root/doc/html/libEF_8h-source.html @ 125

Revision 106, 60.2 kB (checked in by smidl, 17 years ago)

doc

Line 
1<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN">
2<html><head><meta http-equiv="Content-Type" content="text/html;charset=UTF-8">
3<title>mixpp: work/mixpp/bdm/stat/libEF.h Source File</title>
4<link href="doxygen.css" rel="stylesheet" type="text/css">
5<link href="tabs.css" rel="stylesheet" type="text/css">
6</head><body>
7<!-- Generated by Doxygen 1.5.5 -->
8<div class="navigation" id="top">
9  <div class="tabs">
10    <ul>
11      <li><a href="index.html"><span>Main&nbsp;Page</span></a></li>
12      <li><a href="pages.html"><span>Related&nbsp;Pages</span></a></li>
13      <li><a href="annotated.html"><span>Classes</span></a></li>
14      <li class="current"><a href="files.html"><span>Files</span></a></li>
15    </ul>
16  </div>
17<h1>work/mixpp/bdm/stat/libEF.h</h1><a href="libEF_8h.html">Go to the documentation of this file.</a><div class="fragment"><pre class="fragment"><a name="l00001"></a>00001
18<a name="l00013"></a>00013 <span class="preprocessor">#ifndef EF_H</span>
19<a name="l00014"></a>00014 <span class="preprocessor"></span><span class="preprocessor">#define EF_H</span>
20<a name="l00015"></a>00015 <span class="preprocessor"></span>
21<a name="l00016"></a>00016 <span class="preprocessor">#include &lt;itpp/itbase.h&gt;</span>
22<a name="l00017"></a>00017 <span class="preprocessor">#include "../math/libDC.h"</span>
23<a name="l00018"></a>00018 <span class="preprocessor">#include "<a class="code" href="libBM_8h.html" title="Bayesian Models (bm) that use Bayes rule to learn from observations.">libBM.h</a>"</span>
24<a name="l00019"></a>00019 <span class="preprocessor">#include "../itpp_ext.h"</span>
25<a name="l00020"></a>00020 <span class="comment">//#include &lt;std&gt;</span>
26<a name="l00021"></a>00021
27<a name="l00022"></a>00022 <span class="keyword">using namespace </span>itpp;
28<a name="l00023"></a>00023
29<a name="l00024"></a>00024
30<a name="l00026"></a>00026 <span class="keyword">extern</span> Uniform_RNG UniRNG;
31<a name="l00028"></a>00028 <span class="keyword">extern</span> Normal_RNG NorRNG;
32<a name="l00030"></a>00030 <span class="keyword">extern</span> <a class="code" href="classitpp_1_1Gamma__RNG.html" title="Gamma distribution.">Gamma_RNG</a> GamRNG;
33<a name="l00031"></a>00031
34<a name="l00038"></a><a class="code" href="classeEF.html">00038</a> <span class="keyword">class </span><a class="code" href="classeEF.html" title="General conjugate exponential family posterior density.">eEF</a> : <span class="keyword">public</span> <a class="code" href="classepdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a> {
35<a name="l00039"></a>00039 <span class="keyword">public</span>:
36<a name="l00040"></a>00040 <span class="comment">//      eEF() :epdf() {};</span>
37<a name="l00042"></a><a class="code" href="classeEF.html#7e3c63655e8375c76bf1f421245427a7">00042</a> <span class="comment"></span>        <a class="code" href="classeEF.html#7e3c63655e8375c76bf1f421245427a7" title="default constructor">eEF</a> ( <span class="keyword">const</span> <a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> &amp;<a class="code" href="classepdf.html#74da992e3f5d598da8850b646b79b9d9" title="Identified of the random variable.">rv</a> ) :<a class="code" href="classepdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a> ( rv ) {};
38<a name="l00044"></a>00044         <span class="keyword">virtual</span> <span class="keywordtype">double</span> <a class="code" href="classeEF.html#69e5680dac10375d62520d26c672477d" title="logarithm of the normalizing constant, ">lognc</a>()<span class="keyword">const</span> =0;
39<a name="l00046"></a><a class="code" href="classeEF.html#fd88bc35550ec8fe9281d358216d0fcf">00046</a>         <span class="keyword">virtual</span> <span class="keywordtype">void</span> <a class="code" href="classeEF.html#fd88bc35550ec8fe9281d358216d0fcf" title="TODO decide if it is really needed.">tupdate</a> ( <span class="keywordtype">double</span> phi, mat &amp;vbar, <span class="keywordtype">double</span> nubar ) {};
40<a name="l00048"></a><a class="code" href="classeEF.html#5863718c3b2fb1496dece10c5b745d5c">00048</a>         <span class="keyword">virtual</span> <span class="keywordtype">void</span> <a class="code" href="classeEF.html#5863718c3b2fb1496dece10c5b745d5c" title="TODO decide if it is really needed.">dupdate</a> ( mat &amp;v,<span class="keywordtype">double</span> nu=1.0 ) {};
41<a name="l00049"></a>00049 };
42<a name="l00050"></a>00050
43<a name="l00057"></a><a class="code" href="classmEF.html">00057</a> <span class="keyword">class </span><a class="code" href="classmEF.html" title="Exponential family model.">mEF</a> : <span class="keyword">public</span> <a class="code" href="classmpdf.html" title="Conditional probability density, e.g. modeling some dependencies.">mpdf</a> {
44<a name="l00058"></a>00058
45<a name="l00059"></a>00059 <span class="keyword">public</span>:
46<a name="l00061"></a><a class="code" href="classmEF.html#8bf51fe8654d7b83c8c8afeb19409d4f">00061</a>         <a class="code" href="classmEF.html#8bf51fe8654d7b83c8c8afeb19409d4f" title="Default constructor.">mEF</a> ( <span class="keyword">const</span> <a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> &amp;rv0, <span class="keyword">const</span> <a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> &amp;rvc0 ) :<a class="code" href="classmpdf.html" title="Conditional probability density, e.g. modeling some dependencies.">mpdf</a> ( rv0,rvc0 ) {};
47<a name="l00062"></a>00062 };
48<a name="l00063"></a>00063
49<a name="l00069"></a>00069 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt;
50<a name="l00070"></a>00070
51<a name="l00071"></a><a class="code" href="classenorm.html">00071</a> <span class="keyword">class </span><a class="code" href="classenorm.html" title="Gaussian density with positive definite (decomposed) covariance matrix.">enorm</a> : <span class="keyword">public</span> <a class="code" href="classeEF.html" title="General conjugate exponential family posterior density.">eEF</a> {
52<a name="l00072"></a>00072 <span class="keyword">protected</span>:
53<a name="l00074"></a><a class="code" href="classenorm.html#71fde0d54bba147e00f612577f95ad20">00074</a>         vec <a class="code" href="classenorm.html#71fde0d54bba147e00f612577f95ad20" title="mean value">mu</a>;
54<a name="l00076"></a><a class="code" href="classenorm.html#4ccc8d8514d644ef1c98d8ab023748a1">00076</a>         sq_T <a class="code" href="classenorm.html#4ccc8d8514d644ef1c98d8ab023748a1" title="Covariance matrix in decomposed form.">R</a>;
55<a name="l00078"></a><a class="code" href="classenorm.html#6938fc390a19cdaf6ad4503fcbaada4e">00078</a>         <span class="keywordtype">int</span> <a class="code" href="classenorm.html#6938fc390a19cdaf6ad4503fcbaada4e" title="dimension (redundant from rv.count() for easier coding )">dim</a>;
56<a name="l00079"></a>00079 <span class="keyword">public</span>:
57<a name="l00080"></a>00080 <span class="comment">//      enorm() :eEF() {};</span>
58<a name="l00082"></a>00082 <span class="comment"></span>        <a class="code" href="classenorm.html#7b5cb487a2570e8109bfdc0df149aa06" title="Default constructor.">enorm</a> ( <a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> &amp;<a class="code" href="classepdf.html#74da992e3f5d598da8850b646b79b9d9" title="Identified of the random variable.">rv</a> );
