html#044263356944c92209eecd39a5187d25" title="Pointer inside est to sufficient statistics.">beta</a> = mB-&gt;<a class="code" href="classbdm_1_1multiBM.html#044263356944c92209eecd39a5187d25" title="Pointer inside est to sufficient statistics.">beta</a>;}
+<a name="l00334"></a><a class="code" href="classbdm_1_1multiBM.html#1e4bf41b61937fd80f34049742e23f95">00334</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 &amp;dt) {
+<a name="l00335"></a>00335                         <span class="keywordflow">if</span> (<a class="code" href="classbdm_1_1BMEF.html#1331865e10fb1ccef65bb4c47fa3be64" title="forgetting factor">frg</a> &lt; 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>();}
+<a name="l00336"></a>00336                         <a class="code" href="classbdm_1_1multiBM.html#044263356944c92209eecd39a5187d25" title="Pointer inside est to sufficient statistics.">beta</a> += dt;
+<a name="l00337"></a>00337                         <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>;}
+<a name="l00338"></a>00338                 }
+<a name="l00339"></a><a class="code" href="classbdm_1_1multiBM.html#e157b607c1e3fa91d42aeea44458e2bf">00339</a>                 <span class="keywordtype">double</span> <a class="code" href="classbdm_1_1multiBM.html#e157b607c1e3fa91d42aeea44458e2bf">logpred</a> (<span class="keyword">const</span> vec &amp;dt)<span class="keyword"> const </span>{
+<a name="l00340"></a>00340                         <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>);
+<a name="l00341"></a>00341                         vec &amp;<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>();
+<a name="l00342"></a>00342 
+<a name="l00343"></a>00343                         <span class="keywordtype">double</span> lll;
+<a name="l00344"></a>00344                         <span class="keywordflow">if</span> (<a class="code" href="classbdm_1_1BMEF.html#1331865e10fb1ccef65bb4c47fa3be64" title="forgetting factor">frg</a> &lt; 1.0)
+<a name="l00345"></a>00345                                 {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>();}
+<a name="l00346"></a>00346                         <span class="keywordflow">else</span>
+<a name="l00347"></a>00347                                 <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>;}
+<a name="l00348"></a>00348                                 <span class="keywordflow">else</span>{lll = pred.<a class="code" href="classbdm_1_1eDirich.html#279a99f6266c82fe2273e83841f19eb2" title="logarithm of the normalizing constant, ">lognc</a>();}
 <a name="l00349"></a>00349 
-<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>
-<a name="l00360"></a>00360 {
-<a name="l00361"></a>00361         <span class="keyword">protected</span>:
-<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>;
-<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>;
-<a name="l00366"></a>00366         <span class="keyword">public</span> :
-<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) {};
-<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 &amp;a, <span class="keyword">const</span> vec &amp;b) {set_parameters (a, b);};
-<a name="l00371"></a>00371                 <span class="keywordtype">void</span> set_parameters (<span class="keyword">const</span> vec &amp;a, <span class="keyword">const</span> vec &amp;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();};
-<a name="l00373"></a>00373 
-<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>;
-<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 &amp;val) <span class="keyword">const</span>;
-<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>;
-<a name="l00378"></a><a class="code" href="classbdm_1_1egamma.html#0865cb3d6339fdc7410806cf70a329ed">00378</a>                 vec&amp; <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>;}
-<a name="l00380"></a><a class="code" href="classbdm_1_1egamma.html#c42cadd9cbd344caaa69b0b433cd16ca">00380</a>                 vec&amp; <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;}
-<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);}
-<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)); }
-<a name="l00383"></a>00383 
-<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 &amp;<span class="keyword">set</span>) {
-<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>
-<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);
-<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);
-<a name="l00396"></a>00396                         <a class="code" href="classbdm_1_1egamma.html#c3a8d8ae8ba79d0fb35036711fa7d127" title="This method TODO.">validate</a>();
-<a name="l00397"></a>00397                 }
-<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>() {
-<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>);
-<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();
-<a name="l00401"></a>00401                 }
-<a name="l00402"></a>00402 };
-<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);
-<a name="l00404"></a>00404 SHAREDPTR ( egamma );
-<a name="l00405"></a>00405 
-<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>
-<a name="l00423"></a>00423 {
-<a name="l00424"></a>00424         <span class="keyword">protected</span>:
-<a name="l00425"></a>00425         <span class="keyword">public</span> :
-<a name="l00430"></a>00430 
-<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>();};
-<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);}
-<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);}
-<a name="l00435"></a>00435 };
-<a name="l00436"></a>00436 <span class="comment">/*</span>
-<a name="l00438"></a>00438 <span class="comment">class emix : public epdf {</span>
-<a name="l00439"></a>00439 <span class="comment">protected:</span>
-<a name="l00440"></a>00440 <span class="comment">        int n;</span>
-<a name="l00441"></a>00441 <span class="comment">        vec &amp;w;</span>
-<a name="l00442"></a>00442 <span class="comment">        Array&lt;epdf*&gt; Coms;</span>
-<a name="l00443"></a>00443 <span class="comment">public:</span>
-<a name="l00445"></a>00445 <span class="comment">        emix ( const RV &amp;rv, vec &amp;w0): epdf(rv), n(w0.length()), w(w0), Coms(n) {};</span>
-<a name="l00446"></a>00446 <span class="comment">        void set_parameters( int &amp;i, double wi, epdf* ep){w(i)=wi;Coms(i)=ep;}</span>
-<a name="l00447"></a>00447 <span class="comment">        vec mean(){vec pom; for(int i=0;i&lt;n;i++){pom+=Coms(i)-&gt;mean()*w(i);} return pom;};</span>
-<a name="l00448"></a>00448 <span class="comment">        vec sample() {it_error ( "Not implemented" );return 0;}</span>
-<a name="l00449"></a>00449 <span class="comment">};</span>
-<a name="l00450"></a>00450 <span class="comment">*/</span>
-<a name="l00451"></a>00451 
-<a name="l00453"></a>00453 
-<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>
-<a name="l00455"></a>00455 {
-<a name="l00456"></a>00456         <span class="keyword">protected</span>:
-<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>;
-<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>;
-<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>;
-<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>;
-<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>;
-<a name="l00467"></a>00467         <span class="keyword">public</span>:
-<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> () {}
-<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 &amp;low0, <span class="keyword">const</span> vec &amp;high0) {set_parameters (low0, high0);}
-<a name="l00472"></a>00472                 <span class="keywordtype">void</span> set_parameters (<span class="keyword">const</span> vec &amp;low0, <span class="keyword">const</span> vec &amp;high0) {
-<a name="l00473"></a>00473                         <a class="code" href="classbdm_1_1euni.html#d3c27e331f90c754d80228108de8ed4c" title="internal">distance</a> = high0 - low0;
-<a name="l00474"></a>00474                         it_assert_debug (min (<a class="code" href="classbdm_1_1euni.html#d3c27e331f90c754d80228108de8ed4c" title="internal">distance</a>) &gt; 0.0, <span class="stringliteral">"bad support"</span>);
-<a name="l00475"></a>00475                         <a class="code" href="classbdm_1_1euni.html#ff7ce6a2ef5ef0015bbd1398bed12f32" title="lower bound on support">low</a> = low0;
-<a name="l00476"></a>00476                         <a class="code" href="classbdm_1_1euni.html#cfad2dea4a62db6872bda8abd75f0de1" title="upper bound on support">high</a> = high0;
-<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>);
-<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>);
-<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();
-<a name="l00480"></a>00480                 }
-<a name="l00482"></a>00482 
-<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 &amp;val)<span class="keyword"> const  </span>{
-<a name="l00484"></a>00484                         <span class="keywordflow">if</span> (any (val &lt; <a class="code" href="classbdm_1_1euni.html#ff7ce6a2ef5ef0015bbd1398bed12f32" title="lower bound on support">low</a>) &amp;&amp; any (val &gt; <a class="code" href="classbdm_1_1euni.html#cfad2dea4a62db6872bda8abd75f0de1" title="upper bound on support">high</a>)) {<span class="keywordflow">return</span> inf;}
-<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>;
-<a name="l00486"></a>00486                 }
-<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>{
-<a name="l00488"></a>00488                         vec smp (<a class="code" href="classbdm_1_1epdf.html#16adac20ec7fe07e1ea0b27d917788ce" title="dimension of the random variable">dim</a>);
-<a name="l00489"></a>00489 <span class="preprocessor">#pragma omp critical</span>
-<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);
-<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);
-<a name="l00492"></a>00492                 }
-<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;}
-<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;}
-<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 &amp;<span class="keyword">set</span>) {
-<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>
-<a name="l00506"></a>00506 
-<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);
-<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);
-<a name="l00509"></a>00509                 }
-<a name="l00510"></a>00510 };
-<a name="l00511"></a>00511 
-<a name="l00512"></a>00512 
-<a name="l00518"></a>00518 <span class="keyword">template</span> &lt; <span class="keyword">class</span> sq_T, <span class="keyword">template</span> &lt;<span class="keyword">typename</span>&gt; <span class="keyword">class </span>TEpdf = enorm &gt;
-<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>&lt; TEpdf&lt;sq_T&gt; &gt;
-<a name="l00520"></a>00520 {
-<a name="l00521"></a>00521         <span class="keyword">protected</span>:
-<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>;
-<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>;
-<a name="l00526"></a>00526 <span class="comment">//                      vec&amp; _mu; //cached epdf.mu; !!!!!! WHY NOT?</span>
-<a name="l00527"></a>00527         <span class="keyword">public</span>:
-<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>&lt; TEpdf&lt;sq_T&gt; &gt;() {};
-<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 &amp;<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 &amp;mu0, <span class="keyword">const</span> sq_T &amp;R) : <a class="code" href="classbdm_1_1mpdf__internal.html" title="Mpdf with internal epdf that is modified by function condition.">mpdf_internal</a>&lt; TEpdf&lt;sq_T&gt; &gt;() {
-<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);
-<a name="l00533"></a>00533                 }
-<a name="l00534"></a>00534 
-<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 &amp;A0, <span class="keyword">const</span> vec &amp;mu0, <span class="keyword">const</span> sq_T &amp;R0) {
-<a name="l00537"></a>00537                         it_assert_debug (A0.rows() == mu0.length(), <span class="stringliteral">""</span>);
-<a name="l00538"></a>00538                         it_assert_debug (A0.rows() == R0.rows(), <span class="stringliteral">""</span>);
-<a name="l00539"></a>00539 
-<a name="l00540"></a>00540                         this-&gt;<a class="code" href="classbdm_1_1mpdf__internal.html#47bab632af15120c88aad647ae129468" title="Internal epdf used for sampling.">iepdf</a>.set_parameters (zeros (A0.rows()), R0);
-<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;
-<a name="l00542"></a>00542                         <a class="code" href="classbdm_1_1mlnorm.html#831b50121cad10aa03a16682bd0c3ed6" title="Constant additive term.">mu_const</a> = mu0;
-<a name="l00543"></a>00543                         this-&gt;<a class="code" href="classbdm_1_1mpdf.html#7c1900976ff13dbc09c9729b3bbff9e6" title="dimension of the condition">dimc</a> = A0.cols();
-<a name="l00544"></a>00544                 }
-<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 &amp;cond) {
-<a name="l00548"></a>00548                         this-&gt;<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>;
-<a name="l00549"></a>00549 <span class="comment">//R is already assigned;</span>
-<a name="l00550"></a>00550                 }
-<a name="l00551"></a>00551 
-<a name="l00553"></a><a class="code" href="classbdm_1_1mlnorm.html#6332e5200f3afa15db3f7f4bca09b17f">00553</a>                 vec&amp; <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>;}
-<a name="l00555"></a><a class="code" href="classbdm_1_1mlnorm.html#b256b547c5156b5898a3a1e5462f9540">00555</a>                 mat&amp; <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>;}
-<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-&gt;<a class="code" href="classbdm_1_1mpdf__internal.html#47bab632af15120c88aad647ae129468" title="Internal epdf used for sampling.">iepdf</a>._R().to_mat(); }
-<a name="l00558"></a>00558 
-<a name="l00560"></a>00560                 <span class="keyword">template</span>&lt;<span class="keyword">typename</span> sq_M&gt;
-<a name="l00561"></a>00561                 <span class="keyword">friend</span> std::ostream &amp;operator&lt;&lt; (std::ostream &amp;os,  mlnorm&lt;sq_M, enorm&gt; &amp;ml);
-<a name="l00562"></a>00562 
-<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 &amp;<span class="keyword">set</span>) {
-<a name="l00564"></a>00564                         <a class="code" href="classbdm_1_1mlnorm.html#52980f13d80162d00b30d5864343f564">mpdf::from_setting</a> (<span class="keyword">set</span>);
-<a name="l00565"></a>00565 
-<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);
-<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);
-<a name="l00568"></a>00568                         mat R0;
-<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);
-<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);
-<a name="l00571"></a>00571                 };
-<a name="l00572"></a>00572 };
-<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);
-<a name="l00574"></a>00574 SHAREDPTR2 ( mlnorm, ldmat );
-<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);
-<a name="l00576"></a>00576 SHAREDPTR2 ( mlnorm, fsqmat );
-<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);
-<a name="l00578"></a>00578 SHAREDPTR2 ( mlnorm, chmat );
-<a name="l00579"></a>00579 
-<a name="l00581"></a>00581 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt;
-<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>&lt; enorm&lt; sq_T &gt; &gt;
-<a name="l00583"></a>00583 {
-<a name="l00584"></a>00584         <span class="keyword">private</span>:
-<a name="l00585"></a>00585 <span class="comment">//                      vec &amp;mu; WHY NOT?</span>
-<a name="l00586"></a>00586                 <a class="code" href="classbdm_1_1shared__ptr.html">shared_ptr&lt;fnc&gt;</a> g;
-<a name="l00587"></a>00587 
-<a name="l00588"></a>00588         <span class="keyword">public</span>:
-<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>&lt;<a class="code" href="classbdm_1_1enorm.html" title="Gaussian density with positive definite (decomposed) covariance matrix.">enorm</a>&lt;sq_T&gt; &gt;() { }
-<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&lt;fnc&gt;</a> &amp;g0, <span class="keyword">const</span> sq_T &amp;R0);
-<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 &amp;cond);
-<a name="l00594"></a>00594 
-<a name="l00595"></a>00595 
-<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 &amp;<span class="keyword">set</span>) {
-<a name="l00624"></a>00624                         <a class="code" href="classbdm_1_1shared__ptr.html">shared_ptr&lt;fnc&gt;</a> g = UI::build&lt;fnc&gt; (<span class="keyword">set</span>, <span class="stringliteral">"g"</span>, UI::compulsory);
-<a name="l00625"></a>00625 
-<a name="l00626"></a>00626                         mat R;
-<a name="l00627"></a>00627                         vec dR;
-<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>))
-<a name="l00629"></a>00629                                 R = diag (dR);
-<a name="l00630"></a>00630                         <span class="keywordflow">else</span>
-<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);
-<a name="l00632"></a>00632 
-<a name="l00633"></a>00633                         <a class="code" href="classbdm_1_1mgnorm.html#b736332d20e418bf50d45836e129f339" title="set mean function">set_parameters</a> (g, R);
-<a name="l00634"></a>00634                 }
-<a name="l00635"></a>00635 };
-<a name="l00636"></a>00636 
-<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);
-<a name="l00638"></a>00638 SHAREDPTR2 ( mgnorm, chmat );
-<a name="l00639"></a>00639 
-<a name="l00640"></a>00640 
-<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>&lt;ldmat, enorm&gt;
-<a name="l00649"></a>00649 {
-<a name="l00650"></a>00650         <span class="keyword">protected</span>:
-<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>;
-<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> &amp;<a class="code" href="classbdm_1_1mlnorm.html#564715dea56f7bbff0083aec295ce97e" title="access function">_R</a>;
-<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>;
-<a name="l00657"></a>00657         <span class="keyword">public</span>:
-<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>&lt;<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>&gt; (),
-<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>()) {}
-<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 &amp;A0, <span class="keyword">const</span> vec &amp;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> &amp;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>&amp; Lambda0) {
-<a name="l00662"></a>00662                         it_assert_debug (A0.rows() == mu0.length(), <span class="stringliteral">""</span>);
-<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>);
