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    r91 r99  
    3333<a name="l00031"></a>00031  
    3434<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  
    36 <a name="l00040"></a>00040 <span class="keyword">public</span>: 
    37 <a name="l00041"></a>00041 <span class="comment">//      eEF() :epdf() {};</span> 
    38 <a name="l00043"></a><a class="code" href="classeEF.html#7e3c63655e8375c76bf1f421245427a7">00043</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 ) {}; 
    39 <a name="l00045"></a><a class="code" href="classeEF.html#fd88bc35550ec8fe9281d358216d0fcf">00045</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="l00047"></a><a class="code" href="classeEF.html#5863718c3b2fb1496dece10c5b745d5c">00047</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="l00048"></a>00048 }; 
    42 <a name="l00049"></a>00049  
    43 <a name="l00056"></a><a class="code" href="classmEF.html">00056</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="l00057"></a>00057  
    45 <a name="l00058"></a>00058 <span class="keyword">public</span>: 
    46 <a name="l00060"></a><a class="code" href="classmEF.html#8bf51fe8654d7b83c8c8afeb19409d4f">00060</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="l00061"></a>00061 }; 
    48 <a name="l00062"></a>00062  
    49 <a name="l00068"></a>00068 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt; 
    50 <a name="l00069"></a>00069  
    51 <a name="l00070"></a><a class="code" href="classenorm.html">00070</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="l00071"></a>00071 <span class="keyword">protected</span>: 
    53 <a name="l00073"></a><a class="code" href="classenorm.html#71fde0d54bba147e00f612577f95ad20">00073</a>         vec <a class="code" href="classenorm.html#71fde0d54bba147e00f612577f95ad20" title="mean value">mu</a>; 
    54 <a name="l00075"></a><a class="code" href="classenorm.html#4ccc8d8514d644ef1c98d8ab023748a1">00075</a>         sq_T <a class="code" href="classenorm.html#4ccc8d8514d644ef1c98d8ab023748a1" title="Covariance matrix in decomposed form.">R</a>; 
    55 <a name="l00077"></a><a class="code" href="classenorm.html#6938fc390a19cdaf6ad4503fcbaada4e">00077</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="l00078"></a>00078 <span class="keyword">public</span>: 
    57 <a name="l00079"></a>00079 <span class="comment">//      enorm() :eEF() {};</span> 
    58 <a name="l00081"></a>00081 <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="l00083"></a>00083         <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="l00085"></a>00085         <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="l00087"></a>00087         <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="l00088"></a>00088  
    63 <a name="l00089"></a>00089         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="l00091"></a>00091         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="l00092"></a>00092         <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="l00093"></a>00093         <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="l00094"></a><a class="code" href="classenorm.html#50fa84da7bae02f7af17a98f37566899">00094</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>;} 
    68 <a name="l00095"></a>00095  
    69 <a name="l00096"></a>00096 <span class="comment">//Access methods</span> 
    70 <a name="l00098"></a><a class="code" href="classenorm.html#0b8cb284e5af920a1b64a21d057ec5ac">00098</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>;} 
    71 <a name="l00099"></a>00099          
    72 <a name="l00101"></a><a class="code" href="classenorm.html#d892a38f03be12e572ea57d9689cef6b">00101</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;} 
    73 <a name="l00102"></a>00102  
    74 <a name="l00104"></a><a class="code" href="classenorm.html#7a5034b25771a84450a990d10fc40ac9">00104</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>;} 
    75 <a name="l00105"></a>00105  
    76 <a name="l00107"></a><a class="code" href="classenorm.html#9b9f58dc86affa23511c246887420658">00107</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();} 
    77 <a name="l00108"></a>00108 }; 
    78 <a name="l00109"></a>00109  
    79 <a name="l00119"></a><a class="code" href="classegamma.html">00119</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> { 
    80 <a name="l00120"></a>00120 <span class="keyword">protected</span>: 
    81 <a name="l00122"></a><a class="code" href="classegamma.html#376cebd8932546c440f21b182910b01b">00122</a>         vec <a class="code" href="classegamma.html#376cebd8932546c440f21b182910b01b" title="Vector .">alpha</a>; 