59<a name="l00084"></a>00084         <span class="keywordtype">void</span> <a class="code" href="classenorm.html#1394a65caa6e00d42e00cc99b12227af" title="Set mean value mu and covariance R.">set_parameters</a> ( <span class="keyword">const</span> vec &amp;<a class="code" href="classenorm.html#71fde0d54bba147e00f612577f95ad20" title="mean value">mu</a>,<span class="keyword">const</span> sq_T &amp;<a class="code" href="classenorm.html#4ccc8d8514d644ef1c98d8ab023748a1" title="Covariance matrix in decomposed form.">R</a> );
60<a name="l00086"></a>00086         <span class="keywordtype">void</span> <a class="code" href="classenorm.html#5b5fd142b6b17ea334597960e3fe126a" title="tupdate in exponential form (not really handy)">tupdate</a> ( <span class="keywordtype">double</span> phi, mat &amp;vbar, <span class="keywordtype">double</span> nubar );
61<a name="l00088"></a>00088         <span class="keywordtype">void</span> <a class="code" href="classenorm.html#5bf185e31e5954fceb90ada3debd2ff2" title="dupdate in exponential form (not really handy)">dupdate</a> ( mat &amp;v,<span class="keywordtype">double</span> nu=1.0 );
62<a name="l00089"></a>00089
63<a name="l00090"></a>00090         vec <a class="code" href="classenorm.html#60b47544f6181ffd4530d3e415ce12c5" title="Returns the required moment of the epdf.">sample</a>() <span class="keyword">const</span>;
64<a name="l00092"></a>00092         mat <a class="code" href="classenorm.html#60b47544f6181ffd4530d3e415ce12c5" title="Returns the required moment of the epdf.">sample</a> ( <span class="keywordtype">int</span> N ) <span class="keyword">const</span>;
65<a name="l00093"></a>00093         <span class="keywordtype">double</span> <a class="code" href="classenorm.html#b9e1dfd33692d7b3f1a59f17b0e61bd0" title="Compute probability of argument val.">eval</a> ( <span class="keyword">const</span> vec &amp;val ) <span class="keyword">const</span> ;
66<a name="l00094"></a>00094         <span class="keywordtype">double</span> <a class="code" href="classenorm.html#609a7c33dbb4fdfab050f3bdd1122401" title="Compute log-probability of argument val.">evalpdflog</a> ( <span class="keyword">const</span> vec &amp;val ) <span class="keyword">const</span>;
67<a name="l00095"></a>00095         <span class="keywordtype">double</span> <a class="code" href="classenorm.html#b289a36a69db59d182bb6eba9c05d4a8" title="logarithm of the normalizing constant, ">lognc</a> () <span class="keyword">const</span>;
68<a name="l00096"></a><a class="code" href="classenorm.html#50fa84da7bae02f7af17a98f37566899">00096</a>         vec <a class="code" href="classenorm.html#50fa84da7bae02f7af17a98f37566899" title="return expected value">mean</a>()<span class="keyword"> const </span>{<span class="keywordflow">return</span> <a class="code" href="classenorm.html#71fde0d54bba147e00f612577f95ad20" title="mean value">mu</a>;}
69<a name="l00097"></a>00097
70<a name="l00098"></a>00098 <span class="comment">//Access methods</span>
71<a name="l00100"></a><a class="code" href="classenorm.html#0b8cb284e5af920a1b64a21d057ec5ac">00100</a> <span class="comment"></span>        vec&amp; <a class="code" href="classenorm.html#0b8cb284e5af920a1b64a21d057ec5ac" title="returns a pointer to the internal mean value. Use with Care!">_mu</a>() {<span class="keywordflow">return</span> <a class="code" href="classenorm.html#71fde0d54bba147e00f612577f95ad20" title="mean value">mu</a>;}
72<a name="l00101"></a>00101         
73<a name="l00103"></a><a class="code" href="classenorm.html#d892a38f03be12e572ea57d9689cef6b">00103</a>         <span class="keywordtype">void</span> <a class="code" href="classenorm.html#d892a38f03be12e572ea57d9689cef6b" title="access function">set_mu</a>(<span class="keyword">const</span> vec mu0) { <a class="code" href="classenorm.html#71fde0d54bba147e00f612577f95ad20" title="mean value">mu</a>=mu0;}
74<a name="l00104"></a>00104
75<a name="l00106"></a><a class="code" href="classenorm.html#7a5034b25771a84450a990d10fc40ac9">00106</a>         sq_T&amp; <a class="code" href="classenorm.html#7a5034b25771a84450a990d10fc40ac9" title="returns pointers to the internal variance and its inverse. Use with Care!">_R</a>() {<span class="keywordflow">return</span> <a class="code" href="classenorm.html#4ccc8d8514d644ef1c98d8ab023748a1" title="Covariance matrix in decomposed form.">R</a>;}
76<a name="l00107"></a>00107
77<a name="l00109"></a><a class="code" href="classenorm.html#9b9f58dc86affa23511c246887420658">00109</a>         mat <a class="code" href="classenorm.html#9b9f58dc86affa23511c246887420658" title="access method">getR</a> () {<span class="keywordflow">return</span> <a class="code" href="classenorm.html#4ccc8d8514d644ef1c98d8ab023748a1" title="Covariance matrix in decomposed form.">R</a>.to_mat();}
78<a name="l00110"></a>00110 };
79<a name="l00111"></a>00111
80<a name="l00117"></a><a class="code" href="classegiw.html">00117</a> <span class="keyword">class </span><a class="code" href="classegiw.html" title="Gauss-inverse-Wishart density stored in LD form.">egiw</a> : <span class="keyword">public</span> <a class="code" href="classeEF.html" title="General conjugate exponential family posterior density.">eEF</a> {
81<a name="l00118"></a>00118 <span class="keyword">protected</span>:
82<a name="l00120"></a><a class="code" href="classegiw.html#f343d03ede89db820edf44a6297fa442">00120</a>         <a class="code" href="classldmat.html" title="Matrix stored in LD form, (typically known as UD).">ldmat</a> <a class="code" href="classegiw.html#f343d03ede89db820edf44a6297fa442" title="Extended information matrix of sufficient statistics.">V</a>;
83<a name="l00122"></a><a class="code" href="classegiw.html#4a2f130b91afe84f6d62fed289d5d453">00122</a>         <span class="keywordtype">double</span> <a class="code" href="classegiw.html#4a2f130b91afe84f6d62fed289d5d453" title="Number of data records (degrees of freedom) of sufficient statistics.">nu</a>;
84<a name="l00123"></a>00123 <span class="keyword">public</span>:
85<a name="l00125"></a><a class="code" href="classegiw.html#c52a2173c6eb1490edce9c6c7c05d60b">00125</a>         <a class="code" href="classegiw.html#c52a2173c6eb1490edce9c6c7c05d60b" title="Default constructor.">egiw</a>(<a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> <a class="code" href="classepdf.html#74da992e3f5d598da8850b646b79b9d9" title="Identified of the random variable.">rv</a>, mat V0, <span class="keywordtype">double</span> nu0): <a class="code" href="classeEF.html" title="General conjugate exponential family posterior density.">eEF</a>(rv), <a class="code" href="classegiw.html#f343d03ede89db820edf44a6297fa442" title="Extended information matrix of sufficient statistics.">V</a>(V0), <a class="code" href="classegiw.html#4a2f130b91afe84f6d62fed289d5d453" title="Number of data records (degrees of freedom) of sufficient statistics.">nu</a>(nu0) {
86<a name="l00126"></a>00126                 it_assert_debug(rv.<a class="code" href="classRV.html#f5c7b8bd589eef09ccdf3329a0addea0" title="Return number of scalars in the RV.">count</a>()==<a class="code" href="classegiw.html#f343d03ede89db820edf44a6297fa442" title="Extended information matrix of sufficient statistics.">V</a>.<a class="code" href="classldmat.html#96dfb21865db4f5bd36fa70f9b0b1163" title="access function">rows</a>(),<span class="stringliteral">"Incompatible V0."</span>);
87<a name="l00127"></a>00127         }
88<a name="l00128"></a>00128
89<a name="l00129"></a>00129         vec <a class="code" href="classegiw.html#3d2c1f2ba0f9966781f1e0ae695e8a6f" title="Returns the required moment of the epdf.">sample</a>() <span class="keyword">const</span>;