-<a name="l00664"></a>00664 
-<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>
-<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;
-<a name="l00667"></a>00667                         <a class="code" href="classbdm_1_1mlnorm.html#831b50121cad10aa03a16682bd0c3ed6" title="Constant additive term.">mu_const</a> = mu0;
-<a name="l00668"></a>00668                         <a class="code" href="classbdm_1_1mlstudent.html#1c063ad6cb6e079ee11bc4128c2c9fe8" title="Variable .">Re</a> = R0;
-<a name="l00669"></a>00669                         <a class="code" href="classbdm_1_1mlstudent.html#41595144a79594acbe288c6b59412657" title="Variable  from theory.">Lambda</a> = Lambda0;
-<a name="l00670"></a>00670                 }
-<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 &amp;cond) {
-<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>;
-<a name="l00673"></a>00673                         <span class="keywordtype">double</span> zeta;
-<a name="l00674"></a>00674                         <span class="comment">//ugly hack!</span>
-<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>()) {
-<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)));
-<a name="l00677"></a>00677                         } <span class="keywordflow">else</span> {
-<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);
-<a name="l00679"></a>00679                         }
-<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>;
-<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 ); &lt;&lt; nu is in Re!!!!!!</span>
-<a name="l00682"></a>00682                 };
-<a name="l00683"></a>00683 
-<a name="l00684"></a>00684 };
-<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>&lt;egamma&gt;
-<a name="l00695"></a>00695 {
-<a name="l00696"></a>00696         <span class="keyword">protected</span>:
-<a name="l00697"></a>00697 
-<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>;
-<a name="l00700"></a>00700 
-<a name="l00702"></a><a class="code" href="classbdm_1_1mgamma.html#3d95f4dde9214ff6dba265e18af60312">00702</a>                 vec &amp;<a class="code" href="classbdm_1_1mgamma.html#3d95f4dde9214ff6dba265e18af60312" title="cache of iepdf.beta">_beta</a>;
-<a name="l00703"></a>00703 
-<a name="l00704"></a>00704         <span class="keyword">public</span>:
-<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>&lt;<a class="code" href="classbdm_1_1egamma.html" title="Gamma posterior density.">egamma</a>&gt;(), <a class="code" href="classbdm_1_1mgamma.html#b20cf88cca1fe9b0b8f2a412608bfd09" title="Constant .">k</a> (0),
-<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>()) {
-<a name="l00708"></a>00708                 }
-<a name="l00709"></a>00709 
-<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 &amp;beta0);
-<a name="l00712"></a>00712 
-<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 &amp;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;};
-<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 &amp;<span class="keyword">set</span>) {
-<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>
-<a name="l00725"></a>00725                         vec betatmp; <span class="comment">// ugly but necessary</span>
-<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);
-<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);
-<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);
-<a name="l00729"></a>00729                 }
-<a name="l00730"></a>00730 };
-<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);
-<a name="l00732"></a>00732 SHAREDPTR (mgamma);
-<a name="l00733"></a>00733 
-<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>&lt;eigamma&gt;
-<a name="l00744"></a>00744 {
-<a name="l00745"></a>00745         <span class="keyword">protected</span>:
-<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>;
-<a name="l00748"></a>00748 
-<a name="l00750"></a><a class="code" href="classbdm_1_1migamma.html#c9847093da59a9ba0ebb68d2c592f5dc">00750</a>                 vec &amp;<a class="code" href="classbdm_1_1migamma.html#c9847093da59a9ba0ebb68d2c592f5dc" title="cache of iepdf.alpha">_alpha</a>;
+<a name="l00350"></a>00350                         beta += dt;
+<a name="l00351"></a>00351                         <span class="keywordflow">return</span> pred.<a class="code" href="classbdm_1_1eDirich.html#279a99f6266c82fe2273e83841f19eb2" title="logarithm of the normalizing constant, ">lognc</a>() - lll;
+<a name="l00352"></a>00352                 }
+<a name="l00353"></a><a class="code" href="classbdm_1_1multiBM.html#aaeb18c989088feb8d26d300e4971732">00353</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) {
+<a name="l00354"></a>00354                         <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&lt;</span><span class="keyword">const </span><a class="code" href="classbdm_1_1multiBM.html" title="Estimator for Multinomial density.">multiBM</a>*<span class="keyword">&gt;</span> (B);
+<a name="l00355"></a>00355                         <span class="comment">// sum(beta) should be equal to sum(B.beta)</span>
+<a name="l00356"></a>00356                         <span class="keyword">const</span> vec &amp;Eb = E-&gt;<a class="code" href="classbdm_1_1multiBM.html#044263356944c92209eecd39a5187d25" title="Pointer inside est to sufficient statistics.">beta</a>;<span class="comment">//const_cast&lt;multiBM*&gt; ( E )-&gt;_beta();</span>
+<a name="l00357"></a>00357                         <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>));
+<a name="l00358"></a>00358                         <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>();}
+<a name="l00359"></a>00359                 }
+<a name="l00361"></a><a class="code" href="classbdm_1_1multiBM.html#31ff93f89473f099e489b9e1dc8d9513">00361</a>                 <span class="keyword">const</span> <a class="code" href="classbdm_1_1eDirich.html" title="Dirichlet posterior density.">eDirich</a>&amp; <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>;};
+<a name="l00363"></a><a class="code" href="classbdm_1_1multiBM.html#7a480eace4446661bacca94c57499f01">00363</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 &amp;beta0) {
+<a name="l00364"></a>00364                         <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);
+<a name="l00365"></a>00365                         <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>();}
+<a name="l00366"></a>00366                 }
+<a name="l00367"></a>00367 };
+<a name="l00368"></a>00368 
+<a name="l00378"></a><a class="code" href="classbdm_1_1egamma.html">00378</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>
+<a name="l00379"></a>00379 {
+<a name="l00380"></a>00380         <span class="keyword">protected</span>:
+<a name="l00382"></a><a class="code" href="classbdm_1_1egamma.html#0901ec983e66b8337aaa506e13b122fa">00382</a>                 vec <a class="code" href="classbdm_1_1egamma.html#0901ec983e66b8337aaa506e13b122fa" title="Vector .">alpha</a>;
+<a name="l00384"></a><a class="code" href="classbdm_1_1egamma.html#457bfb1ccb2057df85073e519a15ccc1">00384</a>                 vec <a class="code" href="classbdm_1_1egamma.html#457bfb1ccb2057df85073e519a15ccc1" title="Vector .">beta</a>;
+<a name="l00385"></a>00385         <span class="keyword">public</span> :
+<a name="l00388"></a>00388                 <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) {};
+<a name="l00389"></a>00389                 <a class="code" href="classbdm_1_1egamma.html" title="Gamma posterior density.">egamma</a> (<span class="keyword">const</span> vec &amp;a, <span class="keyword">const</span> vec &amp;b) {set_parameters (a, b);};
+<a name="l00390"></a>00390                 <span class="keywordtype">void</span> set_parameters (<span class="keyword">const</span> vec &amp;a, <span class="keyword">const</span> vec &amp;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();};
+<a name="l00392"></a>00392 
+<a name="l00393"></a>00393                 vec <a class="code" href="classbdm_1_1egamma.html#6ed82f0fd05f6002487256d8e75a0bbd" title="Returns a sample,  from density .">sample</a>() <span class="keyword">const</span>;
+<a name="l00394"></a>00394                 <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 &amp;val) <span class="keyword">const</span>;
+<a name="l00395"></a>00395                 <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>;
+<a name="l00397"></a><a class="code" href="classbdm_1_1egamma.html#0865cb3d6339fdc7410806cf70a329ed">00397</a>                 vec&amp; <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>;}
+<a name="l00399"></a><a class="code" href="classbdm_1_1egamma.html#c42cadd9cbd344caaa69b0b433cd16ca">00399</a>                 vec&amp; <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;}
+<a name="l00400"></a><a class="code" href="classbdm_1_1egamma.html#49d256c42cce14c6faa56ec242b57e85">00400</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);}
+<a name="l00401"></a><a class="code" href="classbdm_1_1egamma.html#36986cc01917cd0796fadc17125bdec1">00401</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)); }
+<a name="l00402"></a>00402 
+<a name="l00411"></a><a class="code" href="classbdm_1_1egamma.html#8a6fd1a1c0190f3e0d95a2a1f99aafc1">00411</a>                 <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1egamma.html#8a6fd1a1c0190f3e0d95a2a1f99aafc1">from_setting</a> (<span class="keyword">const</span> Setting &amp;<span class="keyword">set</span>) {
+<a name="l00412"></a>00412                         <a class="code" href="classbdm_1_1egamma.html#8a6fd1a1c0190f3e0d95a2a1f99aafc1">epdf::from_setting</a> (<span class="keyword">set</span>); <span class="comment">// reads rv</span>
+<a name="l00413"></a>00413                         <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);
+<a name="l00414"></a>00414                         <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);
+<a name="l00415"></a>00415                         <a class="code" href="classbdm_1_1egamma.html#c3a8d8ae8ba79d0fb35036711fa7d127" title="This method TODO.">validate</a>();
+<a name="l00416"></a>00416                 }
+<a name="l00417"></a><a class="code" href="classbdm_1_1egamma.html#c3a8d8ae8ba79d0fb35036711fa7d127">00417</a>                 <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1egamma.html#c3a8d8ae8ba79d0fb35036711fa7d127" title="This method TODO.">validate</a>() {
+<a name="l00418"></a>00418                         <a class="code" href="bdmerror_8h.html#89a0f906b242b79c5d3d342291b2cab4" title="Throw std::runtime_exception if t is not true and NDEBUG is not defined.">bdm_assert_debug</a> (<a class="code" href="classbdm_1_1egamma.html#0901ec983e66b8337aaa506e13b122fa" title="Vector .">alpha</a>.length() == beta.length(), <span class="stringliteral">"parameters do not match"</span>);
+<a name="l00419"></a>00419                         <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();
+<a name="l00420"></a>00420                 }
+<a name="l00421"></a>00421 };
+<a name="l00422"></a>00422 <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);
+<a name="l00423"></a>00423 SHAREDPTR ( egamma );
+<a name="l00424"></a>00424 
+<a name="l00441"></a><a class="code" href="classbdm_1_1eigamma.html">00441</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>
+<a name="l00442"></a>00442 {
+<a name="l00443"></a>00443         <span class="keyword">protected</span>:
+<a name="l00444"></a>00444         <span class="keyword">public</span> :
+<a name="l00449"></a>00449 
+<a name="l00450"></a><a class="code" href="classbdm_1_1eigamma.html#3aff7bf25ddac27731c60826fcfd878f">00450</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>();};
+<a name="l00452"></a><a class="code" href="classbdm_1_1eigamma.html#46cecb295edbabd28120cb0f6f572bcb">00452</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);}
+<a name="l00453"></a><a class="code" href="classbdm_1_1eigamma.html#c2c696f8c668e9f65392c9449f6a5133">00453</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);}
+<a name="l00454"></a>00454 };
+<a name="l00455"></a>00455 <span class="comment">/*</span>
+<a name="l00457"></a>00457 <span class="comment">class emix : public epdf {</span>
+<a name="l00458"></a>00458 <span class="comment">protected:</span>
+<a name="l00459"></a>00459 <span class="comment">        int n;</span>
+<a name="l00460"></a>00460 <span class="comment">        vec &amp;w;</span>
+<a name="l00461"></a>00461 <span class="comment">        Array&lt;epdf*&gt; Coms;</span>
+<a name="l00462"></a>00462 <span class="comment">public:</span>
+<a name="l00464"></a>00464 <span class="comment">        emix ( const RV &amp;rv, vec &amp;w0): epdf(rv), n(w0.length()), w(w0), Coms(n) {};</span>
+<a name="l00465"></a>00465 <span class="comment">        void set_parameters( int &amp;i, double wi, epdf* ep){w(i)=wi;Coms(i)=ep;}</span>
+<a name="l00466"></a>00466 <span class="comment">        vec mean(){vec pom; for(int i=0;i&lt;n;i++){pom+=Coms(i)-&gt;mean()*w(i);} return pom;};</span>
+<a name="l00467"></a>00467 <span class="comment">};</span>
+<a name="l00468"></a>00468 <span class="comment">*/</span>
+<a name="l00469"></a>00469 
+<a name="l00471"></a>00471 
+<a name="l00472"></a><a class="code" href="classbdm_1_1euni.html">00472</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>
+<a name="l00473"></a>00473 {
+<a name="l00474"></a>00474         <span class="keyword">protected</span>:
+<a name="l00476"></a><a class="code" href="classbdm_1_1euni.html#ff7ce6a2ef5ef0015bbd1398bed12f32">00476</a>                 vec <a class="code" href="classbdm_1_1euni.html#ff7ce6a2ef5ef0015bbd1398bed12f32" title="lower bound on support">low</a>;
+<a name="l00478"></a><a class="code" href="classbdm_1_1euni.html#cfad2dea4a62db6872bda8abd75f0de1">00478</a>                 vec <a class="code" href="classbdm_1_1euni.html#cfad2dea4a62db6872bda8abd75f0de1" title="upper bound on support">high</a>;
+<a name="l00480"></a><a class="code" href="classbdm_1_1euni.html#d3c27e331f90c754d80228108de8ed4c">00480</a>                 vec <a class="code" href="classbdm_1_1euni.html#d3c27e331f90c754d80228108de8ed4c" title="internal">distance</a>;
+<a name="l00482"></a><a class="code" href="classbdm_1_1euni.html#31bb13e8449a8eff35246d46dae35c20">00482</a>                 <span class="keywordtype">double</span> <a class="code" href="classbdm_1_1euni.html#31bb13e8449a8eff35246d46dae35c20" title="normalizing coefficients">nk</a>;
+<a name="l00484"></a><a class="code" href="classbdm_1_1euni.html#3e63be48dd58659663ca60cd18700476">00484</a>                 <span class="keywordtype">double</span> <a class="code" href="classbdm_1_1euni.html#3e63be48dd58659663ca60cd18700476" title="cache of log( nk )">lnk</a>;
+<a name="l00485"></a>00485         <span class="keyword">public</span>:
+<a name="l00488"></a>00488                 <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> () {}
+<a name="l00489"></a>00489                 <a class="code" href="classbdm_1_1euni.html" title="Uniform distributed density on a rectangular support.">euni</a> (<span class="keyword">const</span> vec &amp;low0, <span class="keyword">const</span> vec &amp;high0) {set_parameters (low0, high0);}
+<a name="l00490"></a>00490                 <span class="keywordtype">void</span> set_parameters (<span class="keyword">const</span> vec &amp;low0, <span class="keyword">const</span> vec &amp;high0) {
+<a name="l00491"></a>00491                         <a class="code" href="classbdm_1_1euni.html#d3c27e331f90c754d80228108de8ed4c" title="internal">distance</a> = high0 - low0;
+<a name="l00492"></a>00492                         <a class="code" href="bdmerror_8h.html#89a0f906b242b79c5d3d342291b2cab4" title="Throw std::runtime_exception if t is not true and NDEBUG is not defined.">bdm_assert_debug</a> (min (<a class="code" href="classbdm_1_1euni.html#d3c27e331f90c754d80228108de8ed4c" title="internal">distance</a>) &gt; 0.0, <span class="stringliteral">"bad support"</span>);
+<a name="l00493"></a>00493                         <a class="code" href="classbdm_1_1euni.html#ff7ce6a2ef5ef0015bbd1398bed12f32" title="lower bound on support">low</a> = low0;
+<a name="l00494"></a>00494                         <a class="code" href="classbdm_1_1euni.html#cfad2dea4a62db6872bda8abd75f0de1" title="upper bound on support">high</a> = high0;
+<a name="l00495"></a>00495                         <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>);
+<a name="l00496"></a>00496                         <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>);
+<a name="l00497"></a>00497                         <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();
+<a name="l00498"></a>00498                 }
+<a name="l00500"></a>00500 
+<a name="l00501"></a><a class="code" href="classbdm_1_1euni.html#caa07b8307bd793d5339d6583e0aba81">00501</a>                 <span class="keywordtype">double</span> <a class="code" href="classbdm_1_1euni.html#caa07b8307bd793d5339d6583e0aba81">evallog</a> (<span class="keyword">const</span> vec &amp;val)<span class="keyword"> const  </span>{
+<a name="l00502"></a>00502                         <span class="keywordflow">if</span> (any (val &lt; <a class="code" href="classbdm_1_1euni.html#ff7ce6a2ef5ef0015bbd1398bed12f32" title="lower bound on support">low</a>) &amp;&amp; any (val &gt; <a class="code" href="classbdm_1_1euni.html#cfad2dea4a62db6872bda8abd75f0de1" title="upper bound on support">high</a>)) {<span class="keywordflow">return</span> inf;}
+<a name="l00503"></a>00503                         <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>;
+<a name="l00504"></a>00504                 }
+<a name="l00505"></a><a class="code" href="classbdm_1_1euni.html#fc5df80359ead2918384b2004ce67194">00505</a>                 vec <a class="code" href="classbdm_1_1euni.html#fc5df80359ead2918384b2004ce67194" title="Returns a sample,  from density .">sample</a>()<span class="keyword"> const </span>{
+<a name="l00506"></a>00506                         vec smp (<a class="code" href="classbdm_1_1epdf.html#16adac20ec7fe07e1ea0b27d917788ce" title="dimension of the random variable">dim</a>);
+<a name="l00507"></a>00507 <span class="preprocessor">#pragma omp critical</span>
+<a name="l00508"></a>00508 <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);
+<a name="l00509"></a>00509                         <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);
+<a name="l00510"></a>00510                 }
+<a name="l00512"></a><a class="code" href="classbdm_1_1euni.html#46caa8c13aba2e6228f964208918b226">00512</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;}
+<a name="l00513"></a><a class="code" href="classbdm_1_1euni.html#951f932155111f6053c980f672b4c22c">00513</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;}