    82 <a name="l00124"></a><a class="code" href="classegamma.html#cfc5f136467488a421ab22f886323790">00124</a>         vec <a class="code" href="classegamma.html#cfc5f136467488a421ab22f886323790" title="Vector .">beta</a>; 
    83 <a name="l00125"></a>00125 <span class="keyword">public</span> : 
    84 <a name="l00127"></a><a class="code" href="classegamma.html#4b1d34f3b244ea51a58ec10c468788c1">00127</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 ) {}; 
    85 <a name="l00129"></a><a class="code" href="classegamma.html#8e348b89be82b70471fe8c5630f61339">00129</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;}; 
    86 <a name="l00130"></a>00130         vec <a class="code" href="classegamma.html#8e10c0021b5dfdd9cb62c6959b5ef425" title="Returns the required moment of the epdf.">sample</a>() <span class="keyword">const</span>; 
    87 <a name="l00132"></a>00132         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>; 
    88 <a name="l00133"></a>00133         <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>; 
    89 <a name="l00135"></a><a class="code" href="classegamma.html#44445c56e60b91b377f207f8d5089790">00135</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>;}; 
    90 <a name="l00136"></a><a class="code" href="classegamma.html#6ab5ba56f7cdb2e5921c3e77524fa50a">00136</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;} 
    91 <a name="l00137"></a>00137 }; 
    92 <a name="l00138"></a>00138 <span class="comment">/*</span> 
    93 <a name="l00140"></a>00140 <span class="comment">class emix : public epdf {</span> 
    94 <a name="l00141"></a>00141 <span class="comment">protected:</span> 
    95 <a name="l00142"></a>00142 <span class="comment">        int n;</span> 
    96 <a name="l00143"></a>00143 <span class="comment">        vec &amp;w;</span> 
    97 <a name="l00144"></a>00144 <span class="comment">        Array&lt;epdf*&gt; Coms;</span> 
    98 <a name="l00145"></a>00145 <span class="comment">public:</span> 
    99 <a name="l00147"></a>00147 <span class="comment">        emix ( const RV &amp;rv, vec &amp;w0): epdf(rv), n(w0.length()), w(w0), Coms(n) {};</span> 
    100 <a name="l00148"></a>00148 <span class="comment">        void set_parameters( int &amp;i, double wi, epdf* ep){w(i)=wi;Coms(i)=ep;}</span> 
    101 <a name="l00149"></a>00149 <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> 
    102 <a name="l00150"></a>00150 <span class="comment">        vec sample() {it_error ( "Not implemented" );return 0;}</span> 
    103 <a name="l00151"></a>00151 <span class="comment">};</span> 
    104 <a name="l00152"></a>00152 <span class="comment">*/</span> 
    105 <a name="l00153"></a>00153  
    106 <a name="l00155"></a>00155  
    107 <a name="l00156"></a><a class="code" href="classeuni.html">00156</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> { 
    108 <a name="l00157"></a>00157 <span class="keyword">protected</span>: 
    109 <a name="l00159"></a><a class="code" href="classeuni.html#ef42cd8d7645422048d46c46ec5cdac1">00159</a>         vec <a class="code" href="classeuni.html#ef42cd8d7645422048d46c46ec5cdac1" title="lower bound on support">low</a>; 
    110 <a name="l00161"></a><a class="code" href="classeuni.html#71b6d6b41aeb61a7f76f682b72119231">00161</a>         vec <a class="code" href="classeuni.html#71b6d6b41aeb61a7f76f682b72119231" title="upper bound on support">high</a>; 
    111 <a name="l00163"></a><a class="code" href="classeuni.html#52a6ff4a54010f88a6a19fca605c64a4">00163</a>         vec <a class="code" href="classeuni.html#52a6ff4a54010f88a6a19fca605c64a4" title="internal">distance</a>; 
    112 <a name="l00165"></a><a class="code" href="classeuni.html#63105490e946e43372d6187ad1bafdda">00165</a>         <span class="keywordtype">double</span> <a class="code" href="classeuni.html#63105490e946e43372d6187ad1bafdda" title="normalizing coefficients">nk</a>; 
    113 <a name="l00167"></a><a class="code" href="classeuni.html#f445a0ce24f39d14c1a4eed53fc8e2c3">00167</a>         <span class="keywordtype">double</span> <a class="code" href="classeuni.html#f445a0ce24f39d14c1a4eed53fc8e2c3" title="cache of log( nk )">lnk</a>; 
    114 <a name="l00168"></a>00168 <span class="keyword">public</span>: 
    115 <a name="l00170"></a><a class="code" href="classeuni.html#2537a6c239cff52e3ba814851a1116cd">00170</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 ) {} 
    116 <a name="l00171"></a><a class="code" href="classeuni.html#2723d4992900b5c5495bfa03628195ed">00171</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>;} 
    117 <a name="l00172"></a><a class="code" href="classeuni.html#06af95d514a6623ad4688bd2ad50ad71">00172</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>;} 