90<a name="l00130"></a>00130         vec <a class="code" href="classegiw.html#6deb0ff2859f41ef7cbdf6a842cabb29" title="return expected value">mean</a>() <span class="keyword">const</span>;
91<a name="l00131"></a>00131         <span class="keywordtype">double</span> <a class="code" href="classegiw.html#425cbc53b377274e28c6add942bab62d" title="Compute log-probability of argument val.">evalpdflog</a> ( <span class="keyword">const</span> vec &amp;val ) <span class="keyword">const</span>;
92<a name="l00132"></a>00132         <span class="keywordtype">double</span> <a class="code" href="classegiw.html#70eb1a0b88459b227f919b425b0d3359" title="logarithm of the normalizing constant, ">lognc</a> () <span class="keyword">const</span>;
93<a name="l00133"></a>00133
94<a name="l00134"></a>00134         <span class="comment">//Access</span>
95<a name="l00136"></a><a class="code" href="classegiw.html#533e792e1175bfa06d5d595dc5d080d5">00136</a> <span class="comment"></span>        <a class="code" href="classldmat.html" title="Matrix stored in LD form, (typically known as UD).">ldmat</a>&amp; <a class="code" href="classegiw.html#533e792e1175bfa06d5d595dc5d080d5" title="returns a pointer to the internal statistics. Use with Care!">_V</a>() {<span class="keywordflow">return</span> <a class="code" href="classegiw.html#f343d03ede89db820edf44a6297fa442" title="Extended information matrix of sufficient statistics.">V</a>;}
96<a name="l00138"></a><a class="code" href="classegiw.html#08029c481ff95d24f093df0573879afe">00138</a>         <span class="keywordtype">double</span>&amp; <a class="code" href="classegiw.html#08029c481ff95d24f093df0573879afe" title="returns a pointer to the internal statistics. Use with Care!">_nu</a>() {<span class="keywordflow">return</span> <a class="code" href="classegiw.html#4a2f130b91afe84f6d62fed289d5d453" title="Number of data records (degrees of freedom) of sufficient statistics.">nu</a>;}
97<a name="l00139"></a>00139
98<a name="l00140"></a>00140 };
99<a name="l00141"></a>00141
100<a name="l00151"></a><a class="code" href="classegamma.html">00151</a> <span class="keyword">class </span><a class="code" href="classegamma.html" title="Gamma posterior density.">egamma</a> : <span class="keyword">public</span> <a class="code" href="classeEF.html" title="General conjugate exponential family posterior density.">eEF</a> {
101<a name="l00152"></a>00152 <span class="keyword">protected</span>:
102<a name="l00154"></a><a class="code" href="classegamma.html#376cebd8932546c440f21b182910b01b">00154</a>         vec <a class="code" href="classegamma.html#376cebd8932546c440f21b182910b01b" title="Vector .">alpha</a>;
103<a name="l00156"></a><a class="code" href="classegamma.html#cfc5f136467488a421ab22f886323790">00156</a>         vec <a class="code" href="classegamma.html#cfc5f136467488a421ab22f886323790" title="Vector .">beta</a>;
104<a name="l00157"></a>00157 <span class="keyword">public</span> :
105<a name="l00159"></a><a class="code" href="classegamma.html#4b1d34f3b244ea51a58ec10c468788c1">00159</a>         <a class="code" href="classegamma.html#4b1d34f3b244ea51a58ec10c468788c1" title="Default constructor.">egamma</a> ( <span class="keyword">const</span> <a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> &amp;<a class="code" href="classepdf.html#74da992e3f5d598da8850b646b79b9d9" title="Identified of the random variable.">rv</a> ) :<a class="code" href="classeEF.html" title="General conjugate exponential family posterior density.">eEF</a> ( rv ) {};
106<a name="l00161"></a><a class="code" href="classegamma.html#8e348b89be82b70471fe8c5630f61339">00161</a>         <span class="keywordtype">void</span> <a class="code" href="classegamma.html#8e348b89be82b70471fe8c5630f61339" title="Sets parameters.">set_parameters</a> ( <span class="keyword">const</span> vec &amp;a, <span class="keyword">const</span> vec &amp;b ) {<a class="code" href="classegamma.html#376cebd8932546c440f21b182910b01b" title="Vector .">alpha</a>=a,<a class="code" href="classegamma.html#cfc5f136467488a421ab22f886323790" title="Vector .">beta</a>=b;};
107<a name="l00162"></a>00162         vec <a class="code" href="classegamma.html#8e10c0021b5dfdd9cb62c6959b5ef425" title="Returns the required moment of the epdf.">sample</a>() <span class="keyword">const</span>;
108<a name="l00164"></a>00164         mat <a class="code" href="classegamma.html#8e10c0021b5dfdd9cb62c6959b5ef425" title="Returns the required moment of the epdf.">sample</a> ( <span class="keywordtype">int</span> N ) <span class="keyword">const</span>;
109<a name="l00165"></a>00165         <span class="keywordtype">double</span> <a class="code" href="classegamma.html#de84faac8f9799dfe2777ddbedf997ef" title="Compute log-probability of argument val.">evalpdflog</a> ( <span class="keyword">const</span> vec &amp;val ) <span class="keyword">const</span>;
110<a name="l00166"></a>00166         <span class="keywordtype">double</span> <a class="code" href="classegamma.html#d6dbbdb72360f9e54d64501f80318bb6" title="logarithm of the normalizing constant, ">lognc</a> () <span class="keyword">const</span>;
111<a name="l00168"></a><a class="code" href="classegamma.html#44445c56e60b91b377f207f8d5089790">00168</a>         <span class="keywordtype">void</span> <a class="code" href="classegamma.html#44445c56e60b91b377f207f8d5089790" title="Returns poiter to alpha and beta. Potentially dengerous: use with care!">_param</a> ( vec* &amp;a, vec* &amp;b ) {a=&amp;<a class="code" href="classegamma.html#376cebd8932546c440f21b182910b01b" title="Vector .">alpha</a>;b=&amp;<a class="code" href="classegamma.html#cfc5f136467488a421ab22f886323790" title="Vector .">beta</a>;};
112<a name="l00169"></a><a class="code" href="classegamma.html#6ab5ba56f7cdb2e5921c3e77524fa50a">00169</a>         vec <a class="code" href="classegamma.html#6ab5ba56f7cdb2e5921c3e77524fa50a" title="return expected value">mean</a>()<span class="keyword"> const </span>{vec pom ( <a class="code" href="classegamma.html#376cebd8932546c440f21b182910b01b" title="Vector .">alpha</a> ); pom/=<a class="code" href="classegamma.html#cfc5f136467488a421ab22f886323790" title="Vector .">beta</a>; <span class="keywordflow">return</span> pom;}
113<a name="l00170"></a>00170 };
114<a name="l00171"></a>00171 <span class="comment">/*</span>
115<a name="l00173"></a>00173 <span class="comment">class emix : public epdf {</span>
116<a name="l00174"></a>00174 <span class="comment">protected:</span>
117<a name="l00175"></a>00175 <span class="comment">        int n;</span>
118<a name="l00176"></a>00176 <span class="comment">        vec &amp;w;</span>
119<a name="l00177"></a>00177 <span class="comment">        Array&lt;epdf*&gt; Coms;</span>
120<a name="l00178"></a>00178 <span class="comment">public:</span>
121<a name="l00180"></a>00180 <span class="comment">        emix ( const RV &amp;rv, vec &amp;w0): epdf(rv), n(w0.length()), w(w0), Coms(n) {};</span>
122<a name="l00181"></a>00181 <span class="comment">        void set_parameters( int &amp;i, double wi, epdf* ep){w(i)=wi;Coms(i)=ep;}</span>
123<a name="l00182"></a>00182 <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>
124<a name="l00183"></a>00183 <span class="comment">        vec sample() {it_error ( "Not implemented" );return 0;}</span>
125<a name="l00184"></a>00184 <span class="comment">};</span>
126<a name="l00185"></a>00185 <span class="comment">*/</span>
127<a name="l00186"></a>00186