+<a name="l00522"></a><a class="code" href="classbdm_1_1euni.html#77f5fef1f006fe056066da23b9e5f042">00522</a>                 <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1euni.html#77f5fef1f006fe056066da23b9e5f042">from_setting</a> (<span class="keyword">const</span> Setting &amp;<span class="keyword">set</span>) {
+<a name="l00523"></a>00523                         <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>
+<a name="l00524"></a>00524 
+<a name="l00525"></a>00525                         <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);
+<a name="l00526"></a>00526                         <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);
+<a name="l00527"></a>00527                 }
+<a name="l00528"></a>00528 };
+<a name="l00529"></a>00529 
+<a name="l00530"></a>00530 
+<a name="l00536"></a>00536 <span class="keyword">template</span> &lt; <span class="keyword">class</span> sq_T, <span class="keyword">template</span> &lt;<span class="keyword">typename</span>&gt; <span class="keyword">class </span>TEpdf = enorm &gt;
+<a name="l00537"></a><a class="code" href="classbdm_1_1mlnorm.html">00537</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>&lt; TEpdf&lt;sq_T&gt; &gt;
+<a name="l00538"></a>00538 {
+<a name="l00539"></a>00539         <span class="keyword">protected</span>:
+<a name="l00541"></a><a class="code" href="classbdm_1_1mlnorm.html#c71bbf59fc732beb2b459d7117bd6e42">00541</a>                 mat <a class="code" href="classbdm_1_1mlnorm.html#c71bbf59fc732beb2b459d7117bd6e42" title="Internal epdf that arise by conditioning on rvc.">A</a>;
+<a name="l00543"></a><a class="code" href="classbdm_1_1mlnorm.html#831b50121cad10aa03a16682bd0c3ed6">00543</a>                 vec <a class="code" href="classbdm_1_1mlnorm.html#831b50121cad10aa03a16682bd0c3ed6" title="Constant additive term.">mu_const</a>;
+<a name="l00544"></a>00544 <span class="comment">//                      vec&amp; _mu; //cached epdf.mu; !!!!!! WHY NOT?</span>
+<a name="l00545"></a>00545         <span class="keyword">public</span>:
+<a name="l00548"></a>00548                 <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>&lt; TEpdf&lt;sq_T&gt; &gt;() {};
+<a name="l00549"></a>00549                 <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 &amp;<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 &amp;mu0, <span class="keyword">const</span> sq_T &amp;R) : <a class="code" href="classbdm_1_1mpdf__internal.html" title="Mpdf with internal epdf that is modified by function condition.">mpdf_internal</a>&lt; TEpdf&lt;sq_T&gt; &gt;() {
+<a name="l00550"></a>00550                         <a class="code" href="classbdm_1_1mlnorm.html#04f7c6cda7b2f95161dd5fbcf15d1fd5" title="Set A and R.">set_parameters</a> (A, mu0, R);
+<a name="l00551"></a>00551                 }
+<a name="l00552"></a>00552 
+<a name="l00554"></a><a class="code" href="classbdm_1_1mlnorm.html#04f7c6cda7b2f95161dd5fbcf15d1fd5">00554</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 &amp;A0, <span class="keyword">const</span> vec &amp;mu0, <span class="keyword">const</span> sq_T &amp;R0) {
+<a name="l00555"></a>00555                         <a class="code" href="bdmerror_8h.html#89a0f906b242b79c5d3d342291b2cab4" title="Throw std::runtime_exception if t is not true and NDEBUG is not defined.">bdm_assert_debug</a> (A0.rows() == mu0.length(), <span class="stringliteral">"mlnorm: A vs. mu mismatch"</span>);
+<a name="l00556"></a>00556                         <a class="code" href="bdmerror_8h.html#89a0f906b242b79c5d3d342291b2cab4" title="Throw std::runtime_exception if t is not true and NDEBUG is not defined.">bdm_assert_debug</a> (A0.rows() == R0.rows(), <span class="stringliteral">"mlnorm: A vs. R mismatch"</span>);
+<a name="l00557"></a>00557 
+<a name="l00558"></a>00558                         this-&gt;<a class="code" href="classbdm_1_1mpdf__internal.html#47bab632af15120c88aad647ae129468" title="Internal epdf used for sampling.">iepdf</a>.set_parameters (zeros (A0.rows()), R0);
+<a name="l00559"></a>00559                         <a class="code" href="classbdm_1_1mlnorm.html#c71bbf59fc732beb2b459d7117bd6e42" title="Internal epdf that arise by conditioning on rvc.">A</a> = A0;
+<a name="l00560"></a>00560                         <a class="code" href="classbdm_1_1mlnorm.html#831b50121cad10aa03a16682bd0c3ed6" title="Constant additive term.">mu_const</a> = mu0;
+<a name="l00561"></a>00561                         this-&gt;<a class="code" href="classbdm_1_1mpdf.html#7c1900976ff13dbc09c9729b3bbff9e6" title="dimension of the condition">dimc</a> = A0.cols();
+<a name="l00562"></a>00562                 }
+<a name="l00565"></a><a class="code" href="classbdm_1_1mlnorm.html#c2895ae549ee76d961be98d7061bd110">00565</a>                 <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1mlnorm.html#c2895ae549ee76d961be98d7061bd110">condition</a> (<span class="keyword">const</span> vec &amp;cond) {
+<a name="l00566"></a>00566                         this-&gt;<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>;
+<a name="l00567"></a>00567 <span class="comment">//R is already assigned;</span>
+<a name="l00568"></a>00568                 }
+<a name="l00569"></a>00569 
+<a name="l00571"></a><a class="code" href="classbdm_1_1mlnorm.html#6332e5200f3afa15db3f7f4bca09b17f">00571</a>                 vec&amp; <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>;}
+<a name="l00573"></a><a class="code" href="classbdm_1_1mlnorm.html#b256b547c5156b5898a3a1e5462f9540">00573</a>                 mat&amp; <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>;}
+<a name="l00575"></a><a class="code" href="classbdm_1_1mlnorm.html#564715dea56f7bbff0083aec295ce97e">00575</a>                 mat <a class="code" href="classbdm_1_1mlnorm.html#564715dea56f7bbff0083aec295ce97e" title="access function">_R</a>() { <span class="keywordflow">return</span> this-&gt;<a class="code" href="classbdm_1_1mpdf__internal.html#47bab632af15120c88aad647ae129468" title="Internal epdf used for sampling.">iepdf</a>._R().to_mat(); }
+<a name="l00576"></a>00576 
+<a name="l00578"></a>00578                 <span class="keyword">template</span>&lt;<span class="keyword">typename</span> sq_M&gt;
+<a name="l00579"></a>00579                 <span class="keyword">friend</span> std::ostream &amp;operator&lt;&lt; (std::ostream &amp;os,  mlnorm&lt;sq_M, enorm&gt; &amp;ml);
+<a name="l00580"></a>00580 
+<a name="l00581"></a><a class="code" href="classbdm_1_1mlnorm.html#52980f13d80162d00b30d5864343f564">00581</a>                 <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1mlnorm.html#52980f13d80162d00b30d5864343f564">from_setting</a> (<span class="keyword">const</span> Setting &amp;<span class="keyword">set</span>) {
+<a name="l00582"></a>00582                         <a class="code" href="classbdm_1_1mlnorm.html#52980f13d80162d00b30d5864343f564">mpdf::from_setting</a> (<span class="keyword">set</span>);
+<a name="l00583"></a>00583 
+<a name="l00584"></a>00584                         <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);
+<a name="l00585"></a>00585                         <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);
+<a name="l00586"></a>00586                         mat R0;
+<a name="l00587"></a>00587                         <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);
+<a name="l00588"></a>00588                         <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);
+<a name="l00589"></a>00589                 };
+<a name="l00590"></a>00590 };
+<a name="l00591"></a>00591 <a class="code" href="user__info_8h.html#b06f1e7c44a8306e321f62a0099210b9" title="Variant of UIREGISTER for templated classes.">UIREGISTER2</a> (mlnorm,ldmat);
+<a name="l00592"></a>00592 SHAREDPTR2 ( mlnorm, ldmat );
+<a name="l00593"></a>00593 <a class="code" href="user__info_8h.html#b06f1e7c44a8306e321f62a0099210b9" title="Variant of UIREGISTER for templated classes.">UIREGISTER2</a> (mlnorm,fsqmat);
+<a name="l00594"></a>00594 SHAREDPTR2 ( mlnorm, fsqmat );
+<a name="l00595"></a>00595 <a class="code" href="user__info_8h.html#b06f1e7c44a8306e321f62a0099210b9" title="Variant of UIREGISTER for templated classes.">UIREGISTER2</a> (mlnorm, chmat);
+<a name="l00596"></a>00596 SHAREDPTR2 ( mlnorm, chmat );
+<a name="l00597"></a>00597 
+<a name="l00599"></a>00599 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt;
+<a name="l00600"></a><a class="code" href="classbdm_1_1mgnorm.html">00600</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>&lt; enorm&lt; sq_T &gt; &gt;
+<a name="l00601"></a>00601 {
+<a name="l00602"></a>00602         <span class="keyword">private</span>:
+<a name="l00603"></a>00603 <span class="comment">//                      vec &amp;mu; WHY NOT?</span>
+<a name="l00604"></a>00604                 <a class="code" href="classbdm_1_1shared__ptr.html">shared_ptr&lt;fnc&gt;</a> g;
+<a name="l00605"></a>00605 
+<a name="l00606"></a>00606         <span class="keyword">public</span>:
+<a name="l00608"></a><a class="code" href="classbdm_1_1mgnorm.html#1b014915d74470d3efab74e07cacb97d">00608</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>&lt;<a class="code" href="classbdm_1_1enorm.html" title="Gaussian density with positive definite (decomposed) covariance matrix.">enorm</a>&lt;sq_T&gt; &gt;() { }
+<a name="l00610"></a>00610                 <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&lt;fnc&gt;</a> &amp;g0, <span class="keyword">const</span> sq_T &amp;R0);
+<a name="l00611"></a>00611                 <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 &amp;cond);
+<a name="l00612"></a>00612 
+<a name="l00613"></a>00613 
+<a name="l00641"></a><a class="code" href="classbdm_1_1mgnorm.html#d717dacc6a9eb967f8410994dc6dc6f9">00641</a>                 <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1mgnorm.html#d717dacc6a9eb967f8410994dc6dc6f9">from_setting</a> (<span class="keyword">const</span> Setting &amp;<span class="keyword">set</span>) {
+<a name="l00642"></a>00642                         <a class="code" href="classbdm_1_1shared__ptr.html">shared_ptr&lt;fnc&gt;</a> g = UI::build&lt;fnc&gt; (<span class="keyword">set</span>, <span class="stringliteral">"g"</span>, UI::compulsory);
+<a name="l00643"></a>00643 
+<a name="l00644"></a>00644                         mat R;
+<a name="l00645"></a>00645                         vec dR;
+<a name="l00646"></a>00646                         <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>))
+<a name="l00647"></a>00647                                 R = diag (dR);
+<a name="l00648"></a>00648                         <span class="keywordflow">else</span>
+<a name="l00649"></a>00649                                 <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);
+<a name="l00650"></a>00650 
+<a name="l00651"></a>00651                         <a class="code" href="classbdm_1_1mgnorm.html#b736332d20e418bf50d45836e129f339" title="set mean function">set_parameters</a> (g, R);
+<a name="l00652"></a>00652                 }
+<a name="l00653"></a>00653 };
+<a name="l00654"></a>00654 
+<a name="l00655"></a>00655 <a class="code" href="user__info_8h.html#b06f1e7c44a8306e321f62a0099210b9" title="Variant of UIREGISTER for templated classes.">UIREGISTER2</a> (mgnorm, chmat);
+<a name="l00656"></a>00656 SHAREDPTR2 ( mgnorm, chmat );
+<a name="l00657"></a>00657 
+<a name="l00658"></a>00658 
+<a name="l00666"></a><a class="code" href="classbdm_1_1mlstudent.html">00666</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>&lt;ldmat, enorm&gt;
+<a name="l00667"></a>00667 {
+<a name="l00668"></a>00668         <span class="keyword">protected</span>:
+<a name="l00670"></a><a class="code" href="classbdm_1_1mlstudent.html#41595144a79594acbe288c6b59412657">00670</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>;
+<a name="l00672"></a><a class="code" href="classbdm_1_1mlstudent.html#72e9bda4d6684e07faafc4b2192daf39">00672</a>                 <a class="code" href="classbdm_1_1ldmat.html" title="Matrix stored in LD form, (commonly known as UD).">ldmat</a> &amp;<a class="code" href="classbdm_1_1mlnorm.html#564715dea56f7bbff0083aec295ce97e" title="access function">_R</a>;
+<a name="l00674"></a><a class="code" href="classbdm_1_1mlstudent.html#1c063ad6cb6e079ee11bc4128c2c9fe8">00674</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>;
+<a name="l00675"></a>00675         <span class="keyword">public</span>:
+<a name="l00676"></a>00676                 <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>&lt;<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>&gt; (),
+<a name="l00677"></a>00677                                 <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>()) {}
+<a name="l00679"></a><a class="code" href="classbdm_1_1mlstudent.html#4cdf79aac1b2165c0290e73810a0e4a3">00679</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 &amp;A0, <span class="keyword">const</span> vec &amp;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> &amp;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>&amp; Lambda0) {
+<a name="l00680"></a>00680                         <a class="code" href="bdmerror_8h.html#89a0f906b242b79c5d3d342291b2cab4" title="Throw std::runtime_exception if t is not true and NDEBUG is not defined.">bdm_assert_debug</a> (A0.rows() == mu0.length(), <span class="stringliteral">"mlstudent: A vs. mu mismatch"</span>);
+<a name="l00681"></a>00681                         <a class="code" href="bdmerror_8h.html#89a0f906b242b79c5d3d342291b2cab4" title="Throw std::runtime_exception if t is not true and NDEBUG is not defined.">bdm_assert_debug</a> (R0.<a class="code" href="classbdm_1_1sqmat.html#73e639221343dcce76c3305524d67590" title="Reimplementing common functions of mat: rows().">rows</a>() == A0.rows(), <span class="stringliteral">"mlstudent: A vs. R mismatch"</span>);
+<a name="l00682"></a>00682 
+<a name="l00683"></a>00683                         <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, R0);<span class="comment">// was Lambda, why?</span>
+<a name="l00684"></a>00684                         <a class="code" href="classbdm_1_1mlnorm.html#c71bbf59fc732beb2b459d7117bd6e42" title="Internal epdf that arise by conditioning on rvc.">A</a> = A0;
+<a name="l00685"></a>00685                         <a class="code" href="classbdm_1_1mlnorm.html#831b50121cad10aa03a16682bd0c3ed6" title="Constant additive term.">mu_const</a> = mu0;
+<a name="l00686"></a>00686                         <a class="code" href="classbdm_1_1mlstudent.html#1c063ad6cb6e079ee11bc4128c2c9fe8" title="Variable .">Re</a> = R0;
+<a name="l00687"></a>00687                         <a class="code" href="classbdm_1_1mlstudent.html#41595144a79594acbe288c6b59412657" title="Variable  from theory.">Lambda</a> = Lambda0;
+<a name="l00688"></a>00688                 }
+<a name="l00689"></a><a class="code" href="classbdm_1_1mlstudent.html#efd37560585c8613897f30d3c2f58d0d">00689</a>                 <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1mlstudent.html#efd37560585c8613897f30d3c2f58d0d">condition</a> (<span class="keyword">const</span> vec &amp;cond) {
+<a name="l00690"></a>00690                         <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>;
+<a name="l00691"></a>00691                         <span class="keywordtype">double</span> zeta;
+<a name="l00692"></a>00692                         <span class="comment">//ugly hack!</span>
+<a name="l00693"></a>00693                         <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>()) {
+<a name="l00694"></a>00694                                 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)));
+<a name="l00695"></a>00695                         } <span class="keywordflow">else</span> {
+<a name="l00696"></a>00696                                 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);
+<a name="l00697"></a>00697                         }
+<a name="l00698"></a>00698                         <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>;
+<a name="l00699"></a>00699                         <a class="code" href="classbdm_1_1mlnorm.html#564715dea56f7bbff0083aec295ce97e" title="access function">_R</a> *= (1 + zeta);<span class="comment">// / ( nu ); &lt;&lt; nu is in Re!!!!!!</span>
+<a name="l00700"></a>00700                 };
+<a name="l00701"></a>00701 
+<a name="l00702"></a>00702 };
+<a name="l00712"></a><a class="code" href="classbdm_1_1mgamma.html">00712</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>&lt;egamma&gt;
+<a name="l00713"></a>00713 {
+<a name="l00714"></a>00714         <span class="keyword">protected</span>:
+<a name="l00715"></a>00715 
+<a name="l00717"></a><a class="code" href="classbdm_1_1mgamma.html#b20cf88cca1fe9b0b8f2a412608bfd09">00717</a>                 <span class="keywordtype">double</span> <a class="code" href="classbdm_1_1mgamma.html#b20cf88cca1fe9b0b8f2a412608bfd09" title="Constant .">k</a>;
+<a name="l00718"></a>00718 
+<a name="l00720"></a><a class="code" href="classbdm_1_1mgamma.html#3d95f4dde9214ff6dba265e18af60312">00720</a>                 vec &amp;<a class="code" href="classbdm_1_1mgamma.html#3d95f4dde9214ff6dba265e18af60312" title="cache of iepdf.beta">_beta</a>;
+<a name="l00721"></a>00721 
+<a name="l00722"></a>00722         <span class="keyword">public</span>:
+<a name="l00724"></a><a class="code" href="classbdm_1_1mgamma.html#1a9dc8661e5b214a8185d6e6b9956eb1">00724</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>&lt;<a class="code" href="classbdm_1_1egamma.html" title="Gamma posterior density.">egamma</a>&gt;(), <a class="code" href="classbdm_1_1mgamma.html#b20cf88cca1fe9b0b8f2a412608bfd09" title="Constant .">k</a> (0),
+<a name="l00725"></a>00725                                 <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>()) {
+<a name="l00726"></a>00726                 }
+<a name="l00727"></a>00727 
+<a name="l00729"></a>00729                 <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 &amp;beta0);
+<a name="l00730"></a>00730 
+<a name="l00731"></a><a class="code" href="classbdm_1_1mgamma.html#8996500f1885e39cde30221b20900bff">00731</a>                 <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1mgamma.html#8996500f1885e39cde30221b20900bff">condition</a> (<span class="keyword">const</span> vec &amp;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;};
+<a name="l00741"></a><a class="code" href="classbdm_1_1mgamma.html#da2af0f327e5452bee71d1bf97452ae4">00741</a>                 <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1mgamma.html#da2af0f327e5452bee71d1bf97452ae4">from_setting</a> (<span class="keyword">const</span> Setting &amp;<span class="keyword">set</span>) {
+<a name="l00742"></a>00742                         <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>