    118 <a name="l00173"></a><a class="code" href="classeuni.html#4a0e09392be17beaee120ba98fc038cd">00173</a>         vec <a class="code" href="classeuni.html#4a0e09392be17beaee120ba98fc038cd" title="Returns the required moment of the epdf.">sample</a>()<span class="keyword"> const </span>{ 
    119 <a name="l00174"></a>00174                 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 ); 
    120 <a name="l00175"></a>00175                 <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; 
    121 <a name="l00176"></a>00176         } 
    122 <a name="l00178"></a><a class="code" href="classeuni.html#4fd7c6a05100616ad16ece405cad7bf2">00178</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 ) { 
    123 <a name="l00179"></a>00179                 <a class="code" href="classeuni.html#52a6ff4a54010f88a6a19fca605c64a4" title="internal">distance</a> = high0-low0; 
    124 <a name="l00180"></a>00180                 it_assert_debug ( min ( <a class="code" href="classeuni.html#52a6ff4a54010f88a6a19fca605c64a4" title="internal">distance</a> ) &gt;0.0,<span class="stringliteral">"bad support"</span> ); 
    125 <a name="l00181"></a>00181                 <a class="code" href="classeuni.html#ef42cd8d7645422048d46c46ec5cdac1" title="lower bound on support">low</a> = low0; 
    126 <a name="l00182"></a>00182                 <a class="code" href="classeuni.html#71b6d6b41aeb61a7f76f682b72119231" title="upper bound on support">high</a> = high0; 
    127 <a name="l00183"></a>00183                 <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> ); 
    128 <a name="l00184"></a>00184                 <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> ); 
    129 <a name="l00185"></a>00185         } 
    130 <a name="l00186"></a><a class="code" href="classeuni.html#8050087e421a9cfd1b4b1f8bd33b1cc1">00186</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;} 
    131 <a name="l00187"></a>00187 }; 
     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  
    132128<a name="l00188"></a>00188  
    133 <a name="l00189"></a>00189  
    134 <a name="l00195"></a>00195 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt; 
    135 <a name="l00196"></a><a class="code" href="classmlnorm.html">00196</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> { 
    136 <a name="l00198"></a>00198         <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>; 
    137 <a name="l00199"></a>00199         mat A; 
    138 <a name="l00200"></a>00200         vec&amp; _mu; <span class="comment">//cached epdf.mu;</span> 
     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>; 
    139136<a name="l00201"></a>00201 <span class="keyword">public</span>: 
    140 <a name="l00203"></a>00203         <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> ); 
    141 <a name="l00205"></a>00205         <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 ); 
    142 <a name="l00207"></a>00207         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 ); 
    143 <a name="l00209"></a>00209         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 ); 
    144 <a name="l00211"></a>00211         <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 ); 
    145 <a name="l00212"></a>00212 }; 
    146 <a name="l00213"></a>00213  
    147 <a name="l00223"></a><a class="code" href="classmgamma.html">00223</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> { 
    148 <a name="l00224"></a>00224 <span class="keyword">protected</span>: 
    149 <a name="l00226"></a><a class="code" href="classmgamma.html#612dbf35c770a780027619aaac2c443e">00226</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>; 
    150 <a name="l00228"></a><a class="code" href="classmgamma.html#43f733cce0245a52363d566099add687">00228</a>         <span class="keywordtype">double</span> <a class="code" href="classmgamma.html#43f733cce0245a52363d566099add687" title="Constant .">k</a>; 
    151 <a name="l00230"></a><a class="code" href="classmgamma.html#5e90652837448bcc29707e7412f99691">00230</a>         vec* <a class="code" href="classmgamma.html#5e90652837448bcc29707e7412f99691" title="cache of epdf.beta">_beta</a>; 
    152 <a name="l00231"></a>00231  
    153 <a name="l00232"></a>00232 <span class="keyword">public</span>: 
    154 <a name="l00234"></a>00234         <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> ); 
    155 <a name="l00236"></a>00236         <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> ); 
    156 <a name="l00238"></a>00238         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 ); 
    157 <a name="l00240"></a>00240         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 ); 
    158 <a name="l00241"></a><a class="code" href="classmgamma.html#a61094c9f7a2d64ea77b130cbc031f97">00241</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;}; 