128<a name="l00188"></a>00188
129<a name="l00189"></a><a class="code" href="classeuni.html">00189</a> <span class="keyword">class </span><a class="code" href="classeuni.html" title="Uniform distributed density on a rectangular support.">euni</a>: <span class="keyword">public</span> <a class="code" href="classepdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a> {
130<a name="l00190"></a>00190 <span class="keyword">protected</span>:
131<a name="l00192"></a><a class="code" href="classeuni.html#ef42cd8d7645422048d46c46ec5cdac1">00192</a>         vec <a class="code" href="classeuni.html#ef42cd8d7645422048d46c46ec5cdac1" title="lower bound on support">low</a>;
132<a name="l00194"></a><a class="code" href="classeuni.html#71b6d6b41aeb61a7f76f682b72119231">00194</a>         vec <a class="code" href="classeuni.html#71b6d6b41aeb61a7f76f682b72119231" title="upper bound on support">high</a>;
133<a name="l00196"></a><a class="code" href="classeuni.html#52a6ff4a54010f88a6a19fca605c64a4">00196</a>         vec <a class="code" href="classeuni.html#52a6ff4a54010f88a6a19fca605c64a4" title="internal">distance</a>;
134<a name="l00198"></a><a class="code" href="classeuni.html#63105490e946e43372d6187ad1bafdda">00198</a>         <span class="keywordtype">double</span> <a class="code" href="classeuni.html#63105490e946e43372d6187ad1bafdda" title="normalizing coefficients">nk</a>;
135<a name="l00200"></a><a class="code" href="classeuni.html#f445a0ce24f39d14c1a4eed53fc8e2c3">00200</a>         <span class="keywordtype">double</span> <a class="code" href="classeuni.html#f445a0ce24f39d14c1a4eed53fc8e2c3" title="cache of log( nk )">lnk</a>;
136<a name="l00201"></a>00201 <span class="keyword">public</span>:
137<a name="l00203"></a><a class="code" href="classeuni.html#2537a6c239cff52e3ba814851a1116cd">00203</a>         <a class="code" href="classeuni.html#2537a6c239cff52e3ba814851a1116cd" title="Defualt constructor.">euni</a> ( <span class="keyword">const</span> <a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> <a class="code" href="classepdf.html#74da992e3f5d598da8850b646b79b9d9" title="Identified of the random variable.">rv</a> ) :<a class="code" href="classepdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a> ( rv ) {}
138<a name="l00204"></a><a class="code" href="classeuni.html#2723d4992900b5c5495bfa03628195ed">00204</a>         <span class="keywordtype">double</span> <a class="code" href="classeuni.html#2723d4992900b5c5495bfa03628195ed" title="Compute probability of argument val.">eval</a> ( <span class="keyword">const</span> vec &amp;val )<span class="keyword"> const  </span>{<span class="keywordflow">return</span> <a class="code" href="classeuni.html#63105490e946e43372d6187ad1bafdda" title="normalizing coefficients">nk</a>;}
139<a name="l00205"></a><a class="code" href="classeuni.html#06af95d514a6623ad4688bd2ad50ad71">00205</a>         <span class="keywordtype">double</span> <a class="code" href="classeuni.html#06af95d514a6623ad4688bd2ad50ad71" title="Compute log-probability of argument val.">evalpdflog</a> ( <span class="keyword">const</span> vec &amp;val )<span class="keyword"> const  </span>{<span class="keywordflow">return</span> <a class="code" href="classeuni.html#f445a0ce24f39d14c1a4eed53fc8e2c3" title="cache of log( nk )">lnk</a>;}
140<a name="l00206"></a><a class="code" href="classeuni.html#4a0e09392be17beaee120ba98fc038cd">00206</a>         vec <a class="code" href="classeuni.html#4a0e09392be17beaee120ba98fc038cd" title="Returns the required moment of the epdf.">sample</a>()<span class="keyword"> const </span>{
141<a name="l00207"></a>00207                 vec smp ( <a class="code" href="classepdf.html#74da992e3f5d598da8850b646b79b9d9" title="Identified of the random variable.">rv</a>.<a class="code" href="classRV.html#f5c7b8bd589eef09ccdf3329a0addea0" title="Return number of scalars in the RV.">count</a>() ); UniRNG.sample_vector ( <a class="code" href="classepdf.html#74da992e3f5d598da8850b646b79b9d9" title="Identified of the random variable.">rv</a>.<a class="code" href="classRV.html#f5c7b8bd589eef09ccdf3329a0addea0" title="Return number of scalars in the RV.">count</a>(),smp );
142<a name="l00208"></a>00208                 <span class="keywordflow">return</span> <a class="code" href="classeuni.html#ef42cd8d7645422048d46c46ec5cdac1" title="lower bound on support">low</a>+<a class="code" href="classeuni.html#52a6ff4a54010f88a6a19fca605c64a4" title="internal">distance</a>*smp;
143<a name="l00209"></a>00209         }
144<a name="l00211"></a><a class="code" href="classeuni.html#4fd7c6a05100616ad16ece405cad7bf2">00211</a>         <span class="keywordtype">void</span> <a class="code" href="classeuni.html#4fd7c6a05100616ad16ece405cad7bf2" title="set values of low and high ">set_parameters</a> ( <span class="keyword">const</span> vec &amp;low0, <span class="keyword">const</span> vec &amp;high0 ) {
145<a name="l00212"></a>00212                 <a class="code" href="classeuni.html#52a6ff4a54010f88a6a19fca605c64a4" title="internal">distance</a> = high0-low0;
146<a name="l00213"></a>00213                 it_assert_debug ( min ( <a class="code" href="classeuni.html#52a6ff4a54010f88a6a19fca605c64a4" title="internal">distance</a> ) &gt;0.0,<span class="stringliteral">"bad support"</span> );
147<a name="l00214"></a>00214                 <a class="code" href="classeuni.html#ef42cd8d7645422048d46c46ec5cdac1" title="lower bound on support">low</a> = low0;
148<a name="l00215"></a>00215                 <a class="code" href="classeuni.html#71b6d6b41aeb61a7f76f682b72119231" title="upper bound on support">high</a> = high0;
149<a name="l00216"></a>00216                 <a class="code" href="classeuni.html#63105490e946e43372d6187ad1bafdda" title="normalizing coefficients">nk</a> = prod ( 1.0/<a class="code" href="classeuni.html#52a6ff4a54010f88a6a19fca605c64a4" title="internal">distance</a> );
150<a name="l00217"></a>00217                 <a class="code" href="classeuni.html#f445a0ce24f39d14c1a4eed53fc8e2c3" title="cache of log( nk )">lnk</a> = log ( <a class="code" href="classeuni.html#63105490e946e43372d6187ad1bafdda" title="normalizing coefficients">nk</a> );
151<a name="l00218"></a>00218         }
152<a name="l00219"></a><a class="code" href="classeuni.html#8050087e421a9cfd1b4b1f8bd33b1cc1">00219</a>         vec <a class="code" href="classeuni.html#8050087e421a9cfd1b4b1f8bd33b1cc1" title="return expected value">mean</a>()<span class="keyword"> const </span>{vec pom=<a class="code" href="classeuni.html#71b6d6b41aeb61a7f76f682b72119231" title="upper bound on support">high</a>; pom-=<a class="code" href="classeuni.html#ef42cd8d7645422048d46c46ec5cdac1" title="lower bound on support">low</a>; pom/=2.0; <span class="keywordflow">return</span> pom;}
153<a name="l00220"></a>00220 };
154<a name="l00221"></a>00221
155<a name="l00222"></a>00222
156<a name="l00228"></a>00228 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt;
157<a name="l00229"></a><a class="code" href="classmlnorm.html">00229</a> <span class="keyword">class </span><a class="code" href="classmlnorm.html" title="Normal distributed linear function with linear function of mean value;.">mlnorm</a> : <span class="keyword">public</span> <a class="code" href="classmEF.html" title="Exponential family model.">mEF</a> {
158<a name="l00231"></a>00231         <a class="code" href="classenorm.html" title="Gaussian density with positive definite (decomposed) covariance matrix.">enorm&lt;sq_T&gt;</a> <a class="code" href="classepdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a>;