+<a name="l00743"></a>00743                         vec betatmp; <span class="comment">// ugly but necessary</span>
+<a name="l00744"></a>00744                         <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);
+<a name="l00745"></a>00745                         <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);
+<a name="l00746"></a>00746                         <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);
+<a name="l00747"></a>00747                 }
+<a name="l00748"></a>00748 };
+<a name="l00749"></a>00749 <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);
+<a name="l00750"></a>00750 SHAREDPTR (mgamma);
 <a name="l00751"></a>00751 
-<a name="l00753"></a><a class="code" href="classbdm_1_1migamma.html#0d854c047001b5465cf1ba21f52904b5">00753</a>                 vec &amp;<a class="code" href="classbdm_1_1migamma.html#0d854c047001b5465cf1ba21f52904b5" title="cache of iepdf.beta">_beta</a>;
-<a name="l00754"></a>00754 
-<a name="l00755"></a>00755         <span class="keyword">public</span>:
-<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>&lt;<a class="code" href="classbdm_1_1eigamma.html" title="Inverse-Gamma posterior density.">eigamma</a>&gt;(),
-<a name="l00759"></a>00759                                 <a class="code" href="classbdm_1_1migamma.html#dc56bc9da542e0103ec16b9be8e5e38c" title="Constant .">k</a> (0),
-<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>()),
-<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>()) {
-<a name="l00762"></a>00762                 }
-<a name="l00763"></a>00763 
-<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> &amp;m) : <a class="code" href="classbdm_1_1mpdf__internal.html" title="Mpdf with internal epdf that is modified by function condition.">mpdf_internal</a>&lt;<a class="code" href="classbdm_1_1eigamma.html" title="Inverse-Gamma posterior density.">eigamma</a>&gt;(),
-<a name="l00765"></a>00765                                 <a class="code" href="classbdm_1_1migamma.html#dc56bc9da542e0103ec16b9be8e5e38c" title="Constant .">k</a> (0),
-<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>()),
-<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>()) {
-<a name="l00768"></a>00768                 }
-<a name="l00770"></a>00770 
-<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) {
-<a name="l00773"></a>00773                         <a class="code" href="classbdm_1_1migamma.html#dc56bc9da542e0103ec16b9be8e5e38c" title="Constant .">k</a> = k0;
-<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>);
-<a name="l00775"></a>00775                         <a class="code" href="classbdm_1_1mpdf.html#7c1900976ff13dbc09c9729b3bbff9e6" title="dimension of the condition">dimc</a> = dimension();
-<a name="l00776"></a>00776                 };
-<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 &amp;val) {
-<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));
-<a name="l00779"></a>00779                 };
-<a name="l00780"></a>00780 };
+<a name="l00761"></a><a class="code" href="classbdm_1_1migamma.html">00761</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>&lt;eigamma&gt;
+<a name="l00762"></a>00762 {
+<a name="l00763"></a>00763         <span class="keyword">protected</span>:
+<a name="l00765"></a><a class="code" href="classbdm_1_1migamma.html#dc56bc9da542e0103ec16b9be8e5e38c">00765</a>                 <span class="keywordtype">double</span> <a class="code" href="classbdm_1_1migamma.html#dc56bc9da542e0103ec16b9be8e5e38c" title="Constant .">k</a>;
+<a name="l00766"></a>00766 
+<a name="l00768"></a><a class="code" href="classbdm_1_1migamma.html#c9847093da59a9ba0ebb68d2c592f5dc">00768</a>                 vec &amp;<a class="code" href="classbdm_1_1migamma.html#c9847093da59a9ba0ebb68d2c592f5dc" title="cache of iepdf.alpha">_alpha</a>;
+<a name="l00769"></a>00769 
+<a name="l00771"></a><a class="code" href="classbdm_1_1migamma.html#0d854c047001b5465cf1ba21f52904b5">00771</a>                 vec &amp;<a class="code" href="classbdm_1_1migamma.html#0d854c047001b5465cf1ba21f52904b5" title="cache of iepdf.beta">_beta</a>;
+<a name="l00772"></a>00772 
+<a name="l00773"></a>00773         <span class="keyword">public</span>:
+<a name="l00776"></a>00776                 <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>&lt;<a class="code" href="classbdm_1_1eigamma.html" title="Inverse-Gamma posterior density.">eigamma</a>&gt;(),
+<a name="l00777"></a>00777                                 <a class="code" href="classbdm_1_1migamma.html#dc56bc9da542e0103ec16b9be8e5e38c" title="Constant .">k</a> (0),
+<a name="l00778"></a>00778                                 <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>()),
+<a name="l00779"></a>00779                                 <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>()) {
+<a name="l00780"></a>00780                 }
 <a name="l00781"></a>00781 
-<a name="l00782"></a>00782 
-<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>
-<a name="l00795"></a>00795 {
-<a name="l00796"></a>00796         <span class="keyword">protected</span>:
-<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>;
-<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>;
-<a name="l00801"></a>00801         <span class="keyword">public</span>:
-<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> () {};
-<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) {
-<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);
-<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;
-<a name="l00808"></a>00808                         <a class="code" href="classbdm_1_1mpdf.html#7c1900976ff13dbc09c9729b3bbff9e6" title="dimension of the condition">dimc</a> = dimension();
-<a name="l00809"></a>00809                 };
-<a name="l00810"></a>00810 
-<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 &amp;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;};
-<a name="l00812"></a>00812 };
-<a name="l00813"></a>00813 
-<a name="l00814"></a>00814 
-<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>
-<a name="l00828"></a>00828 {
-<a name="l00829"></a>00829         <span class="keyword">protected</span>:
-<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>;
-<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>;
-<a name="l00834"></a>00834         <span class="keyword">public</span>:
-<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> () {};
-<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) {
-<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);
-<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);
-<a name="l00841"></a>00841                         <a class="code" href="classbdm_1_1migamma__ref.html#cdc1345ba8375fbdb18a69322d2f841d" title="parameter l">l</a> = l0;
-<a name="l00842"></a>00842                         <a class="code" href="classbdm_1_1mpdf.html#7c1900976ff13dbc09c9729b3bbff9e6" title="dimension of the condition">dimc</a> = dimension();
-<a name="l00843"></a>00843                 };
-<a name="l00844"></a>00844 
-<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 &amp;val) {
-<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>));
-<a name="l00847"></a>00847                         <a class="code" href="classbdm_1_1migamma__ref.html#ae86b2e4ff963d62e05d4e130514634a">migamma::condition</a> (mean);
-<a name="l00848"></a>00848                 };
-<a name="l00849"></a>00849 
-<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 &amp;<span class="keyword">set</span>);
-<a name="l00871"></a>00871 
-<a name="l00872"></a>00872                 <span class="comment">// TODO dodelat void to_setting( Setting &amp;set ) const;</span>
-<a name="l00873"></a>00873 };
-<a name="l00874"></a>00874 
-<a name="l00875"></a>00875 
-<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);
-<a name="l00877"></a>00877 SHAREDPTR (migamma_ref);
-<a name="l00878"></a>00878 
-<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>&lt;ldmat&gt;
-<a name="l00889"></a>00889 {
-<a name="l00890"></a>00890         <span class="keyword">public</span>:
-<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&lt;ldmat&gt;::sample</a>());};
-<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&lt;ldmat&gt;::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);};
+<a name="l00782"></a>00782                 <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> &amp;m) : <a class="code" href="classbdm_1_1mpdf__internal.html" title="Mpdf with internal epdf that is modified by function condition.">mpdf_internal</a>&lt;<a class="code" href="classbdm_1_1eigamma.html" title="Inverse-Gamma posterior density.">eigamma</a>&gt;(),
+<a name="l00783"></a>00783                                 <a class="code" href="classbdm_1_1migamma.html#dc56bc9da542e0103ec16b9be8e5e38c" title="Constant .">k</a> (0),
+<a name="l00784"></a>00784                                 <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>()),
+<a name="l00785"></a>00785                                 <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>()) {
+<a name="l00786"></a>00786                 }
+<a name="l00788"></a>00788 
+<a name="l00790"></a><a class="code" href="classbdm_1_1migamma.html#8b10ab922e2a7bae2fb6bb3efc7b6151">00790</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) {
+<a name="l00791"></a>00791                         <a class="code" href="classbdm_1_1migamma.html#dc56bc9da542e0103ec16b9be8e5e38c" title="Constant .">k</a> = k0;
+<a name="l00792"></a>00792                         <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>);
+<a name="l00793"></a>00793                         <a class="code" href="classbdm_1_1mpdf.html#7c1900976ff13dbc09c9729b3bbff9e6" title="dimension of the condition">dimc</a> = dimension();
+<a name="l00794"></a>00794                 };
+<a name="l00795"></a><a class="code" href="classbdm_1_1migamma.html#7a34b1e2e3aa2250d7c0ed7df1665b8c">00795</a>                 <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1migamma.html#7a34b1e2e3aa2250d7c0ed7df1665b8c">condition</a> (<span class="keyword">const</span> vec &amp;val) {
+<a name="l00796"></a>00796                         <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));
+<a name="l00797"></a>00797                 };
+<a name="l00798"></a>00798 };
+<a name="l00799"></a>00799 
+<a name="l00800"></a>00800 
+<a name="l00812"></a><a class="code" href="classbdm_1_1mgamma__fix.html">00812</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>
+<a name="l00813"></a>00813 {
+<a name="l00814"></a>00814         <span class="keyword">protected</span>:
+<a name="l00816"></a><a class="code" href="classbdm_1_1mgamma__fix.html#1eb701506aabb2e6af007e487212d6fa">00816</a>                 <span class="keywordtype">double</span> <a class="code" href="classbdm_1_1mgamma__fix.html#1eb701506aabb2e6af007e487212d6fa" title="parameter l">l</a>;
+<a name="l00818"></a><a class="code" href="classbdm_1_1mgamma__fix.html#018c6f901a04e419455308a07eb3b0b2">00818</a>                 vec <a class="code" href="classbdm_1_1mgamma__fix.html#018c6f901a04e419455308a07eb3b0b2" title="reference vector">refl</a>;
+<a name="l00819"></a>00819         <span class="keyword">public</span>:
+<a name="l00821"></a><a class="code" href="classbdm_1_1mgamma__fix.html#9a31bc9b4b60188a18a2a6b588dc4b2d">00821</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> () {};
+<a name="l00823"></a><a class="code" href="classbdm_1_1mgamma__fix.html#1bfd30e90db9dc1fbda4a9fbb0b716b2">00823</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) {
+<a name="l00824"></a>00824                         <a class="code" href="classbdm_1_1mgamma__fix.html#1bfd30e90db9dc1fbda4a9fbb0b716b2" title="Set value of k.">mgamma::set_parameters</a> (k0, ref0);
+<a name="l00825"></a>00825                         <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;
+<a name="l00826"></a>00826                         <a class="code" href="classbdm_1_1mpdf.html#7c1900976ff13dbc09c9729b3bbff9e6" title="dimension of the condition">dimc</a> = dimension();
+<a name="l00827"></a>00827                 };
+<a name="l00828"></a>00828 
+<a name="l00829"></a><a class="code" href="classbdm_1_1mgamma__fix.html#1d539591deb7a38bb3403c2b396c8ff7">00829</a>                 <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1mgamma__fix.html#1d539591deb7a38bb3403c2b396c8ff7">condition</a> (<span class="keyword">const</span> vec &amp;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;};
+<a name="l00830"></a>00830 };
+<a name="l00831"></a>00831 
+<a name="l00832"></a>00832 
+<a name="l00845"></a><a class="code" href="classbdm_1_1migamma__ref.html">00845</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>
+<a name="l00846"></a>00846 {
+<a name="l00847"></a>00847         <span class="keyword">protected</span>:
+<a name="l00849"></a><a class="code" href="classbdm_1_1migamma__ref.html#cdc1345ba8375fbdb18a69322d2f841d">00849</a>                 <span class="keywordtype">double</span> <a class="code" href="classbdm_1_1migamma__ref.html#cdc1345ba8375fbdb18a69322d2f841d" title="parameter l">l</a>;
+<a name="l00851"></a><a class="code" href="classbdm_1_1migamma__ref.html#3692dc67caf4367e15564d37f45476f6">00851</a>                 vec <a class="code" href="classbdm_1_1migamma__ref.html#3692dc67caf4367e15564d37f45476f6" title="reference vector">refl</a>;
+<a name="l00852"></a>00852         <span class="keyword">public</span>:
+<a name="l00854"></a><a class="code" href="classbdm_1_1migamma__ref.html#f45b15a10f084991ba6b48295f10421f">00854</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> () {};
+<a name="l00856"></a><a class="code" href="classbdm_1_1migamma__ref.html#b0b4eb278ef5d0831ec4954ba7bd2800">00856</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) {
+<a name="l00857"></a>00857                         <a class="code" href="classbdm_1_1migamma__ref.html#b0b4eb278ef5d0831ec4954ba7bd2800" title="Set value of k.">migamma::set_parameters</a> (ref0.length(), k0);
+<a name="l00858"></a>00858                         <a class="code" href="classbdm_1_1migamma__ref.html#3692dc67caf4367e15564d37f45476f6" title="reference vector">refl</a> = pow (ref0, 1.0 - l0);
+<a name="l00859"></a>00859                         <a class="code" href="classbdm_1_1migamma__ref.html#cdc1345ba8375fbdb18a69322d2f841d" title="parameter l">l</a> = l0;
+<a name="l00860"></a>00860                         <a class="code" href="classbdm_1_1mpdf.html#7c1900976ff13dbc09c9729b3bbff9e6" title="dimension of the condition">dimc</a> = dimension();
+<a name="l00861"></a>00861                 };
+<a name="l00862"></a>00862 
+<a name="l00863"></a><a class="code" href="classbdm_1_1migamma__ref.html#ae86b2e4ff963d62e05d4e130514634a">00863</a>                 <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1migamma__ref.html#ae86b2e4ff963d62e05d4e130514634a">condition</a> (<span class="keyword">const</span> vec &amp;val) {
+<a name="l00864"></a>00864                         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>));
+<a name="l00865"></a>00865                         <a class="code" href="classbdm_1_1migamma__ref.html#ae86b2e4ff963d62e05d4e130514634a">migamma::condition</a> (mean);
+<a name="l00866"></a>00866                 };
+<a name="l00867"></a>00867 
+<a name="l00888"></a>00888                 <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1migamma__ref.html#9e7e0f7d2aa9ecca8ec1af8cbcb5ef1d">from_setting</a> (<span class="keyword">const</span> Setting &amp;<span class="keyword">set</span>);
+<a name="l00889"></a>00889 
+<a name="l00890"></a>00890                 <span class="comment">// TODO dodelat void to_setting( Setting &amp;set ) const;</span>
+<a name="l00891"></a>00891 };
+<a name="l00892"></a>00892 
 <a name="l00893"></a>00893 
-<a name="l00894"></a>00894 };
-<a name="l00895"></a>00895 
-<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>&lt;elognorm&gt;
-<a name="l00908"></a>00908 {
-<a name="l00909"></a>00909         <span class="keyword">protected</span>:
-<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>;
-<a name="l00912"></a>00912 
-<a name="l00914"></a><a class="code" href="classbdm_1_1mlognorm.html#7d0063f77d899ef22e8c5edd642176d2">00914</a>                 vec &amp;<a class="code" href="classbdm_1_1mlognorm.html#7d0063f77d899ef22e8c5edd642176d2" title="access">mu</a>;
-<a name="l00915"></a>00915         <span class="keyword">public</span>:
-<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>&lt;<a class="code" href="classbdm_1_1elognorm.html">elognorm</a>&gt;(),
-<a name="l00918"></a>00918                                 <a class="code" href="classbdm_1_1mlognorm.html#a51128a2e503b8b2ce698244b9e0db1a" title="parameter 1/2*sigma^2">sig2</a> (0),
-<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()) {
-<a name="l00920"></a>00920                 }
-<a name="l00921"></a>00921 
-<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) {
-<a name="l00924"></a>00924                         <a class="code" href="classbdm_1_1mlognorm.html#a51128a2e503b8b2ce698244b9e0db1a" title="parameter 1/2*sigma^2">sig2</a> = 0.5 * log (k * k + 1);
-<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 1/2*sigma^2">sig2</a>*eye (size));
-<a name="l00926"></a>00926 
-<a name="l00927"></a>00927                         <a class="code" href="classbdm_1_1mpdf.html#7c1900976ff13dbc09c9729b3bbff9e6" title="dimension of the condition">dimc</a> = size;
-<a name="l00928"></a>00928                 };
-<a name="l00929"></a>00929 
-<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 &amp;val) {
-<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>
-<a name="l00932"></a>00932                 };
-<a name="l00933"></a>00933 
-<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 &amp;<span class="keyword">set</span>);
-<a name="l00953"></a>00953 
-<a name="l00954"></a>00954                 <span class="comment">// TODO dodelat void to_setting( Setting &amp;set ) const;</span>
-<a name="l00955"></a>00955 
-<a name="l00956"></a>00956 };
-<a name="l00957"></a>00957 
-<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);
-<a name="l00959"></a>00959 SHAREDPTR (mlognorm);
-<a name="l00960"></a>00960 
-<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>
-<a name="l00965"></a>00965 {
-<a name="l00966"></a>00966         <span class="keyword">protected</span>:
-<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>;
-<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>;
-<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>;
-<a name="l00973"></a>00973         <span class="keyword">public</span>:
-<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 &amp;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>; }
-<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>{
-<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>);