159<a name="l00232"></a>00232         mat A;
160<a name="l00233"></a>00233         vec&amp; _mu; <span class="comment">//cached epdf.mu;</span>
161<a name="l00234"></a>00234 <span class="keyword">public</span>:
162<a name="l00236"></a>00236         <a class="code" href="classmlnorm.html#f927203b3f31171c5c10ffc7caa797f5" title="Constructor.">mlnorm</a> ( <a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> &amp;<a class="code" href="classmpdf.html#f6687c07ff07d47812dd565368ca59eb" title="modeled random variable">rv</a>,<a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> &amp;<a class="code" href="classmpdf.html#acb7dda792b3cd5576f39fa3129abbab" title="random variable in condition">rvc</a> );
163<a name="l00238"></a>00238         <span class="keywordtype">void</span> <a class="code" href="classmlnorm.html#b6749030c5d5abcb3eb6898f74cea3c0" title="Set A and R.">set_parameters</a> ( <span class="keyword">const</span>  mat &amp;A, <span class="keyword">const</span> sq_T &amp;R );
164<a name="l00240"></a>00240         vec <a class="code" href="classmlnorm.html#decf3e3b5c8e0812e5b4dbe94fa2ae18" title="Generate one sample of the posterior.">samplecond</a> ( vec &amp;cond, <span class="keywordtype">double</span> &amp;lik );
165<a name="l00242"></a>00242         mat <a class="code" href="classmlnorm.html#decf3e3b5c8e0812e5b4dbe94fa2ae18" title="Generate one sample of the posterior.">samplecond</a> ( vec &amp;cond, vec &amp;lik, <span class="keywordtype">int</span> n );
166<a name="l00244"></a>00244         <span class="keywordtype">void</span> <a class="code" href="classmlnorm.html#5232fc7e305eceab4e2bd6a8daa44195" title="Set value of rvc . Result of this operation is stored in epdf use function _ep to...">condition</a> ( vec &amp;cond );
167<a name="l00245"></a>00245 };
168<a name="l00246"></a>00246
169<a name="l00256"></a><a class="code" href="classmgamma.html">00256</a> <span class="keyword">class </span><a class="code" href="classmgamma.html" title="Gamma random walk.">mgamma</a> : <span class="keyword">public</span> <a class="code" href="classmEF.html" title="Exponential family model.">mEF</a> {
170<a name="l00257"></a>00257 <span class="keyword">protected</span>:
171<a name="l00259"></a><a class="code" href="classmgamma.html#612dbf35c770a780027619aaac2c443e">00259</a>         <a class="code" href="classegamma.html" title="Gamma posterior density.">egamma</a> <a class="code" href="classepdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a>;
172<a name="l00261"></a><a class="code" href="classmgamma.html#43f733cce0245a52363d566099add687">00261</a>         <span class="keywordtype">double</span> <a class="code" href="classmgamma.html#43f733cce0245a52363d566099add687" title="Constant .">k</a>;
173<a name="l00263"></a><a class="code" href="classmgamma.html#5e90652837448bcc29707e7412f99691">00263</a>         vec* <a class="code" href="classmgamma.html#5e90652837448bcc29707e7412f99691" title="cache of epdf.beta">_beta</a>;
174<a name="l00264"></a>00264
175<a name="l00265"></a>00265 <span class="keyword">public</span>:
176<a name="l00267"></a>00267         <a class="code" href="classmgamma.html#af43e61b86900c0398d5c0ffc83b94e6" title="Constructor.">mgamma</a> ( <span class="keyword">const</span> <a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> &amp;<a class="code" href="classmpdf.html#f6687c07ff07d47812dd565368ca59eb" title="modeled random variable">rv</a>,<span class="keyword">const</span> <a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> &amp;<a class="code" href="classmpdf.html#acb7dda792b3cd5576f39fa3129abbab" title="random variable in condition">rvc</a> );
177<a name="l00269"></a>00269         <span class="keywordtype">void</span> <a class="code" href="classmgamma.html#a9d646cf758a70126dde7c48790b6e94" title="Set value of k.">set_parameters</a> ( <span class="keywordtype">double</span> <a class="code" href="classmgamma.html#43f733cce0245a52363d566099add687" title="Constant .">k</a> );
178<a name="l00271"></a>00271         vec <a class="code" href="classmgamma.html#9f40dc43885085fad8e3d6652b79e139" title="Generate one sample of the posterior.">samplecond</a> ( vec &amp;cond, <span class="keywordtype">double</span> &amp;lik );
179<a name="l00273"></a>00273         mat <a class="code" href="classmgamma.html#9f40dc43885085fad8e3d6652b79e139" title="Generate one sample of the posterior.">samplecond</a> ( vec &amp;cond, vec &amp;lik, <span class="keywordtype">int</span> n );
180<a name="l00274"></a><a class="code" href="classmgamma.html#a61094c9f7a2d64ea77b130cbc031f97">00274</a>         <span class="keywordtype">void</span> <a class="code" href="classmgamma.html#a61094c9f7a2d64ea77b130cbc031f97" title="Update ep so that it represents this mpdf conditioned on rvc = cond.">condition</a> ( <span class="keyword">const</span> vec &amp;val ) {*<a class="code" href="classmgamma.html#5e90652837448bcc29707e7412f99691" title="cache of epdf.beta">_beta</a>=<a class="code" href="classmgamma.html#43f733cce0245a52363d566099add687" title="Constant .">k</a>/val;};
181<a name="l00275"></a>00275 };
182<a name="l00276"></a>00276
183<a name="l00288"></a><a class="code" href="classmgamma__fix.html">00288</a> <span class="keyword">class </span><a class="code" href="classmgamma__fix.html" title="Gamma random walk around a fixed point.">mgamma_fix</a> : <span class="keyword">public</span> <a class="code" href="classmgamma.html" title="Gamma random walk.">mgamma</a> {
184<a name="l00289"></a>00289 <span class="keyword">protected</span>:
185<a name="l00291"></a><a class="code" href="classmgamma__fix.html#3f48c09caddc298901ad75fe7c0529f6">00291</a>         <span class="keywordtype">double</span> <a class="code" href="classmgamma__fix.html#3f48c09caddc298901ad75fe7c0529f6" title="parameter l">l</a>;
186<a name="l00293"></a><a class="code" href="classmgamma__fix.html#81ce49029ecc385418619b200dcafeb0">00293</a>         vec <a class="code" href="classmgamma__fix.html#81ce49029ecc385418619b200dcafeb0" title="reference vector">refl</a>;
187<a name="l00294"></a>00294 <span class="keyword">public</span>:
188<a name="l00296"></a><a class="code" href="classmgamma__fix.html#b92c3d2e5fd0381033a072e5ef3bcf80">00296</a>         <a class="code" href="classmgamma__fix.html#b92c3d2e5fd0381033a072e5ef3bcf80" title="Constructor.">mgamma_fix</a> ( <span class="keyword">const</span> <a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> &amp;<a class="code" href="classmpdf.html#f6687c07ff07d47812dd565368ca59eb" title="modeled random variable">rv</a>,<span class="keyword">const</span> <a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> &amp;<a class="code" href="classmpdf.html#acb7dda792b3cd5576f39fa3129abbab" title="random variable in condition">rvc</a> ) : <a class="code" href="classmgamma.html" title="Gamma random walk.">mgamma</a> ( rv,rvc ),<a class="code" href="classmgamma__fix.html#81ce49029ecc385418619b200dcafeb0" title="reference vector">refl</a> ( rv.count() ) {};
189<a name="l00298"></a><a class="code" href="classmgamma__fix.html#ec6f846896749e27cb7be9fa48dd1cb1">00298</a>         <span class="keywordtype">void</span> <a class="code" href="classmgamma__fix.html#ec6f846896749e27cb7be9fa48dd1cb1" title="Set value of k.">set_parameters</a> ( <span class="keywordtype">double</span> k0 , vec ref0, <span class="keywordtype">double</span> l0 ) {
190<a name="l00299"></a>00299                 <a class="code" href="classmgamma.html#a9d646cf758a70126dde7c48790b6e94" title="Set value of k.">mgamma::set_parameters</a> ( k0 );
191<a name="l00300"></a>00300                 <a class="code" href="classmgamma__fix.html#81ce49029ecc385418619b200dcafeb0" title="reference vector">refl</a>=pow ( ref0,1.0-l0 );<a class="code" href="classmgamma__fix.html#3f48c09caddc298901ad75fe7c0529f6" title="parameter l">l</a>=l0;
192<a name="l00301"></a>00301         };
193<a name="l00302"></a>00302
194<a name="l00303"></a><a class="code" href="classmgamma__fix.html#6ea3931eec7b7da7b693e45981052460">00303</a>         <span class="keywordtype">void</span> <a class="code" href="classmgamma__fix.html#6ea3931eec7b7da7b693e45981052460" title="Update ep so that it represents this mpdf conditioned on rvc = cond.">condition</a> ( <span class="keyword">const</span> vec &amp;val ) {vec mean=elem_mult ( <a class="code" href="classmgamma__fix.html#81ce49029ecc385418619b200dcafeb0" title="reference vector">refl</a>,pow ( val,<a class="code" href="classmgamma__fix.html#3f48c09caddc298901ad75fe7c0529f6" title="parameter l">l</a> ) ); *<a class="code" href="classmgamma.html#5e90652837448bcc29707e7412f99691" title="cache of epdf.beta">_beta</a>=<a class="code" href="classmgamma.html#43f733cce0245a52363d566099add687" title="Constant .">k</a>/mean;};
195<a name="l00304"></a>00304 };
196<a name="l00305"></a>00305
197<a name="l00307"></a><a class="code" href="libEF_8h.html#99497a3ff630f761cf6bff7babd23212">00307</a> <span class="keyword">enum</span> <a class="code" href="libEF_8h.html#99497a3ff630f761cf6bff7babd23212" title="Switch between various resampling methods.">RESAMPLING_METHOD</a> { MULTINOMIAL = 0, STRATIFIED = 1, SYSTEMATIC = 3 };
198<a name="l00313"></a><a class="code" href="classeEmp.html">00313</a> <span class="keyword">class </span><a class="code" href="classeEmp.html" title="Weighted empirical density.">eEmp</a>: <span class="keyword">public</span> <a class="code" href="classepdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a> {
199<a name="l00314"></a>00314 <span class="keyword">protected</span> :
200<a name="l00316"></a><a class="code" href="classeEmp.html#8c33034de0e35f03f8bb85d3d67438fd">00316</a>         <span class="keywordtype">int</span> <a class="code" href="classeEmp.html#8c33034de0e35f03f8bb85d3d67438fd" title="Number of particles.">n</a>;
201<a name="l00318"></a><a class="code" href="classeEmp.html#ae78d144404ddba843c93b171b215de8">00318</a>         vec <a class="code" href="classeEmp.html#ae78d144404ddba843c93b171b215de8" title="Sample weights .">w</a>;
202<a name="l00320"></a><a class="code" href="classeEmp.html#a4d6f4bbd6a6824fc39f14676701279a">00320</a>         Array&lt;vec&gt; <a class="code" href="classeEmp.html#a4d6f4bbd6a6824fc39f14676701279a" title="Samples .">samples</a>;
203<a name="l00321"></a>00321 <span class="keyword">public</span>:
204<a name="l00323"></a><a class="code" href="classeEmp.html#0c04b073ecd0dae3d498e680ae27e9e4">00323</a>         <a class="code" href="classeEmp.html#0c04b073ecd0dae3d498e680ae27e9e4" title="Default constructor.">eEmp</a> ( <span class="keyword">const</span> <a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> &amp;rv0 ,<span class="keywordtype">int</span> n0 ) :<a class="code" href="classepdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a> ( rv0 ),<a class="code" href="classeEmp.html#8c33034de0e35f03f8bb85d3d67438fd" title="Number of particles.">n</a> ( n0 ),<a class="code" href="classeEmp.html#ae78d144404ddba843c93b171b215de8" title="Sample weights .">w</a> ( <a class="code" href="classeEmp.html#8c33034de0e35f03f8bb85d3d67438fd" title="Number of particles.">n</a> ),<a class="code" href="classeEmp.html#a4d6f4bbd6a6824fc39f14676701279a" title="Samples .">samples</a> ( <a class="code" href="classeEmp.html#8c33034de0e35f03f8bb85d3d67438fd" title="Number of particles.">n</a> ) {};
205<a name="l00325"></a>00325         <span class="keywordtype">void</span> <a class="code" href="classeEmp.html#6606a656c1b28114f7384c25aaf80e8d" title="Set sample.">set_parameters</a> ( <span class="keyword">const</span> vec &amp;w0, <a class="code" href="classepdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a>* pdf0 );
206<a name="l00327"></a><a class="code" href="classeEmp.html#31b2bfb73b72486a5c89f2ab850c7a9b">00327</a>         vec&amp; <a class="code" href="classeEmp.html#31b2bfb73b72486a5c89f2ab850c7a9b" title="Potentially dangerous, use with care.">_w</a>()  {<span class="keywordflow">return</span> <a class="code" href="classeEmp.html#ae78d144404ddba843c93b171b215de8" title="Sample weights .">w</a>;};
207<a name="l00329"></a><a class="code" href="classeEmp.html#31b747eca73b16f30370827ba4cc3575">00329</a>         Array&lt;vec&gt;&amp; <a class="code" href="classeEmp.html#31b747eca73b16f30370827ba4cc3575" title="access function">_samples</a>() {<span class="keywordflow">return</span> <a class="code" href="classeEmp.html#a4d6f4bbd6a6824fc39f14676701279a" title="Samples .">samples</a>;};
208<a name="l00331"></a>00331         ivec <a class="code" href="classeEmp.html#77268292fc4465cb73ddbfb1f2932a59" title="Function performs resampling, i.e. removal of low-weight samples and duplication...">resample</a> ( <a class="code" href="libEF_8h.html#99497a3ff630f761cf6bff7babd23212" title="Switch between various resampling methods.">RESAMPLING_METHOD</a> method = SYSTEMATIC );
209<a name="l00333"></a><a class="code" href="classeEmp.html#83f9283f92b805508d896479dc1ccf12">00333</a>         vec <a class="code" href="classeEmp.html#83f9283f92b805508d896479dc1ccf12" 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;}
210<a name="l00335"></a><a class="code" href="classeEmp.html#23e7358995400865ad2e278945922fb3">00335</a>         <span class="keywordtype">double</span> <a class="code" href="classeEmp.html#23e7358995400865ad2e278945922fb3" title="inherited operation : NOT implemneted">evalpdflog</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;}
211<a name="l00336"></a><a class="code" href="classeEmp.html#ba055c19038cc72628d98e25197e982d">00336</a>         vec <a class="code" href="classeEmp.html#ba055c19038cc72628d98e25197e982d" title="return expected value">mean</a>()<span class="keyword"> const </span>{
212<a name="l00337"></a>00337                 vec pom=zeros ( <a class="code" href="classepdf.html#74da992e3f5d598da8850b646b79b9d9" title="Identified of the random variable.">rv</a>.<a class="code" href="classRV.html#f5c7b8bd589eef09ccdf3329a0addea0" title="Return number of scalars in the RV.">count</a>() );
213<a name="l00338"></a>00338                 <span class="keywordflow">for</span> ( <span class="keywordtype">int</span> i=0;i&lt;<a class="code" href="classeEmp.html#8c33034de0e35f03f8bb85d3d67438fd" title="Number of particles.">n</a>;i++ ) {pom+=<a class="code" href="classeEmp.html#a4d6f4bbd6a6824fc39f14676701279a" title="Samples .">samples</a> ( i ) *<a class="code" href="classeEmp.html#ae78d144404ddba843c93b171b215de8" title="Sample weights .">w</a> ( i );}
214<a name="l00339"></a>00339                 <span class="keywordflow">return</span> pom;
215<a name="l00340"></a>00340         }
216<a name="l00341"></a>00341 };
217<a name="l00342"></a>00342
218<a name="l00343"></a>00343
219<a name="l00345"></a>00345
220<a name="l00346"></a>00346 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt;