-<a name="l00979"></a>00979 
-<a name="l00980"></a>00980                         <span class="comment">//sample diagonal</span>
-<a name="l00981"></a>00981                         <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0;i &lt; <a class="code" href="classbdm_1_1eWishartCh.html#b745c73faef785009484180582050a1f" title="dimension of matrix ">p</a>;i++) {
-<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>
-<a name="l00983"></a>00983 <span class="preprocessor">#pragma omp critical</span>
-<a name="l00984"></a>00984 <span class="preprocessor"></span>                                X (i, i) = sqrt (GamRNG());
-<a name="l00985"></a>00985                         }
-<a name="l00986"></a>00986                         <span class="comment">//do the rest</span>
-<a name="l00987"></a>00987                         <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0;i &lt; p;i++) {
-<a name="l00988"></a>00988                                 <span class="keywordflow">for</span> (<span class="keywordtype">int</span> j = i + 1;j &lt; p;j++) {
-<a name="l00989"></a>00989 <span class="preprocessor">#pragma omp critical</span>
-<a name="l00990"></a>00990 <span class="preprocessor"></span>                                        X (i, j) = NorRNG.sample();
-<a name="l00991"></a>00991                                 }
-<a name="l00992"></a>00992                         }
-<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>
-<a name="l00994"></a>00994                 }
-<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>{
-<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>);
-<a name="l00997"></a>00997                 }
-<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 &amp;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());}
-<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 &amp;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()); }
-<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>&amp; <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>;}
-<a name="l01004"></a>01004 };
-<a name="l01005"></a>01005 
-<a name="l01007"></a>01007 
-<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>
-<a name="l01010"></a>01010 {
-<a name="l01011"></a>01011         <span class="keyword">protected</span>:
-<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>;
-<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>;
-<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>;
-<a name="l01018"></a>01018         <span class="keyword">public</span>:
-<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 &amp;Y0, <span class="keyword">const</span> <span class="keywordtype">double</span> delta0) {
-<a name="l01021"></a>01021                         <a class="code" href="classbdm_1_1eiWishartCh.html#ca3035f7bd5e4597cc1843cf07af8464" title="parameter delta">delta</a> = delta0;
-<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);
-<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();
-<a name="l01024"></a>01024                 }
-<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>);}
-<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 &amp;y0) {
-<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>);
-<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>);
-<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());
-<a name="l01031"></a>01031 
-<a name="l01032"></a>01032                         iCh = inv (Ch);
-<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);
-<a name="l01034"></a>01034                 }
-<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 &amp;val)<span class="keyword"> const </span>{
-<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>);
-<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>&amp; 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>();
-<a name="l01038"></a>01038 
-<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());
-<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);
-<a name="l01041"></a>01041                         <span class="comment">// compute</span>
-<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>
-<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();
-<a name="l01044"></a>01044 
-<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);
-<a name="l01046"></a>01046                         <span class="comment">//Fixme! Multivariate gamma omitted!! it is ok for sampling, but not otherwise!!</span>
-<a name="l01047"></a>01047 
-<a name="l01048"></a>01048                         <span class="comment">/*                              if (0) {</span>
-<a name="l01049"></a>01049 <span class="comment">                                                                mat XX=X.to_mat();</span>
-<a name="l01050"></a>01050 <span class="comment">                                                                mat YY=Y.to_mat();</span>
-<a name="l01051"></a>01051 <span class="comment"></span>
-<a name="l01052"></a>01052 <span class="comment">                                                                double log2 = 0.5*p*log(det(YY))-0.5*(delta+p+1)*log(det(XX))-0.5*trace(YY*inv(XX));</span>
-<a name="l01053"></a>01053 <span class="comment">                                                                cout &lt;&lt; log1 &lt;&lt; "," &lt;&lt; log2 &lt;&lt; endl;</span>
-<a name="l01054"></a>01054 <span class="comment">                                                        }*/</span>
-<a name="l01055"></a>01055                         <span class="keywordflow">return</span> log1;
-<a name="l01056"></a>01056                 };
-<a name="l01057"></a>01057 
-<a name="l01058"></a>01058 };
-<a name="l01059"></a>01059 
-<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>&lt;eiWishartCh&gt;
-<a name="l01062"></a>01062 {
-<a name="l01063"></a>01063         <span class="keyword">protected</span>:
-<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>;
-<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>;
-<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>;
-<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>;
-<a name="l01072"></a>01072 
-<a name="l01073"></a>01073         <span class="keyword">public</span>:
-<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) {}
-<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) {
-<a name="l01077"></a>01077                         <a class="code" href="classbdm_1_1rwiWishartCh.html#7ba06d431995c347d2fce30a59c20663" title="dimension">p</a> = p0;
-<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;
-<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);
-<a name="l01080"></a>01080                         <a class="code" href="classbdm_1_1rwiWishartCh.html#758cd05efa67c60b4bf4f7554b9ba861" title="power of the reference">l</a> = l0;
-<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>);
-<a name="l01082"></a>01082 
-<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);
-<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>();
-<a name="l01085"></a>01085                 }
-<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 &amp;c) {
-<a name="l01087"></a>01087                         vec z = c;
-<a name="l01088"></a>01088                         <span class="keywordtype">int</span> ri = 0;
-<a name="l01089"></a>01089                         <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0;i &lt; <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>
-<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);
-<a name="l01091"></a>01091                                 ri++;
-<a name="l01092"></a>01092                         }
-<a name="l01093"></a>01093 
-<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);
-<a name="l01095"></a>01095                 }
-<a name="l01096"></a>01096 };
-<a name="l01097"></a>01097 
-<a name="l01099"></a>01099 <span class="keyword">enum</span> RESAMPLING_METHOD { MULTINOMIAL = 0, STRATIFIED = 1, SYSTEMATIC = 3 };
-<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>
-<a name="l01106"></a>01106 {
-<a name="l01107"></a>01107         <span class="keyword">protected</span> :
-<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>;
-<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>;
-<a name="l01113"></a><a class="code" href="classbdm_1_1eEmp.html#73d819553a0f268b055a087d2d4486f3">01113</a>                 Array&lt;vec&gt; <a class="code" href="classbdm_1_1eEmp.html#73d819553a0f268b055a087d2d4486f3" title="Samples .">samples</a>;
-<a name="l01114"></a>01114         <span class="keyword">public</span>:
-<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> () {};
-<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> &amp;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>) {};
-<a name="l01121"></a>01121 
-<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 &amp;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> &amp;pdf0);
-<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> &amp;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);};
-<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);
-<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);};
-<a name="l01131"></a><a class="code" href="classbdm_1_1eEmp.html#d7f83cc0415cd44ae7cc8b4bdad93aef">01131</a>                 vec&amp; <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>;};
-<a name="l01133"></a><a class="code" href="classbdm_1_1eEmp.html#b7d7106f486e3fad38590914a693d714">01133</a>                 <span class="keyword">const</span> vec&amp; <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>;};
-<a name="l01135"></a><a class="code" href="classbdm_1_1eEmp.html#c24966b0aaeb767bc8a6b4fd60931be2">01135</a>                 Array&lt;vec&gt;&amp; <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>;};
-<a name="l01137"></a><a class="code" href="classbdm_1_1eEmp.html#b59af0efdb009d98ea8ebfa965e74ae2">01137</a>                 <span class="keyword">const</span> Array&lt;vec&gt;&amp; <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>;};
-<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);
-<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;}
-<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 &amp;val)<span class="keyword"> const </span>{it_error (<span class="stringliteral">"Not implemented"</span>);<span class="keywordflow">return</span> 0.0;}
-<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>{
-<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>);
-<a name="l01146"></a>01146                         <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0;i &lt; <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);}
-<a name="l01147"></a>01147                         <span class="keywordflow">return</span> pom;
-<a name="l01148"></a>01148                 }
-<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>{
-<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>);
-<a name="l01151"></a>01151                         <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0;i &lt; <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);}
-<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);
-<a name="l01153"></a>01153                 }
-<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 &amp;lb, vec &amp;ub, <span class="keywordtype">double</span> perc = 0.95)<span class="keyword"> const </span>{
-<a name="l01156"></a>01156                         <span class="comment">// lb in inf so than it will be pushed below;</span>
-<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>);
-<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>);
-<a name="l01159"></a>01159                         lb = std::numeric_limits&lt;double&gt;::infinity();
-<a name="l01160"></a>01160                         ub = -std::numeric_limits&lt;double&gt;::infinity();
-<a name="l01161"></a>01161                         <span class="keywordtype">int</span> j;
-<a name="l01162"></a>01162                         <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0;i &lt; <a class="code" href="classbdm_1_1eEmp.html#9798006271ca77629855113f1283a031" title="Number of particles.">n</a>;i++) {
-<a name="l01163"></a>01163                                 <span class="keywordflow">for</span> (j = 0;j &lt; <a class="code" href="classbdm_1_1epdf.html#16adac20ec7fe07e1ea0b27d917788ce" title="dimension of the random variable">dim</a>; j++) {
-<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) &lt; lb (j)) {lb (j) = <a class="code" href="classbdm_1_1eEmp.html#73d819553a0f268b055a087d2d4486f3" title="Samples .">samples</a> (i) (j);}
-<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) &gt; ub (j)) {ub (j) = <a class="code" href="classbdm_1_1eEmp.html#73d819553a0f268b055a087d2d4486f3" title="Samples .">samples</a> (i) (j);}
-<a name="l01166"></a>01166                                 }
-<a name="l01167"></a>01167                         }
-<a name="l01168"></a>01168                 }
-<a name="l01169"></a>01169 };
-<a name="l01170"></a>01170 
-<a name="l01171"></a>01171 
-<a name="l01173"></a>01173 
-<a name="l01174"></a>01174 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt;
-<a name="l01175"></a>01175 <span class="keywordtype">void</span> enorm&lt;sq_T&gt;::set_parameters (<span class="keyword">const</span> vec &amp;mu0, <span class="keyword">const</span> sq_T &amp;R0)
-<a name="l01176"></a>01176 {
-<a name="l01177"></a>01177 <span class="comment">//Fixme test dimensions of mu0 and R0;</span>
-<a name="l01178"></a>01178         mu = mu0;
-<a name="l01179"></a>01179         R = R0;
-<a name="l01180"></a>01180         <a class="code" href="classbdm_1_1root.html#1c314bd6d6dacb8ba78ea5eb88fd9516" title="This method TODO.">validate</a>();
-<a name="l01181"></a>01181 };
-<a name="l01182"></a>01182 
-<a name="l01183"></a>01183 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt;
-<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&lt;sq_T&gt;::from_setting</a> (<span class="keyword">const</span> Setting &amp;<span class="keyword">set</span>)
-<a name="l01185"></a>01185 {
-<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>
-<a name="l01187"></a>01187 
-<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);
-<a name="l01189"></a>01189         mat Rtmp;<span class="comment">// necessary for conversion</span>
-<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);
-<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>
-<a name="l01192"></a>01192         <a class="code" href="classbdm_1_1enorm.html#38eb17ecb75d94a50b6782fcf735cfea" title="This method TODO.">validate</a>();
-<a name="l01193"></a>01193 }
-<a name="l01194"></a>01194 
-<a name="l01195"></a>01195 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt;
-<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&lt;sq_T&gt;::dupdate</a> (mat &amp;v, <span class="keywordtype">double</span> nu)
-<a name="l01197"></a>01197 {
-<a name="l01198"></a>01198         <span class="comment">//</span>
-<a name="l01199"></a>01199 };
-<a name="l01200"></a>01200 
-<a name="l01201"></a>01201 <span class="comment">// template&lt;class sq_T&gt;</span>
-<a name="l01202"></a>01202 <span class="comment">// void enorm&lt;sq_T&gt;::tupdate ( double phi, mat &amp;vbar, double nubar ) {</span>
-<a name="l01203"></a>01203 <span class="comment">//      //</span>
-<a name="l01204"></a>01204 <span class="comment">// };</span>
+<a name="l00894"></a>00894 <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);
+<a name="l00895"></a>00895 SHAREDPTR (migamma_ref);
+<a name="l00896"></a>00896 
+<a name="l00906"></a><a class="code" href="classbdm_1_1elognorm.html">00906</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>&lt;ldmat&gt;
+<a name="l00907"></a>00907 {
+<a name="l00908"></a>00908         <span class="keyword">public</span>:
+<a name="l00909"></a><a class="code" href="classbdm_1_1elognorm.html#8b948e2bce1253765a2542199913aaba">00909</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&lt;ldmat&gt;::sample</a>());};
+<a name="l00910"></a><a class="code" href="classbdm_1_1elognorm.html#adb41e4f4d6600dec6f8c1dbc5ed9eea">00910</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&lt;ldmat&gt;::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);};
+<a name="l00911"></a>00911 
+<a name="l00912"></a>00912 };
+<a name="l00913"></a>00913 
+<a name="l00925"></a><a class="code" href="classbdm_1_1mlognorm.html">00925</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>&lt;elognorm&gt;
+<a name="l00926"></a>00926 {
+<a name="l00927"></a>00927         <span class="keyword">protected</span>:
+<a name="l00929"></a><a class="code" href="classbdm_1_1mlognorm.html#a51128a2e503b8b2ce698244b9e0db1a">00929</a>                 <span class="keywordtype">double</span> <a class="code" href="classbdm_1_1mlognorm.html#a51128a2e503b8b2ce698244b9e0db1a" title="parameter 1/2*sigma^2">sig2</a>;
+<a name="l00930"></a>00930 
+<a name="l00932"></a><a class="code" href="classbdm_1_1mlognorm.html#7d0063f77d899ef22e8c5edd642176d2">00932</a>                 vec &amp;<a class="code" href="classbdm_1_1mlognorm.html#7d0063f77d899ef22e8c5edd642176d2" title="access">mu</a>;
+<a name="l00933"></a>00933         <span class="keyword">public</span>:
+<a name="l00935"></a><a class="code" href="classbdm_1_1mlognorm.html#a5d6eb2688d02e0348b96c4fbd7bde41">00935</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>&lt;<a class="code" href="classbdm_1_1elognorm.html">elognorm</a>&gt;(),
+<a name="l00936"></a>00936                                 <a class="code" href="classbdm_1_1mlognorm.html#a51128a2e503b8b2ce698244b9e0db1a" title="parameter 1/2*sigma^2">sig2</a> (0),
+<a name="l00937"></a>00937                                 <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()) {
+<a name="l00938"></a>00938                 }
+<a name="l00939"></a>00939 
+<a name="l00941"></a><a class="code" href="classbdm_1_1mlognorm.html#604cab0e8a76f9041dc3c606043bb39f">00941</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) {
+<a name="l00942"></a>00942                         <a class="code" href="classbdm_1_1mlognorm.html#a51128a2e503b8b2ce698244b9e0db1a" title="parameter 1/2*sigma^2">sig2</a> = 0.5 * log (k * k + 1);
+<a name="l00943"></a>00943                         <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 1/2*sigma^2">sig2</a>*eye (size));
+<a name="l00944"></a>00944 
+<a name="l00945"></a>00945                         <a class="code" href="classbdm_1_1mpdf.html#7c1900976ff13dbc09c9729b3bbff9e6" title="dimension of the condition">dimc</a> = size;
+<a name="l00946"></a>00946                 };
+<a name="l00947"></a>00947 
+<a name="l00948"></a><a class="code" href="classbdm_1_1mlognorm.html#9106d8fd8bdf2b6be675ffd8f3ca584e">00948</a>                 <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1mlognorm.html#9106d8fd8bdf2b6be675ffd8f3ca584e">condition</a> (<span class="keyword">const</span> vec &amp;val) {