221<a name="l00347"></a><a class="code" href="classenorm.html#7b5cb487a2570e8109bfdc0df149aa06">00347</a> <a class="code" href="classenorm.html#7b5cb487a2570e8109bfdc0df149aa06" title="Default constructor.">enorm&lt;sq_T&gt;::enorm</a> ( <a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> &amp;rv ) :<a class="code" href="classeEF.html" title="General conjugate exponential family posterior density.">eEF</a> ( rv ), mu ( rv.count() ),R ( rv.count() ),dim ( rv.count() ) {};
222<a name="l00348"></a>00348
223<a name="l00349"></a>00349 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt;
224<a name="l00350"></a><a class="code" href="classenorm.html#1394a65caa6e00d42e00cc99b12227af">00350</a> <span class="keywordtype">void</span> <a class="code" href="classenorm.html#1394a65caa6e00d42e00cc99b12227af" title="Set mean value mu and covariance R.">enorm&lt;sq_T&gt;::set_parameters</a> ( <span class="keyword">const</span> vec &amp;mu0, <span class="keyword">const</span> sq_T &amp;R0 ) {
225<a name="l00351"></a>00351 <span class="comment">//Fixme test dimensions of mu0 and R0;</span>
226<a name="l00352"></a>00352         <a class="code" href="classenorm.html#71fde0d54bba147e00f612577f95ad20" title="mean value">mu</a> = mu0;
227<a name="l00353"></a>00353         <a class="code" href="classenorm.html#4ccc8d8514d644ef1c98d8ab023748a1" title="Covariance matrix in decomposed form.">R</a> = R0;
228<a name="l00354"></a>00354 };
229<a name="l00355"></a>00355
230<a name="l00356"></a>00356 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt;
231<a name="l00357"></a><a class="code" href="classenorm.html#5bf185e31e5954fceb90ada3debd2ff2">00357</a> <span class="keywordtype">void</span> <a class="code" href="classenorm.html#5bf185e31e5954fceb90ada3debd2ff2" title="dupdate in exponential form (not really handy)">enorm&lt;sq_T&gt;::dupdate</a> ( mat &amp;v, <span class="keywordtype">double</span> nu ) {
232<a name="l00358"></a>00358         <span class="comment">//</span>
233<a name="l00359"></a>00359 };
234<a name="l00360"></a>00360
235<a name="l00361"></a>00361 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt;
236<a name="l00362"></a><a class="code" href="classenorm.html#5b5fd142b6b17ea334597960e3fe126a">00362</a> <span class="keywordtype">void</span> <a class="code" href="classenorm.html#5b5fd142b6b17ea334597960e3fe126a" title="tupdate in exponential form (not really handy)">enorm&lt;sq_T&gt;::tupdate</a> ( <span class="keywordtype">double</span> phi, mat &amp;vbar, <span class="keywordtype">double</span> nubar ) {
237<a name="l00363"></a>00363         <span class="comment">//</span>
238<a name="l00364"></a>00364 };
239<a name="l00365"></a>00365
240<a name="l00366"></a>00366 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt;
241<a name="l00367"></a><a class="code" href="classenorm.html#60b47544f6181ffd4530d3e415ce12c5">00367</a> vec <a class="code" href="classenorm.html#60b47544f6181ffd4530d3e415ce12c5" title="Returns the required moment of the epdf.">enorm&lt;sq_T&gt;::sample</a>()<span class="keyword"> const </span>{
242<a name="l00368"></a>00368         vec x ( <a class="code" href="classenorm.html#6938fc390a19cdaf6ad4503fcbaada4e" title="dimension (redundant from rv.count() for easier coding )">dim</a> );
243<a name="l00369"></a>00369         NorRNG.sample_vector ( <a class="code" href="classenorm.html#6938fc390a19cdaf6ad4503fcbaada4e" title="dimension (redundant from rv.count() for easier coding )">dim</a>,x );
244<a name="l00370"></a>00370         vec smp = <a class="code" href="classenorm.html#4ccc8d8514d644ef1c98d8ab023748a1" title="Covariance matrix in decomposed form.">R</a>.sqrt_mult ( x );
245<a name="l00371"></a>00371
246<a name="l00372"></a>00372         smp += <a class="code" href="classenorm.html#71fde0d54bba147e00f612577f95ad20" title="mean value">mu</a>;
247<a name="l00373"></a>00373         <span class="keywordflow">return</span> smp;
248<a name="l00374"></a>00374 };
249<a name="l00375"></a>00375
250<a name="l00376"></a>00376 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt;
251<a name="l00377"></a><a class="code" href="classenorm.html#60f0f3bfa53d6e65843eea9532b16d36">00377</a> mat <a class="code" href="classenorm.html#60b47544f6181ffd4530d3e415ce12c5" title="Returns the required moment of the epdf.">enorm&lt;sq_T&gt;::sample</a> ( <span class="keywordtype">int</span> N )<span class="keyword"> const </span>{
252<a name="l00378"></a>00378         mat X ( <a class="code" href="classenorm.html#6938fc390a19cdaf6ad4503fcbaada4e" title="dimension (redundant from rv.count() for easier coding )">dim</a>,N );
253<a name="l00379"></a>00379         vec x ( <a class="code" href="classenorm.html#6938fc390a19cdaf6ad4503fcbaada4e" title="dimension (redundant from rv.count() for easier coding )">dim</a> );
254<a name="l00380"></a>00380         vec pom;
255<a name="l00381"></a>00381         <span class="keywordtype">int</span> i;
256<a name="l00382"></a>00382
257<a name="l00383"></a>00383         <span class="keywordflow">for</span> ( i=0;i&lt;N;i++ ) {
258<a name="l00384"></a>00384                 NorRNG.sample_vector ( <a class="code" href="classenorm.html#6938fc390a19cdaf6ad4503fcbaada4e" title="dimension (redundant from rv.count() for easier coding )">dim</a>,x );
259<a name="l00385"></a>00385                 pom = <a class="code" href="classenorm.html#4ccc8d8514d644ef1c98d8ab023748a1" title="Covariance matrix in decomposed form.">R</a>.sqrt_mult ( x );
260<a name="l00386"></a>00386                 pom +=<a class="code" href="classenorm.html#71fde0d54bba147e00f612577f95ad20" title="mean value">mu</a>;
261<a name="l00387"></a>00387                 X.set_col ( i, pom );
262<a name="l00388"></a>00388         }
263<a name="l00389"></a>00389
264<a name="l00390"></a>00390         <span class="keywordflow">return</span> X;
265<a name="l00391"></a>00391 };
266<a name="l00392"></a>00392
267<a name="l00393"></a>00393 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt;
268<a name="l00394"></a><a class="code" href="classenorm.html#b9e1dfd33692d7b3f1a59f17b0e61bd0">00394</a> <span class="keywordtype">double</span> <a class="code" href="classenorm.html#b9e1dfd33692d7b3f1a59f17b0e61bd0" title="Compute probability of argument val.">enorm&lt;sq_T&gt;::eval</a> ( <span class="keyword">const</span> vec &amp;val )<span class="keyword"> const </span>{
269<a name="l00395"></a>00395         <span class="keywordtype">double</span> pdfl,e;
270<a name="l00396"></a>00396         pdfl = <a class="code" href="classenorm.html#609a7c33dbb4fdfab050f3bdd1122401" title="Compute log-probability of argument val.">evalpdflog</a> ( val );
271<a name="l00397"></a>00397         e = exp ( pdfl );
272<a name="l00398"></a>00398         <span class="keywordflow">return</span> e;
273<a name="l00399"></a>00399 };
274<a name="l00400"></a>00400
275<a name="l00401"></a>00401 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt;
276<a name="l00402"></a><a class="code" href="classenorm.html#609a7c33dbb4fdfab050f3bdd1122401">00402</a> <span class="keywordtype">double</span> <a class="code" href="classenorm.html#609a7c33dbb4fdfab050f3bdd1122401" title="Compute log-probability of argument val.">enorm&lt;sq_T&gt;::evalpdflog</a> ( <span class="keyword">const</span> vec &amp;val )<span class="keyword"> const </span>{
277<a name="l00403"></a>00403         <span class="comment">// 1.83787706640935 = log(2pi)</span>
278<a name="l00404"></a>00404         <span class="keywordflow">return</span>  -0.5* (  +<a class="code" href="classenorm.html#4ccc8d8514d644ef1c98d8ab023748a1" title="Covariance matrix in decomposed form.">R</a>.invqform ( <a class="code" href="classenorm.html#71fde0d54bba147e00f612577f95ad20" title="mean value">mu</a>-val ) ) - <a class="code" href="classenorm.html#b289a36a69db59d182bb6eba9c05d4a8" title="logarithm of the normalizing constant, ">lognc</a>();
279<a name="l00405"></a>00405 };
280<a name="l00406"></a>00406
281<a name="l00407"></a>00407 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt;
282<a name="l00408"></a><a class="code" href="classenorm.html#b289a36a69db59d182bb6eba9c05d4a8">00408</a> <span class="keyword">inline</span> <span class="keywordtype">double</span> <a class="code" href="classenorm.html#b289a36a69db59d182bb6eba9c05d4a8" title="logarithm of the normalizing constant, ">enorm&lt;sq_T&gt;::lognc</a> ()<span class="keyword"> const </span>{
283<a name="l00409"></a>00409         <span class="comment">// 1.83787706640935 = log(2pi)</span>
284<a name="l00410"></a>00410         <span class="keywordflow">return</span> -0.5* ( <a class="code" href="classenorm.html#4ccc8d8514d644ef1c98d8ab023748a1" title="Covariance matrix in decomposed form.">R</a>.cols() * 1.83787706640935 +<a class="code" href="classenorm.html#4ccc8d8514d644ef1c98d8ab023748a1" title="Covariance matrix in decomposed form.">R</a>.logdet());
285<a name="l00411"></a>00411 };
286<a name="l00412"></a>00412
287<a name="l00413"></a>00413 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt;
288<a name="l00414"></a><a class="code" href="classmlnorm.html#f927203b3f31171c5c10ffc7caa797f5">00414</a> <a class="code" href="classmlnorm.html#f927203b3f31171c5c10ffc7caa797f5" title="Constructor.">mlnorm&lt;sq_T&gt;::mlnorm</a> ( <a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> &amp;rv0,<a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> &amp;rvc0 ) :<a class="code" href="classmEF.html" title="Exponential family model.">mEF</a> ( rv0,rvc0 ),<a class="code" href="classepdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a> ( <a class="code" href="classepdf.html#74da992e3f5d598da8850b646b79b9d9" title="Identified of the random variable.">rv</a> ),A ( rv0.count(),rv0.count() ),<a class="code" href="classenorm.html#0b8cb284e5af920a1b64a21d057ec5ac" title="returns a pointer to the internal mean value. Use with Care!">_mu</a>(<a class="code" href="classepdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a>.<a class="code" href="classenorm.html#0b8cb284e5af920a1b64a21d057ec5ac" title="returns a pointer to the internal mean value. Use with Care!">_mu</a>()) {
289<a name="l00415"></a>00415 }
290<a name="l00416"></a>00416
291<a name="l00417"></a>00417 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt;
292<a name="l00418"></a><a class="code" href="classmlnorm.html#b6749030c5d5abcb3eb6898f74cea3c0">00418</a> <span class="keywordtype">void</span> <a class="code" href="classmlnorm.html#b6749030c5d5abcb3eb6898f74cea3c0" title="Set A and R.">mlnorm&lt;sq_T&gt;::set_parameters</a> ( <span class="keyword">const</span> mat &amp;A0, <span class="keyword">const</span> sq_T &amp;R0 ) {
293<a name="l00419"></a>00419         <a class="code" href="classepdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a>.set_parameters ( zeros ( <a class="code" href="classmpdf.html#f6687c07ff07d47812dd565368ca59eb" title="modeled random variable">rv</a>.<a class="code" href="classRV.html#f5c7b8bd589eef09ccdf3329a0addea0" title="Return number of scalars in the RV.">count</a>() ),R0 );
294<a name="l00420"></a>00420         A = A0;
295<a name="l00421"></a>00421 }
296<a name="l00422"></a>00422
297<a name="l00423"></a>00423 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt;
298<a name="l00424"></a><a class="code" href="classmlnorm.html#decf3e3b5c8e0812e5b4dbe94fa2ae18">00424</a> vec <a class="code" href="classmlnorm.html#decf3e3b5c8e0812e5b4dbe94fa2ae18" title="Generate one sample of the posterior.">mlnorm&lt;sq_T&gt;::samplecond</a> ( vec &amp;cond, <span class="keywordtype">double</span> &amp;lik ) {
299<a name="l00425"></a>00425         this-&gt;<a class="code" href="classmlnorm.html#5232fc7e305eceab4e2bd6a8daa44195" title="Set value of rvc . Result of this operation is stored in epdf use function _ep to...">condition</a> ( cond );
300<a name="l00426"></a>00426         vec smp = <a class="code" href="classepdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a>.sample();
301<a name="l00427"></a>00427         lik = <a class="code" href="classepdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a>.eval ( smp );
302<a name="l00428"></a>00428         <span class="keywordflow">return</span> smp;
303<a name="l00429"></a>00429 }
304<a name="l00430"></a>00430
305<a name="l00431"></a>00431 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt;
306<a name="l00432"></a><a class="code" href="classmlnorm.html#215fb88cc8b95d64cdefd6849abdd1e8">00432</a> mat <a class="code" href="classmlnorm.html#decf3e3b5c8e0812e5b4dbe94fa2ae18" title="Generate one sample of the posterior.">mlnorm&lt;sq_T&gt;::samplecond</a> ( vec &amp;cond, vec &amp;lik, <span class="keywordtype">int</span> n ) {
307<a name="l00433"></a>00433         <span class="keywordtype">int</span> i;
308<a name="l00434"></a>00434         <span class="keywordtype">int</span> dim = <a class="code" href="classmpdf.html#f6687c07ff07d47812dd565368ca59eb" title="modeled random variable">rv</a>.<a class="code" href="classRV.html#f5c7b8bd589eef09ccdf3329a0addea0" title="Return number of scalars in the RV.">count</a>();
309<a name="l00435"></a>00435         mat Smp ( dim,n );
310<a name="l00436"></a>00436         vec smp ( dim );
311<a name="l00437"></a>00437         this-&gt;<a class="code" href="classmlnorm.html#5232fc7e305eceab4e2bd6a8daa44195" title="Set value of rvc . Result of this operation is stored in epdf use function _ep to...">condition</a> ( cond );
312<a name="l00438"></a>00438
313<a name="l00439"></a>00439         <span class="keywordflow">for</span> ( i=0; i&lt;n; i++ ) {
314<a name="l00440"></a>00440                 smp = <a class="code" href="classepdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a>.sample();
315<a name="l00441"></a>00441                 lik ( i ) = <a class="code" href="classepdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a>.eval ( smp );
316<a name="l00442"></a>00442                 Smp.set_col ( i ,smp );
317<a name="l00443"></a>00443         }
318<a name="l00444"></a>00444
319<a name="l00445"></a>00445         <span class="keywordflow">return</span> Smp;
320<a name="l00446"></a>00446 }
321<a name="l00447"></a>00447
322<a name="l00448"></a>00448 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt;
323<a name="l00449"></a><a class="code" href="classmlnorm.html#5232fc7e305eceab4e2bd6a8daa44195">00449</a> <span class="keywordtype">void</span> <a class="code" href="classmlnorm.html#5232fc7e305eceab4e2bd6a8daa44195" title="Set value of rvc . Result of this operation is stored in epdf use function _ep to...">mlnorm&lt;sq_T&gt;::condition</a> ( vec &amp;cond ) {
324<a name="l00450"></a>00450         _mu = A*cond;
325<a name="l00451"></a>00451 <span class="comment">//R is already assigned;</span>
326<a name="l00452"></a>00452 }
327<a name="l00453"></a>00453
328<a name="l00455"></a>00455
329<a name="l00456"></a>00456
330<a name="l00457"></a>00457 <span class="preprocessor">#endif //EF_H</span>
331</pre></div></div>
332<hr size="1"><address style="text-align: right;"><small>Generated on Fri May 9 23:06:28 2008 for mixpp by&nbsp;
333<a href="http://www.doxygen.org/index.html">
334<img src="doxygen.png" alt="doxygen" align="middle" border="0"></a> 1.5.5 </small></address>
335</body>
336</html>
Note: See TracBrowser for help on using the browser.