+<a name="l00949"></a>00949                         <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>
+<a name="l00950"></a>00950                 };
+<a name="l00951"></a>00951 
+<a name="l00970"></a>00970                 <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1mlognorm.html#49e45ea13a869da607ef9be7a229128a">from_setting</a> (<span class="keyword">const</span> Setting &amp;<span class="keyword">set</span>);
+<a name="l00971"></a>00971 
+<a name="l00972"></a>00972                 <span class="comment">// TODO dodelat void to_setting( Setting &amp;set ) const;</span>
+<a name="l00973"></a>00973 
+<a name="l00974"></a>00974 };
+<a name="l00975"></a>00975 
+<a name="l00976"></a>00976 <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);
+<a name="l00977"></a>00977 SHAREDPTR (mlognorm);
+<a name="l00978"></a>00978 
+<a name="l00982"></a><a class="code" href="classbdm_1_1eWishartCh.html">00982</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>
+<a name="l00983"></a>00983 {
+<a name="l00984"></a>00984         <span class="keyword">protected</span>:
+<a name="l00986"></a><a class="code" href="classbdm_1_1eWishartCh.html#1b42f9284a32f23b0b253a628cda7490">00986</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>;
+<a name="l00988"></a><a class="code" href="classbdm_1_1eWishartCh.html#b745c73faef785009484180582050a1f">00988</a>                 <span class="keywordtype">int</span> <a class="code" href="classbdm_1_1eWishartCh.html#b745c73faef785009484180582050a1f" title="dimension of matrix ">p</a>;
+<a name="l00990"></a><a class="code" href="classbdm_1_1eWishartCh.html#1879a14d7d2bb05062523b189baa11c3">00990</a>                 <span class="keywordtype">double</span> <a class="code" href="classbdm_1_1eWishartCh.html#1879a14d7d2bb05062523b189baa11c3" title="degrees of freedom ">delta</a>;
+<a name="l00991"></a>00991         <span class="keyword">public</span>:
+<a name="l00993"></a><a class="code" href="classbdm_1_1eWishartCh.html#183d961532ee97b7dc5ec81701aa59a0">00993</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 &amp;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>; }
+<a name="l00995"></a><a class="code" href="classbdm_1_1eWishartCh.html#cc664035d70d2622bf264a29270f8339">00995</a>                 mat <a class="code" href="classbdm_1_1eWishartCh.html#cc664035d70d2622bf264a29270f8339" title="Sample matrix argument.">sample_mat</a>()<span class="keyword"> const </span>{
+<a name="l00996"></a>00996                         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>);
+<a name="l00997"></a>00997 
+<a name="l00998"></a>00998                         <span class="comment">//sample diagonal</span>
+<a name="l00999"></a>00999                         <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0;i &lt; <a class="code" href="classbdm_1_1eWishartCh.html#b745c73faef785009484180582050a1f" title="dimension of matrix ">p</a>;i++) {
+<a name="l01000"></a>01000                                 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>
+<a name="l01001"></a>01001 <span class="preprocessor">#pragma omp critical</span>
+<a name="l01002"></a>01002 <span class="preprocessor"></span>                                X (i, i) = sqrt (GamRNG());
+<a name="l01003"></a>01003                         }
+<a name="l01004"></a>01004                         <span class="comment">//do the rest</span>
+<a name="l01005"></a>01005                         <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0;i &lt; p;i++) {
+<a name="l01006"></a>01006                                 <span class="keywordflow">for</span> (<span class="keywordtype">int</span> j = i + 1;j &lt; p;j++) {
+<a name="l01007"></a>01007 <span class="preprocessor">#pragma omp critical</span>
+<a name="l01008"></a>01008 <span class="preprocessor"></span>                                        X (i, j) = NorRNG.sample();
+<a name="l01009"></a>01009                                 }
+<a name="l01010"></a>01010                         }
+<a name="l01011"></a>01011                         <span class="keywordflow">return</span> X*<a class="code" href="classbdm_1_1eWishartCh.html#1b42f9284a32f23b0b253a628cda7490" title="Upper-Triagle of Choleski decomposition of .">Y</a>.<a class="code" href="classbdm_1_1chmat.html#17daa8c5c5914bd3194cb3053c5793a5" title="Access function.">_Ch</a>();<span class="comment">// return upper triangular part of the decomposition</span>
+<a name="l01012"></a>01012                 }
+<a name="l01013"></a><a class="code" href="classbdm_1_1eWishartCh.html#8f2154b8b5be8f4c5788f261b6d57b9a">01013</a>                 vec <a class="code" href="classbdm_1_1eWishartCh.html#8f2154b8b5be8f4c5788f261b6d57b9a" title="Returns a sample,  from density .">sample</a> ()<span class="keyword"> const </span>{
+<a name="l01014"></a>01014                         <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>);
+<a name="l01015"></a>01015                 }
+<a name="l01017"></a><a class="code" href="classbdm_1_1eWishartCh.html#4eee757c0535c2a88bb20f0767c64981">01017</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 &amp;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());}
+<a name="l01019"></a><a class="code" href="classbdm_1_1eWishartCh.html#7eac414ec10b85aa5536b0092c57bc4a">01019</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 &amp;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()); }
+<a name="l01021"></a><a class="code" href="classbdm_1_1eWishartCh.html#1708cacb5d8cb1b96395d35f5327cb7e">01021</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>&amp; <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>;}
+<a name="l01022"></a>01022 };
+<a name="l01023"></a>01023 
+<a name="l01025"></a>01025 
+<a name="l01027"></a><a class="code" href="classbdm_1_1eiWishartCh.html">01027</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>
+<a name="l01028"></a>01028 {
+<a name="l01029"></a>01029         <span class="keyword">protected</span>:
+<a name="l01031"></a><a class="code" href="classbdm_1_1eiWishartCh.html#c6b684b52dc62b8d46e67d5992f98b9a">01031</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>;
+<a name="l01033"></a><a class="code" href="classbdm_1_1eiWishartCh.html#c11f1c41183f743b97fbb73a4e9ba6cd">01033</a>                 <span class="keywordtype">int</span> <a class="code" href="classbdm_1_1eiWishartCh.html#c11f1c41183f743b97fbb73a4e9ba6cd" title="size of Ch">p</a>;
+<a name="l01035"></a><a class="code" href="classbdm_1_1eiWishartCh.html#ca3035f7bd5e4597cc1843cf07af8464">01035</a>                 <span class="keywordtype">double</span> <a class="code" href="classbdm_1_1eiWishartCh.html#ca3035f7bd5e4597cc1843cf07af8464" title="parameter delta">delta</a>;
+<a name="l01036"></a>01036         <span class="keyword">public</span>:
+<a name="l01038"></a><a class="code" href="classbdm_1_1eiWishartCh.html#f463caed9d22d9949f3ee67614e7dcd3">01038</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 &amp;Y0, <span class="keyword">const</span> <span class="keywordtype">double</span> delta0) {
+<a name="l01039"></a>01039                         <a class="code" href="classbdm_1_1eiWishartCh.html#ca3035f7bd5e4597cc1843cf07af8464" title="parameter delta">delta</a> = delta0;
+<a name="l01040"></a>01040                         <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);
+<a name="l01041"></a>01041                         <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();
+<a name="l01042"></a>01042                 }
+<a name="l01043"></a><a class="code" href="classbdm_1_1eiWishartCh.html#2f668192cc9c2e3a5b7e608164685a3e">01043</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>);}
+<a name="l01045"></a><a class="code" href="classbdm_1_1eiWishartCh.html#d9947933dfc94546cbd6a81f95ec5af5">01045</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 &amp;y0) {
+<a name="l01046"></a>01046                         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>);
+<a name="l01047"></a>01047                         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>);
+<a name="l01048"></a>01048                         copy_vector (<a class="code" href="classbdm_1_1epdf.html#16adac20ec7fe07e1ea0b27d917788ce" title="dimension of the random variable">dim</a>, y0._data(), Ch._data());
+<a name="l01049"></a>01049 
+<a name="l01050"></a>01050                         iCh = inv (Ch);
+<a name="l01051"></a>01051                         <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);
+<a name="l01052"></a>01052                 }
+<a name="l01053"></a><a class="code" href="classbdm_1_1eiWishartCh.html#a6ddbd815b8b666dd542e97f009f89bb">01053</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 &amp;val)<span class="keyword"> const </span>{
+<a name="l01054"></a>01054                         <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>);
+<a name="l01055"></a>01055                         <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>&amp; 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>();
+<a name="l01056"></a>01056 
+<a name="l01057"></a>01057                         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());
+<a name="l01058"></a>01058                         <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);
+<a name="l01059"></a>01059                         <span class="comment">// compute</span>
+<a name="l01060"></a>01060 <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>
+<a name="l01061"></a>01061                         mat M = Y.<a class="code" href="classbdm_1_1chmat.html#4b4c5d4dbb8a3d585b68d936cb6df31b" title="Conversion to full matrix.">to_mat</a>() * iX.to_mat();
+<a name="l01062"></a>01062 
+<a name="l01063"></a>01063                         <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);
+<a name="l01064"></a>01064                         <span class="comment">//Fixme! Multivariate gamma omitted!! it is ok for sampling, but not otherwise!!</span>
+<a name="l01065"></a>01065 
+<a name="l01066"></a>01066                         <span class="comment">/*                              if (0) {</span>
+<a name="l01067"></a>01067 <span class="comment">                                                                mat XX=X.to_mat();</span>
+<a name="l01068"></a>01068 <span class="comment">                                                                mat YY=Y.to_mat();</span>
+<a name="l01069"></a>01069 <span class="comment"></span>
+<a name="l01070"></a>01070 <span class="comment">                                                                double log2 = 0.5*p*log(det(YY))-0.5*(delta+p+1)*log(det(XX))-0.5*trace(YY*inv(XX));</span>
+<a name="l01071"></a>01071 <span class="comment">                                                                cout &lt;&lt; log1 &lt;&lt; "," &lt;&lt; log2 &lt;&lt; endl;</span>
+<a name="l01072"></a>01072 <span class="comment">                                                        }*/</span>
+<a name="l01073"></a>01073                         <span class="keywordflow">return</span> log1;
+<a name="l01074"></a>01074                 };
+<a name="l01075"></a>01075 
+<a name="l01076"></a>01076 };
+<a name="l01077"></a>01077 
+<a name="l01079"></a><a class="code" href="classbdm_1_1rwiWishartCh.html">01079</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>&lt;eiWishartCh&gt;
+<a name="l01080"></a>01080 {
+<a name="l01081"></a>01081         <span class="keyword">protected</span>:
+<a name="l01083"></a><a class="code" href="classbdm_1_1rwiWishartCh.html#2004675b37f712abe3913057bae97cfb">01083</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>;
+<a name="l01085"></a><a class="code" href="classbdm_1_1rwiWishartCh.html#239b26c71ebcc118ba6925dfb6efc50a">01085</a>                 vec <a class="code" href="classbdm_1_1rwiWishartCh.html#239b26c71ebcc118ba6925dfb6efc50a" title="reference point for diagonal">refl</a>;
+<a name="l01087"></a><a class="code" href="classbdm_1_1rwiWishartCh.html#758cd05efa67c60b4bf4f7554b9ba861">01087</a>                 <span class="keywordtype">double</span> <a class="code" href="classbdm_1_1rwiWishartCh.html#758cd05efa67c60b4bf4f7554b9ba861" title="power of the reference">l</a>;
+<a name="l01089"></a><a class="code" href="classbdm_1_1rwiWishartCh.html#7ba06d431995c347d2fce30a59c20663">01089</a>                 <span class="keywordtype">int</span> <a class="code" href="classbdm_1_1rwiWishartCh.html#7ba06d431995c347d2fce30a59c20663" title="dimension">p</a>;
+<a name="l01090"></a>01090 
+<a name="l01091"></a>01091         <span class="keyword">public</span>:
+<a name="l01092"></a>01092                 <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) {}
+<a name="l01094"></a><a class="code" href="classbdm_1_1rwiWishartCh.html#28549ee3ce1ff8509360171ea3cf717c">01094</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) {
+<a name="l01095"></a>01095                         <a class="code" href="classbdm_1_1rwiWishartCh.html#7ba06d431995c347d2fce30a59c20663" title="dimension">p</a> = p0;
+<a name="l01096"></a>01096                         <span class="keywordtype">double</span> delta = 2 / (k * k) + <a class="code" href="classbdm_1_1rwiWishartCh.html#7ba06d431995c347d2fce30a59c20663" title="dimension">p</a> + 3;
+<a name="l01097"></a>01097                         <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);
+<a name="l01098"></a>01098                         <a class="code" href="classbdm_1_1rwiWishartCh.html#758cd05efa67c60b4bf4f7554b9ba861" title="power of the reference">l</a> = l0;
+<a name="l01099"></a>01099                         <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>);
+<a name="l01100"></a>01100 
+<a name="l01101"></a>01101                         <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);
+<a name="l01102"></a>01102                         <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>();
+<a name="l01103"></a>01103                 }
+<a name="l01104"></a><a class="code" href="classbdm_1_1rwiWishartCh.html#ac087ba6c885d3faeda9171229f9b4e6">01104</a>                 <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1rwiWishartCh.html#ac087ba6c885d3faeda9171229f9b4e6">condition</a> (<span class="keyword">const</span> vec &amp;c) {
+<a name="l01105"></a>01105                         vec z = c;
+<a name="l01106"></a>01106                         <span class="keywordtype">int</span> ri = 0;
+<a name="l01107"></a>01107                         <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0;i &lt; <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>
+<a name="l01108"></a>01108                                 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);
+<a name="l01109"></a>01109                                 ri++;
+<a name="l01110"></a>01110                         }
+<a name="l01111"></a>01111 
+<a name="l01112"></a>01112                         <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);
+<a name="l01113"></a>01113                 }
+<a name="l01114"></a>01114 };
+<a name="l01115"></a>01115 
+<a name="l01117"></a>01117 <span class="keyword">enum</span> RESAMPLING_METHOD { MULTINOMIAL = 0, STRATIFIED = 1, SYSTEMATIC = 3 };
+<a name="l01123"></a><a class="code" href="classbdm_1_1eEmp.html">01123</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>
+<a name="l01124"></a>01124 {
+<a name="l01125"></a>01125         <span class="keyword">protected</span> :
+<a name="l01127"></a><a class="code" href="classbdm_1_1eEmp.html#9798006271ca77629855113f1283a031">01127</a>                 <span class="keywordtype">int</span> <a class="code" href="classbdm_1_1eEmp.html#9798006271ca77629855113f1283a031" title="Number of particles.">n</a>;
+<a name="l01129"></a><a class="code" href="classbdm_1_1eEmp.html#9d39241aab7c4bbeb07c6d516421c67d">01129</a>                 vec <a class="code" href="classbdm_1_1eEmp.html#9d39241aab7c4bbeb07c6d516421c67d" title="Sample weights .">w</a>;
+<a name="l01131"></a><a class="code" href="classbdm_1_1eEmp.html#73d819553a0f268b055a087d2d4486f3">01131</a>                 Array&lt;vec&gt; <a class="code" href="classbdm_1_1eEmp.html#73d819553a0f268b055a087d2d4486f3" title="Samples .">samples</a>;
+<a name="l01132"></a>01132         <span class="keyword">public</span>:
+<a name="l01135"></a>01135                 <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> () {};
+<a name="l01137"></a><a class="code" href="classbdm_1_1eEmp.html#a3daf6363455af099921715e1233c076">01137</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> &amp;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>) {};
+<a name="l01139"></a>01139 
+<a name="l01141"></a>01141                 <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 &amp;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> &amp;pdf0);
+<a name="l01143"></a><a class="code" href="classbdm_1_1eEmp.html#4f7e6ba7183972e3c7ae399613861b95">01143</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> &amp;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);};
+<a name="l01145"></a>01145                 <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);
+<a name="l01147"></a><a class="code" href="classbdm_1_1eEmp.html#c74c281d652356c19b6b079e42ca7ef1">01147</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);};
+<a name="l01149"></a><a class="code" href="classbdm_1_1eEmp.html#37937007a3a676cf653a7de412674481">01149</a>                 <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1eEmp.html#37937007a3a676cf653a7de412674481" title="Set samples.">set_parameters</a> (<span class="keyword">const</span> Array&lt;vec&gt; &amp;Av) {
+<a name="l01150"></a>01150                         <a class="code" href="bdmerror_8h.html#89a0f906b242b79c5d3d342291b2cab4" title="Throw std::runtime_exception if t is not true and NDEBUG is not defined.">bdm_assert_debug</a>(Av.size()&gt;0,<span class="stringliteral">"Empty samples"</span>); 
+<a name="l01151"></a>01151                         <a class="code" href="classbdm_1_1eEmp.html#9798006271ca77629855113f1283a031" title="Number of particles.">n</a> = Av.size(); 
+<a name="l01152"></a>01152                         <a class="code" href="classbdm_1_1eEmp.html#c74c281d652356c19b6b079e42ca7ef1" title="Set sample.">epdf::set_parameters</a>(Av(0).length());
+<a name="l01153"></a>01153                         <a class="code" href="classbdm_1_1eEmp.html#9d39241aab7c4bbeb07c6d516421c67d" title="Sample weights .">w</a>=1/n*ones(n);
+<a name="l01154"></a>01154                         <a class="code" href="classbdm_1_1eEmp.html#73d819553a0f268b055a087d2d4486f3" title="Samples .">samples</a>=Av;
+<a name="l01155"></a>01155                 };
+<a name="l01157"></a><a class="code" href="classbdm_1_1eEmp.html#d7f83cc0415cd44ae7cc8b4bdad93aef">01157</a>                 vec&amp; <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>;};
+<a name="l01159"></a><a class="code" href="classbdm_1_1eEmp.html#b7d7106f486e3fad38590914a693d714">01159</a>                 <span class="keyword">const</span> vec&amp; <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>;};
+<a name="l01161"></a><a class="code" href="classbdm_1_1eEmp.html#c24966b0aaeb767bc8a6b4fd60931be2">01161</a>                 Array&lt;vec&gt;&amp; <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>;};
+<a name="l01163"></a><a class="code" href="classbdm_1_1eEmp.html#b59af0efdb009d98ea8ebfa965e74ae2">01163</a>                 <span class="keyword">const</span> Array&lt;vec&gt;&amp; <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>;};
+<a name="l01165"></a>01165                 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);
+<a name="l01166"></a>01166 
+<a name="l01168"></a><a class="code" href="classbdm_1_1eEmp.html#97f1e07b5ae6eebc91c7365f0f88d270">01168</a>                 vec <a class="code" href="classbdm_1_1eEmp.html#97f1e07b5ae6eebc91c7365f0f88d270" title="inherited operation : NOT implemented">sample</a>()<span class="keyword"> const </span>{
+<a name="l01169"></a>01169                         <a class="code" href="bdmerror_8h.html#7c43f3a72afe68ab0c85663a1bb3521a" title="Unconditionally throw std::runtime_error.">bdm_error</a> (<span class="stringliteral">"Not implemented"</span>);
+<a name="l01170"></a>01170                         <span class="keywordflow">return</span> vec();
+<a name="l01171"></a>01171                 }
+<a name="l01172"></a>01172 
+<a name="l01174"></a><a class="code" href="classbdm_1_1eEmp.html#01654c014d3aa068f8d4ecba4be86d09">01174</a>                 <span class="keywordtype">double</span> <a class="code" href="classbdm_1_1eEmp.html#01654c014d3aa068f8d4ecba4be86d09" title="inherited operation : NOT implemented">evallog</a> (<span class="keyword">const</span> vec &amp;val)<span class="keyword"> const </span>{
+<a name="l01175"></a>01175                         <a class="code" href="bdmerror_8h.html#7c43f3a72afe68ab0c85663a1bb3521a" title="Unconditionally throw std::runtime_error.">bdm_error</a> (<span class="stringliteral">"Not implemented"</span>);
+<a name="l01176"></a>01176                         <span class="keywordflow">return</span> 0.0;
+<a name="l01177"></a>01177                 }
+<a name="l01178"></a>01178 
+<a name="l01179"></a><a class="code" href="classbdm_1_1eEmp.html#bbfcb4f868c7381298c281a256d8c4b9">01179</a>                 vec <a class="code" href="classbdm_1_1eEmp.html#bbfcb4f868c7381298c281a256d8c4b9" title="return expected value">mean</a>()<span class="keyword"> const </span>{
+<a name="l01180"></a>01180                         vec pom = zeros (<a class="code" href="classbdm_1_1epdf.html#16adac20ec7fe07e1ea0b27d917788ce" title="dimension of the random variable">dim</a>);
+<a name="l01181"></a>01181                         <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0;i &lt; <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);}
+<a name="l01182"></a>01182                         <span class="keywordflow">return</span> pom;
+<a name="l01183"></a>01183                 }
+<a name="l01184"></a><a class="code" href="classbdm_1_1eEmp.html#05e9ebf467ede737cb6a3621d7fd3c87">01184</a>                 vec <a class="code" href="classbdm_1_1eEmp.html#05e9ebf467ede737cb6a3621d7fd3c87" title="return expected variance (not covariance!)">variance</a>()<span class="keyword"> const </span>{
+<a name="l01185"></a>01185                         vec pom = zeros (<a class="code" href="classbdm_1_1epdf.html#16adac20ec7fe07e1ea0b27d917788ce" title="dimension of the random variable">dim</a>);
+<a name="l01186"></a>01186                         <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0;i &lt; <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);}
+<a name="l01187"></a>01187                         <span class="keywordflow">return</span> pom -pow (<a class="code" href="classbdm_1_1eEmp.html#bbfcb4f868c7381298c281a256d8c4b9" title="return expected value">mean</a>(), 2);
+<a name="l01188"></a>01188                 }
+<a name="l01190"></a><a class="code" href="classbdm_1_1eEmp.html#b1c9df656144edf79ba2d885613f661f">01190</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 &amp;lb, vec &amp;ub, <span class="keywordtype">double</span> perc = 0.95)<span class="keyword"> const </span>{
+<a name="l01191"></a>01191                         <span class="comment">// lb in inf so than it will be pushed below;</span>
+<a name="l01192"></a>01192                         lb.set_size (<a class="code" href="classbdm_1_1epdf.html#16adac20ec7fe07e1ea0b27d917788ce" title="dimension of the random variable">dim</a>);
+<a name="l01193"></a>01193                         ub.set_size (<a class="code" href="classbdm_1_1epdf.html#16adac20ec7fe07e1ea0b27d917788ce" title="dimension of the random variable">dim</a>);
+<a name="l01194"></a>01194                         lb = std::numeric_limits&lt;double&gt;::infinity();
+<a name="l01195"></a>01195                         ub = -std::numeric_limits&lt;double&gt;::infinity();
+<a name="l01196"></a>01196                         <span class="keywordtype">int</span> j;
+<a name="l01197"></a>01197                         <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0;i &lt; <a class="code" href="classbdm_1_1eEmp.html#9798006271ca77629855113f1283a031" title="Number of particles.">n</a>;i++) {
+<a name="l01198"></a>01198                                 <span class="keywordflow">for</span> (j = 0;j &lt; <a class="code" href="classbdm_1_1epdf.html#16adac20ec7fe07e1ea0b27d917788ce" title="dimension of the random variable">dim</a>; j++) {
+<a name="l01199"></a>01199                                         <span class="keywordflow">if</span> (<a class="code" href="classbdm_1_1eEmp.html#73d819553a0f268b055a087d2d4486f3" title="Samples .">samples</a> (i) (j) &lt; lb (j)) {lb (j) = <a class="code" href="classbdm_1_1eEmp.html#73d819553a0f268b055a087d2d4486f3" title="Samples .">samples</a> (i) (j);}
+<a name="l01200"></a>01200                                         <span class="keywordflow">if</span> (<a class="code" href="classbdm_1_1eEmp.html#73d819553a0f268b055a087d2d4486f3" title="Samples .">samples</a> (i) (j) &gt; ub (j)) {ub (j) = <a class="code" href="classbdm_1_1eEmp.html#73d819553a0f268b055a087d2d4486f3" title="Samples .">samples</a> (i) (j);}
+<a name="l01201"></a>01201                                 }
+<a name="l01202"></a>01202                         }
+<a name="l01203"></a>01203                 }
+<a name="l01204"></a>01204 };
 <a name="l01205"></a>01205 
-<a name="l01206"></a>01206 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt;
-<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&lt;sq_T&gt;::sample</a>()<span class="keyword"> const</span>
-<a name="l01208"></a>01208 <span class="keyword"></span>{
-<a name="l01209"></a>01209         vec x (<a class="code" href="classbdm_1_1epdf.html#16adac20ec7fe07e1ea0b27d917788ce" title="dimension of the random variable">dim</a>);
-<a name="l01210"></a>01210 <span class="preprocessor">#pragma omp critical</span>
-<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);
-<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);
-<a name="l01213"></a>01213 
-<a name="l01214"></a>01214         smp += <a class="code" href="classbdm_1_1enorm.html#c702a194720853570d08b65482f842c7" title="mean value">mu</a>;
-<a name="l01215"></a>01215         <span class="keywordflow">return</span> smp;
+<a name="l01206"></a>01206 
+<a name="l01208"></a>01208 
+<a name="l01209"></a>01209 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt;
+<a name="l01210"></a>01210 <span class="keywordtype">void</span> enorm&lt;sq_T&gt;::set_parameters (<span class="keyword">const</span> vec &amp;mu0, <span class="keyword">const</span> sq_T &amp;R0)
+<a name="l01211"></a>01211 {
+<a name="l01212"></a>01212 <span class="comment">//Fixme test dimensions of mu0 and R0;</span>
+<a name="l01213"></a>01213         mu = mu0;
+<a name="l01214"></a>01214         R = R0;
+<a name="l01215"></a>01215         <a class="code" href="classbdm_1_1root.html#1c314bd6d6dacb8ba78ea5eb88fd9516" title="This method TODO.">validate</a>();
 <a name="l01216"></a>01216 };
 <a name="l01217"></a>01217 
-<a name="l01218"></a>01218 <span class="comment">// template&lt;class sq_T&gt;</span>
-<a name="l01219"></a>01219 <span class="comment">// double enorm&lt;sq_T&gt;::eval ( const vec &amp;val ) const {</span>
-<a name="l01220"></a>01220 <span class="comment">//      double pdfl,e;</span>
-<a name="l01221"></a>01221 <span class="comment">//      pdfl = evallog ( val );</span>
-<a name="l01222"></a>01222 <span class="comment">//      e = exp ( pdfl );</span>
-<a name="l01223"></a>01223 <span class="comment">//      return e;</span>
-<a name="l01224"></a>01224 <span class="comment">// };</span>
-<a name="l01225"></a>01225 
-<a name="l01226"></a>01226 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt;
-<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&lt;sq_T&gt;::evallog_nn</a> (<span class="keyword">const</span> vec &amp;val)<span class="keyword"> const</span>
-<a name="l01228"></a>01228 <span class="keyword"></span>{
-<a name="l01229"></a>01229         <span class="comment">// 1.83787706640935 = log(2pi)</span>
-<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>
-<a name="l01231"></a>01231         <span class="keywordflow">return</span>  tmp;
-<a name="l01232"></a>01232 };
-<a name="l01233"></a>01233 
-<a name="l01234"></a>01234 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt;
-<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&lt;sq_T&gt;::lognc</a> ()<span class="keyword"> const</span>
-<a name="l01236"></a>01236 <span class="keyword"></span>{
-<a name="l01237"></a>01237         <span class="comment">// 1.83787706640935 = log(2pi)</span>
-<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());
-<a name="l01239"></a>01239         <span class="keywordflow">return</span> tmp;
-<a name="l01240"></a>01240 };
-<a name="l01241"></a>01241 
-<a name="l01242"></a>01242 
-<a name="l01243"></a>01243 <span class="comment">// template&lt;class sq_T&gt;</span>
-<a name="l01244"></a>01244 <span class="comment">// vec mlnorm&lt;sq_T&gt;::samplecond (const  vec &amp;cond, double &amp;lik ) {</span>
-<a name="l01245"></a>01245 <span class="comment">//      this-&gt;condition ( cond );</span>
-<a name="l01246"></a>01246 <span class="comment">//      vec smp = epdf.sample();</span>
-<a name="l01247"></a>01247 <span class="comment">//      lik = epdf.eval ( smp );</span>
-<a name="l01248"></a>01248 <span class="comment">//      return smp;</span>
-<a name="l01249"></a>01249 <span class="comment">// }</span>
-<a name="l01250"></a>01250 
-<a name="l01251"></a>01251 <span class="comment">// template&lt;class sq_T&gt;</span>
-<a name="l01252"></a>01252 <span class="comment">// mat mlnorm&lt;sq_T&gt;::samplecond (const vec &amp;cond, vec &amp;lik, int n ) {</span>
-<a name="l01253"></a>01253 <span class="comment">//      int i;</span>
-<a name="l01254"></a>01254 <span class="comment">//      int dim = rv.count();</span>
-<a name="l01255"></a>01255 <span class="comment">//      mat Smp ( dim,n );</span>
-<a name="l01256"></a>01256 <span class="comment">//      vec smp ( dim );</span>
-<a name="l01257"></a>01257 <span class="comment">//      this-&gt;condition ( cond );</span>
-<a name="l01258"></a>01258 <span class="comment">//</span>
-<a name="l01259"></a>01259 <span class="comment">//      for ( i=0; i&lt;n; i++ ) {</span>
-<a name="l01260"></a>01260 <span class="comment">//              smp = epdf.sample();</span>
-<a name="l01261"></a>01261 <span class="comment">//              lik ( i ) = epdf.eval ( smp );</span>
-<a name="l01262"></a>01262 <span class="comment">//              Smp.set_col ( i ,smp );</span>
-<a name="l01263"></a>01263 <span class="comment">//      }</span>
-<a name="l01264"></a>01264 <span class="comment">//</span>
-<a name="l01265"></a>01265 <span class="comment">//      return Smp;</span>
-<a name="l01266"></a>01266 <span class="comment">// }</span>
-<a name="l01267"></a>01267 
+<a name="l01218"></a>01218 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt;
+<a name="l01219"></a><a class="code" href="classbdm_1_1enorm.html#61bd470764020bea6e1ed35000f259e6">01219</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1enorm.html#61bd470764020bea6e1ed35000f259e6">enorm&lt;sq_T&gt;::from_setting</a> (<span class="keyword">const</span> Setting &amp;<span class="keyword">set</span>)
+<a name="l01220"></a>01220 {
+<a name="l01221"></a>01221         <a class="code" href="classbdm_1_1enorm.html#61bd470764020bea6e1ed35000f259e6">epdf::from_setting</a> (<span class="keyword">set</span>); <span class="comment">//reads rv</span>
+<a name="l01222"></a>01222 
+<a name="l01223"></a>01223         <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);
+<a name="l01224"></a>01224         mat Rtmp;<span class="comment">// necessary for conversion</span>
+<a name="l01225"></a>01225         <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);
+<a name="l01226"></a>01226         <a class="code" href="classbdm_1_1enorm.html#2d92dde696b2a7a5b10ddef5d22ba2c2" title="Covariance matrix in decomposed form.">R</a> = Rtmp; <span class="comment">// conversion</span>
+<a name="l01227"></a>01227         <a class="code" href="classbdm_1_1enorm.html#38eb17ecb75d94a50b6782fcf735cfea" title="This method TODO.">validate</a>();
+<a name="l01228"></a>01228 }
+<a name="l01229"></a>01229 
+<a name="l01230"></a>01230 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt;
+<a name="l01231"></a><a class="code" href="classbdm_1_1enorm.html#d2e0d3a1e30ab3ab04df2d0c43ae74a2">01231</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1enorm.html#d2e0d3a1e30ab3ab04df2d0c43ae74a2" title="dupdate in exponential form (not really handy)">enorm&lt;sq_T&gt;::dupdate</a> (mat &amp;v, <span class="keywordtype">double</span> nu)
+<a name="l01232"></a>01232 {
+<a name="l01233"></a>01233         <span class="comment">//</span>
+<a name="l01234"></a>01234 };
+<a name="l01235"></a>01235 
+<a name="l01236"></a>01236 <span class="comment">// template&lt;class sq_T&gt;</span>
+<a name="l01237"></a>01237 <span class="comment">// void enorm&lt;sq_T&gt;::tupdate ( double phi, mat &amp;vbar, double nubar ) {</span>
+<a name="l01238"></a>01238 <span class="comment">//      //</span>
+<a name="l01239"></a>01239 <span class="comment">// };</span>
+<a name="l01240"></a>01240 
+<a name="l01241"></a>01241 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt;
+<a name="l01242"></a><a class="code" href="classbdm_1_1enorm.html#e1a48f52351ec3a349bd443b713b1766">01242</a> vec <a class="code" href="classbdm_1_1enorm.html#e1a48f52351ec3a349bd443b713b1766" title="Returns a sample,  from density .">enorm&lt;sq_T&gt;::sample</a>()<span class="keyword"> const</span>
+<a name="l01243"></a>01243 <span class="keyword"></span>{
+<a name="l01244"></a>01244         vec x (<a class="code" href="classbdm_1_1epdf.html#16adac20ec7fe07e1ea0b27d917788ce" title="dimension of the random variable">dim</a>);
+<a name="l01245"></a>01245 <span class="preprocessor">#pragma omp critical</span>
+<a name="l01246"></a>01246 <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);
+<a name="l01247"></a>01247         vec smp = <a class="code" href="classbdm_1_1enorm.html#2d92dde696b2a7a5b10ddef5d22ba2c2" title="Covariance matrix in decomposed form.">R</a>.sqrt_mult (x);
+<a name="l01248"></a>01248 
+<a name="l01249"></a>01249         smp += <a class="code" href="classbdm_1_1enorm.html#c702a194720853570d08b65482f842c7" title="mean value">mu</a>;
+<a name="l01250"></a>01250         <span class="keywordflow">return</span> smp;
+<a name="l01251"></a>01251 };
+<a name="l01252"></a>01252 
+<a name="l01253"></a>01253 <span class="comment">// template&lt;class sq_T&gt;</span>
+<a name="l01254"></a>01254 <span class="comment">// double enorm&lt;sq_T&gt;::eval ( const vec &amp;val ) const {</span>
+<a name="l01255"></a>01255 <span class="comment">//      double pdfl,e;</span>
+<a name="l01256"></a>01256 <span class="comment">//      pdfl = evallog ( val );</span>
+<a name="l01257"></a>01257 <span class="comment">//      e = exp ( pdfl );</span>
+<a name="l01258"></a>01258 <span class="comment">//      return e;</span>
+<a name="l01259"></a>01259 <span class="comment">// };</span>
+<a name="l01260"></a>01260 
+<a name="l01261"></a>01261 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt;
+<a name="l01262"></a><a class="code" href="classbdm_1_1enorm.html#e13aeed5b543b2179bacdc4fa2ae47a3">01262</a> <span class="keywordtype">double</span> <a class="code" href="classbdm_1_1enorm.html#e13aeed5b543b2179bacdc4fa2ae47a3" title="Evaluate normalized log-probability.">enorm&lt;sq_T&gt;::evallog_nn</a> (<span class="keyword">const</span> vec &amp;val)<span class="keyword"> const</span>
+<a name="l01263"></a>01263 <span class="keyword"></span>{
+<a name="l01264"></a>01264         <span class="comment">// 1.83787706640935 = log(2pi)</span>
+<a name="l01265"></a>01265         <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>
+<a name="l01266"></a>01266         <span class="keywordflow">return</span>  tmp;
+<a name="l01267"></a>01267 };
 <a name="l01268"></a>01268 
 <a name="l01269"></a>01269 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt;
-<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&lt;epdf&gt;</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&lt;sq_T&gt;::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> &amp;rvn )<span class="keyword"> const</span>
+<a name="l01270"></a><a class="code" href="classbdm_1_1enorm.html#25785343aff102cc5df1cab08ba16d32">01270</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&lt;sq_T&gt;::lognc</a> ()<span class="keyword"> const</span>
 <a name="l01271"></a>01271 <span class="keyword"></span>{
-<a name="l01272"></a>01272         <a class="code" href="classbdm_1_1enorm.html" title="Gaussian density with positive definite (decomposed) covariance matrix.">enorm&lt;sq_T&gt;</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&lt;sq_T&gt;</a> ();
-<a name="l01273"></a>01273         <a class="code" href="classbdm_1_1shared__ptr.html">shared_ptr&lt;epdf&gt;</a> narrow(tmp);
-<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 );
-<a name="l01275"></a>01275         <span class="keywordflow">return</span> narrow;
-<a name="l01276"></a>01276 }
+<a name="l01272"></a>01272         <span class="comment">// 1.83787706640935 = log(2pi)</span>
+<a name="l01273"></a>01273         <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());
+<a name="l01274"></a>01274         <span class="keywordflow">return</span> tmp;
+<a name="l01275"></a>01275 };
+<a name="l01276"></a>01276 
 <a name="l01277"></a>01277 
-<a name="l01278"></a>01278 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt;
-<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&lt;sq_T&gt;::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> &amp;rvn, <a class="code" href="classbdm_1_1enorm.html" title="Gaussian density with positive definite (decomposed) covariance matrix.">enorm&lt;sq_T&gt;</a> &amp;target )<span class="keyword"> const</span>
-<a name="l01280"></a>01280 <span class="keyword"></span>{
-<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>);
-<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>);
-<a name="l01283"></a>01283 
-<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>
+<a name="l01278"></a>01278 <span class="comment">// template&lt;class sq_T&gt;</span>
+<a name="l01279"></a>01279 <span class="comment">// vec mlnorm&lt;sq_T&gt;::samplecond (const  vec &amp;cond, double &amp;lik ) {</span>
+<a name="l01280"></a>01280 <span class="comment">//      this-&gt;condition ( cond );</span>
+<a name="l01281"></a>01281 <span class="comment">//      vec smp = epdf.sample();</span>
+<a name="l01282"></a>01282 <span class="comment">//      lik = epdf.eval ( smp );</span>
+<a name="l01283"></a>01283 <span class="comment">//      return smp;</span>
+<a name="l01284"></a>01284 <span class="comment">// }</span>
 <a name="l01285"></a>01285 
-<a name="l01286"></a>01286         target.<a class="code" href="classbdm_1_1epdf.html#f423e28448dbb69ef4905295ec8de8ff" title="Name its rv.">set_rv</a> ( rvn );
-<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);
-<a name="l01288"></a>01288 }
-<a name="l01289"></a>01289 
-<a name="l01290"></a>01290 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt;
-<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&lt;mpdf&gt;</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&lt;sq_T&gt;::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> &amp;rvn )<span class="keyword"> const</span>
-<a name="l01292"></a>01292 <span class="keyword"></span>{
-<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&lt;sq_T&gt;</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&lt;sq_T&gt;</a> ();
-<a name="l01294"></a>01294         <a class="code" href="classbdm_1_1shared__ptr.html">shared_ptr&lt;mpdf&gt;</a> narrow(tmp);
-<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 );
-<a name="l01296"></a>01296         <span class="keywordflow">return</span> narrow;
-<a name="l01297"></a>01297 }
-<a name="l01298"></a>01298 
-<a name="l01299"></a>01299 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt;
-<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&lt;sq_T&gt;::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> &amp;rvn, <a class="code" href="classbdm_1_1mpdf.html" title="Conditional probability density, e.g. modeling , where  is random variable, rv, and...">mpdf</a> &amp;target )<span class="keyword"> const</span>
-<a name="l01301"></a>01301 <span class="keyword"></span>{
-<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&lt;sq_T&gt;</a> TMlnorm;
+<a name="l01286"></a>01286 <span class="comment">// template&lt;class sq_T&gt;</span>
+<a name="l01287"></a>01287 <span class="comment">// mat mlnorm&lt;sq_T&gt;::samplecond (const vec &amp;cond, vec &amp;lik, int n ) {</span>
+<a name="l01288"></a>01288 <span class="comment">//      int i;</span>
+<a name="l01289"></a>01289 <span class="comment">//      int dim = rv.count();</span>
+<a name="l01290"></a>01290 <span class="comment">//      mat Smp ( dim,n );</span>
+<a name="l01291"></a>01291 <span class="comment">//      vec smp ( dim );</span>
+<a name="l01292"></a>01292 <span class="comment">//      this-&gt;condition ( cond );</span>
+<a name="l01293"></a>01293 <span class="comment">//</span>
+<a name="l01294"></a>01294 <span class="comment">//      for ( i=0; i&lt;n; i++ ) {</span>
+<a name="l01295"></a>01295 <span class="comment">//              smp = epdf.sample();</span>
+<a name="l01296"></a>01296 <span class="comment">//              lik ( i ) = epdf.eval ( smp );</span>
+<a name="l01297"></a>01297 <span class="comment">//              Smp.set_col ( i ,smp );</span>
+<a name="l01298"></a>01298 <span class="comment">//      }</span>
+<a name="l01299"></a>01299 <span class="comment">//</span>
+<a name="l01300"></a>01300 <span class="comment">//      return Smp;</span>
+<a name="l01301"></a>01301 <span class="comment">// }</span>
+<a name="l01302"></a>01302 
 <a name="l01303"></a>01303 
-<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>);
-<a name="l01305"></a>01305         TMlnorm &amp;uptarget = <span class="keyword">dynamic_cast&lt;</span>TMlnorm &amp;<span class="keyword">&gt;</span>(target);
-<a name="l01306"></a>01306 
-<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);
-<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>);
-<a name="l01309"></a>01309         <span class="comment">//Permutation vector of the new R</span>
-<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>);
-<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>);
-<a name="l01312"></a>01312         ivec perm = concat (irvn , irvc);
-<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);
-<a name="l01314"></a>01314 
-<a name="l01315"></a>01315         <span class="comment">//fixme - could this be done in general for all sq_T?</span>
-<a name="l01316"></a>01316         mat S = Rn.to_mat();
-<a name="l01317"></a>01317         <span class="comment">//fixme</span>
-<a name="l01318"></a>01318         <span class="keywordtype">int</span> n = rvn.<a class="code" href="classbdm_1_1RV.html#de30156104f61d86c94f758861418089">_dsize</a>() - 1;
-<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;
-<a name="l01320"></a>01320         mat S11 = S.get (0, n, 0, n);
-<a name="l01321"></a>01321         mat S12 = S.get (0, n , rvn.<a class="code" href="classbdm_1_1RV.html#de30156104f61d86c94f758861418089">_dsize</a>(), end);
-<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);
-<a name="l01323"></a>01323 
-<a name="l01324"></a>01324         vec mu1 = <a class="code" href="classbdm_1_1enorm.html#c702a194720853570d08b65482f842c7" title="mean value">mu</a> (irvn);
-<a name="l01325"></a>01325         vec mu2 = <a class="code" href="classbdm_1_1enorm.html#c702a194720853570d08b65482f842c7" title="mean value">mu</a> (irvc);
-<a name="l01326"></a>01326         mat A = S12 * inv (S22);
-<a name="l01327"></a>01327         sq_T R_n (S11 - A *S12.T());
-<a name="l01328"></a>01328 
-<a name="l01329"></a>01329         uptarget.set_rv (rvn);
-<a name="l01330"></a>01330         uptarget.set_rvc (rvc);
-<a name="l01331"></a>01331         uptarget.set_parameters (A, mu1 - A*mu2, R_n);
+<a name="l01304"></a>01304 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt;
+<a name="l01305"></a><a class="code" href="classbdm_1_1enorm.html#dcb739443669ba0a8faf634196284c08">01305</a> <a class="code" href="classbdm_1_1shared__ptr.html">shared_ptr&lt;epdf&gt;</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&lt;sq_T&gt;::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> &amp;rvn )<span class="keyword"> const</span>
+<a name="l01306"></a>01306 <span class="keyword"></span>{
+<a name="l01307"></a>01307         <a class="code" href="classbdm_1_1enorm.html" title="Gaussian density with positive definite (decomposed) covariance matrix.">enorm&lt;sq_T&gt;</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&lt;sq_T&gt;</a> ();
+<a name="l01308"></a>01308         <a class="code" href="classbdm_1_1shared__ptr.html">shared_ptr&lt;epdf&gt;</a> narrow(tmp);
+<a name="l01309"></a>01309         <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 );
+<a name="l01310"></a>01310         <span class="keywordflow">return</span> narrow;
+<a name="l01311"></a>01311 }
+<a name="l01312"></a>01312 
+<a name="l01313"></a>01313 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt;
+<a name="l01314"></a>01314 <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&lt;sq_T&gt;::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> &amp;rvn, <a class="code" href="classbdm_1_1enorm.html" title="Gaussian density with positive definite (decomposed) covariance matrix.">enorm&lt;sq_T&gt;</a> &amp;target )<span class="keyword"> const</span>
+<a name="l01315"></a>01315 <span class="keyword"></span>{
+<a name="l01316"></a>01316         <a class="code" href="bdmerror_8h.html#89a0f906b242b79c5d3d342291b2cab4" title="Throw std::runtime_exception if t is not true and NDEBUG is not defined.">bdm_assert_debug</a> (<a class="code" href="classbdm_1_1epdf.html#c4b863ff84c7a4882fb3ad18556027f9" title="True if rv is assigned.">isnamed</a>(), <span class="stringliteral">"rv description is not assigned"</span>);
+<a name="l01317"></a>01317         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>);
+<a name="l01318"></a>01318 
+<a name="l01319"></a>01319         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>
+<a name="l01320"></a>01320 
+<a name="l01321"></a>01321         target.<a class="code" href="classbdm_1_1epdf.html#f423e28448dbb69ef4905295ec8de8ff" title="Name its rv.">set_rv</a> ( rvn );
+<a name="l01322"></a>01322         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);
+<a name="l01323"></a>01323 }
+<a name="l01324"></a>01324 
+<a name="l01325"></a>01325 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt;
+<a name="l01326"></a><a class="code" href="classbdm_1_1enorm.html#40201ca12c6900f7aeb493bb7c582e20">01326</a> <a class="code" href="classbdm_1_1shared__ptr.html">shared_ptr&lt;mpdf&gt;</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&lt;sq_T&gt;::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> &amp;rvn )<span class="keyword"> const</span>
+<a name="l01327"></a>01327 <span class="keyword"></span>{
+<a name="l01328"></a>01328         <a class="code" href="classbdm_1_1mlnorm.html" title="Normal distributed linear function with linear function of mean value;.">mlnorm&lt;sq_T&gt;</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&lt;sq_T&gt;</a> ();
+<a name="l01329"></a>01329         <a class="code" href="classbdm_1_1shared__ptr.html">shared_ptr&lt;mpdf&gt;</a> narrow(tmp);
+<a name="l01330"></a>01330         <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 );
+<a name="l01331"></a>01331         <span class="keywordflow">return</span> narrow;
 <a name="l01332"></a>01332 }
 <a name="l01333"></a>01333 
-<a name="l01336"></a>01336 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt;
-<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&lt;sq_T &gt;::set_parameters</a> (<span class="keyword">const</span> <a class="code" href="classbdm_1_1shared__ptr.html">shared_ptr&lt;fnc&gt;</a> &amp;g0, <span class="keyword">const</span> sq_T &amp;R0) {
-<a name="l01338"></a>01338         g = g0;
-<a name="l01339"></a>01339         this-&gt;<a class="code" href="classbdm_1_1mpdf__internal.html#47bab632af15120c88aad647ae129468" title="Internal epdf used for sampling.">iepdf</a>.set_parameters (zeros (g-&gt;dimension()), R0);
-<a name="l01340"></a>01340 }
+<a name="l01334"></a>01334 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt;
+<a name="l01335"></a>01335 <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&lt;sq_T&gt;::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> &amp;rvn, <a class="code" href="classbdm_1_1mpdf.html" title="Conditional probability density, e.g. modeling , where  is random variable, rv, and...">mpdf</a> &amp;target )<span class="keyword"> const</span>
+<a name="l01336"></a>01336 <span class="keyword"></span>{
+<a name="l01337"></a>01337         <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&lt;sq_T&gt;</a> TMlnorm;
+<a name="l01338"></a>01338 
+<a name="l01339"></a>01339         <a class="code" href="bdmerror_8h.html#89a0f906b242b79c5d3d342291b2cab4" title="Throw std::runtime_exception if t is not true and NDEBUG is not defined.">bdm_assert_debug</a> (<a class="code" href="classbdm_1_1epdf.html#c4b863ff84c7a4882fb3ad18556027f9" title="True if rv is assigned.">isnamed</a>(), <span class="stringliteral">"rvs are not assigned"</span>);
+<a name="l01340"></a>01340         TMlnorm &amp;uptarget = <span class="keyword">dynamic_cast&lt;</span>TMlnorm &amp;<span class="keyword">&gt;</span>(target);
 <a name="l01341"></a>01341 
-<a name="l01342"></a>01342 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt;
-<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&lt;sq_T &gt;::condition</a> (<span class="keyword">const</span> vec &amp;cond) {this-&gt;<a class="code" href="classbdm_1_1mpdf__internal.html#47bab632af15120c88aad647ae129468" title="Internal epdf used for sampling.">iepdf</a>._mu() = g-&gt;eval (cond);};
-<a name="l01344"></a>01344 
-<a name="l01346"></a>01346 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt;
-<a name="l01347"></a>01347 std::ostream &amp;operator&lt;&lt; (std::ostream &amp;os,  mlnorm&lt;sq_T&gt; &amp;ml)
-<a name="l01348"></a>01348 {
-<a name="l01349"></a>01349         os &lt;&lt; <span class="stringliteral">"A:"</span> &lt;&lt; ml.A &lt;&lt; endl;
-<a name="l01350"></a>01350         os &lt;&lt; <span class="stringliteral">"mu:"</span> &lt;&lt; ml.mu_const &lt;&lt; endl;
-<a name="l01351"></a>01351         os &lt;&lt; <span class="stringliteral">"R:"</span> &lt;&lt; ml._R() &lt;&lt; endl;
-<a name="l01352"></a>01352         <span class="keywordflow">return</span> os;
-<a name="l01353"></a>01353 };
-<a name="l01354"></a>01354 
-<a name="l01355"></a>01355 }
-<a name="l01356"></a>01356 <span class="preprocessor">#endif //EF_H</span>
+<a name="l01342"></a>01342         <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);
+<a name="l01343"></a>01343         <a class="code" href="bdmerror_8h.html#89a0f906b242b79c5d3d342291b2cab4" title="Throw std::runtime_exception if t is not true and NDEBUG is not defined.">bdm_assert_debug</a> ( (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>);
+<a name="l01344"></a>01344         <span class="comment">//Permutation vector of the new R</span>
+<a name="l01345"></a>01345         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>);
+<a name="l01346"></a>01346         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>);
+<a name="l01347"></a>01347         ivec perm = concat (irvn , irvc);
+<a name="l01348"></a>01348         sq_T Rn (<a class="code" href="classbdm_1_1enorm.html#2d92dde696b2a7a5b10ddef5d22ba2c2" title="Covariance matrix in decomposed form.">R</a>, perm);
+<a name="l01349"></a>01349 
+<a name="l01350"></a>01350         <span class="comment">//fixme - could this be done in general for all sq_T?</span>
+<a name="l01351"></a>01351         mat S = Rn.to_mat();
+<a name="l01352"></a>01352         <span class="comment">//fixme</span>
+<a name="l01353"></a>01353         <span class="keywordtype">int</span> n = rvn.<a class="code" href="classbdm_1_1RV.html#de30156104f61d86c94f758861418089">_dsize</a>() - 1;
+<a name="l01354"></a>01354         <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;
+<a name="l01355"></a>01355         mat S11 = S.get (0, n, 0, n);
+<a name="l01356"></a>01356         mat S12 = S.get (0, n , rvn.<a class="code" href="classbdm_1_1RV.html#de30156104f61d86c94f758861418089">_dsize</a>(), end);
+<a name="l01357"></a>01357         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);
+<a name="l01358"></a>01358 
+<a name="l01359"></a>01359         vec mu1 = <a class="code" href="classbdm_1_1enorm.html#c702a194720853570d08b65482f842c7" title="mean value">mu</a> (irvn);
+<a name="l01360"></a>01360         vec mu2 = <a class="code" href="classbdm_1_1enorm.html#c702a194720853570d08b65482f842c7" title="mean value">mu</a> (irvc);
+<a name="l01361"></a>01361         mat A = S12 * inv (S22);
+<a name="l01362"></a>01362         sq_T R_n (S11 - A *S12.T());
+<a name="l01363"></a>01363 
+<a name="l01364"></a>01364         uptarget.set_rv (rvn);
+<a name="l01365"></a>01365         uptarget.set_rvc (rvc);
+<a name="l01366"></a>01366         uptarget.set_parameters (A, mu1 - A*mu2, R_n);
+<a name="l01367"></a>01367 }
+<a name="l01368"></a>01368 
+<a name="l01371"></a>01371 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt;
+<a name="l01372"></a><a class="code" href="classbdm_1_1mgnorm.html#b736332d20e418bf50d45836e129f339">01372</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1mgnorm.html#b736332d20e418bf50d45836e129f339" title="set mean function">mgnorm&lt;sq_T &gt;::set_parameters</a> (<span class="keyword">const</span> <a class="code" href="classbdm_1_1shared__ptr.html">shared_ptr&lt;fnc&gt;</a> &amp;g0, <span class="keyword">const</span> sq_T &amp;R0) {
+<a name="l01373"></a>01373         g = g0;
+<a name="l01374"></a>01374         this-&gt;<a class="code" href="classbdm_1_1mpdf__internal.html#47bab632af15120c88aad647ae129468" title="Internal epdf used for sampling.">iepdf</a>.set_parameters (zeros (g-&gt;dimension()), R0);
+<a name="l01375"></a>01375 }
+<a name="l01376"></a>01376 
+<a name="l01377"></a>01377 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt;
+<a name="l01378"></a><a class="code" href="classbdm_1_1mgnorm.html#b31d63472cf6a1030cd8dbd8094c1f6d">01378</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1mgnorm.html#b31d63472cf6a1030cd8dbd8094c1f6d">mgnorm&lt;sq_T &gt;::condition</a> (<span class="keyword">const</span> vec &amp;cond) {this-&gt;<a class="code" href="classbdm_1_1mpdf__internal.html#47bab632af15120c88aad647ae129468" title="Internal epdf used for sampling.">iepdf</a>._mu() = g-&gt;eval (cond);};
+<a name="l01379"></a>01379 
+<a name="l01381"></a>01381 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt;
+<a name="l01382"></a>01382 std::ostream &amp;operator&lt;&lt; (std::ostream &amp;os,  mlnorm&lt;sq_T&gt; &amp;ml)
+<a name="l01383"></a>01383 {
+<a name="l01384"></a>01384         os &lt;&lt; <span class="stringliteral">"A:"</span> &lt;&lt; ml.A &lt;&lt; endl;
+<a name="l01385"></a>01385         os &lt;&lt; <span class="stringliteral">"mu:"</span> &lt;&lt; ml.mu_const &lt;&lt; endl;
+<a name="l01386"></a>01386         os &lt;&lt; <span class="stringliteral">"R:"</span> &lt;&lt; ml._R() &lt;&lt; endl;
+<a name="l01387"></a>01387         <span class="keywordflow">return</span> os;
+<a name="l01388"></a>01388 };
+<a name="l01389"></a>01389 
+<a name="l01390"></a>01390 }
+<a name="l01391"></a>01391 <span class="preprocessor">#endif //EF_H</span>
 </pre></div></div>
-<hr size="1"><address style="text-align: right;"><small>Generated on Sun Aug 16 17:58:18 2009 for mixpp by&nbsp;
+<hr size="1"><address style="text-align: right;"><small>Generated on Sat Aug 29 20:49:42 2009 for mixpp by&nbsp;
 <a href="http://www.doxygen.org/index.html">
 <img src="doxygen.png" alt="doxygen" align="middle" border="0"></a> 1.5.8 </small></address>