    159 <a name="l00242"></a>00242 }; 
    160 <a name="l00243"></a>00243  
    161 <a name="l00255"></a><a class="code" href="classmgamma__fix.html">00255</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> { 
    162 <a name="l00256"></a>00256 <span class="keyword">protected</span>: 
    163 <a name="l00257"></a>00257         <span class="keywordtype">double</span> l; 
    164 <a name="l00258"></a>00258         vec refl; 
    165 <a name="l00259"></a>00259 <span class="keyword">public</span>: 
    166 <a name="l00261"></a><a class="code" href="classmgamma__fix.html#b92c3d2e5fd0381033a072e5ef3bcf80">00261</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 ),refl ( rv.count() ) {}; 
    167 <a name="l00263"></a><a class="code" href="classmgamma__fix.html#ec6f846896749e27cb7be9fa48dd1cb1">00263</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 ) { 
    168 <a name="l00264"></a>00264                 <a class="code" href="classmgamma.html#a9d646cf758a70126dde7c48790b6e94" title="Set value of k.">mgamma::set_parameters</a> ( k0 ); 
    169 <a name="l00265"></a>00265                 refl=pow ( ref0,1.0-l0 );l=l0; 
    170 <a name="l00266"></a>00266         }; 
    171 <a name="l00267"></a>00267  
    172 <a name="l00268"></a><a class="code" href="classmgamma__fix.html#6ea3931eec7b7da7b693e45981052460">00268</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 ( refl,pow ( val,l ) ); *<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;}; 
    173 <a name="l00269"></a>00269 }; 
    174 <a name="l00270"></a>00270  
    175 <a name="l00272"></a><a class="code" href="libEF_8h.html#99497a3ff630f761cf6bff7babd23212">00272</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 }; 
    176 <a name="l00278"></a><a class="code" href="classeEmp.html">00278</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> { 
    177 <a name="l00279"></a>00279 <span class="keyword">protected</span> : 
    178 <a name="l00281"></a><a class="code" href="classeEmp.html#8c33034de0e35f03f8bb85d3d67438fd">00281</a>         <span class="keywordtype">int</span> <a class="code" href="classeEmp.html#8c33034de0e35f03f8bb85d3d67438fd" title="Number of particles.">n</a>; 
    179 <a name="l00283"></a><a class="code" href="classeEmp.html#ae78d144404ddba843c93b171b215de8">00283</a>         vec <a class="code" href="classeEmp.html#ae78d144404ddba843c93b171b215de8" title="Sample weights .">w</a>; 
    180 <a name="l00285"></a><a class="code" href="classeEmp.html#a4d6f4bbd6a6824fc39f14676701279a">00285</a>         Array&lt;vec&gt; <a class="code" href="classeEmp.html#a4d6f4bbd6a6824fc39f14676701279a" title="Samples .">samples</a>; 
    181 <a name="l00286"></a>00286 <span class="keyword">public</span>: 
    182 <a name="l00288"></a><a class="code" href="classeEmp.html#0c04b073ecd0dae3d498e680ae27e9e4">00288</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> ) {}; 
    183 <a name="l00290"></a>00290         <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 ); 
    184 <a name="l00292"></a><a class="code" href="classeEmp.html#31b2bfb73b72486a5c89f2ab850c7a9b">00292</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>;}; 
    185 <a name="l00294"></a><a class="code" href="classeEmp.html#31b747eca73b16f30370827ba4cc3575">00294</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>;}; 
    186 <a name="l00296"></a>00296         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 ); 
    187 <a name="l00298"></a><a class="code" href="classeEmp.html#83f9283f92b805508d896479dc1ccf12">00298</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;} 
    188 <a name="l00300"></a><a class="code" href="classeEmp.html#23e7358995400865ad2e278945922fb3">00300</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;} 
    189 <a name="l00301"></a><a class="code" href="classeEmp.html#ba055c19038cc72628d98e25197e982d">00301</a>         vec <a class="code" href="classeEmp.html#ba055c19038cc72628d98e25197e982d" title="return expected value">mean</a>()<span class="keyword"> const </span>{ 
    190 <a name="l00302"></a>00302                 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>() ); 
    191 <a name="l00303"></a>00303                 <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 );} 
    192 <a name="l00304"></a>00304                 <span class="keywordflow">return</span> pom; 
    193 <a name="l00305"></a>00305         } 
    194 <a name="l00306"></a>00306 }; 
    195 <a name="l00307"></a>00307  
    196 <a name="l00308"></a>00308  
    197 <a name="l00310"></a>00310  
    198 <a name="l00311"></a>00311 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt; 
    199 <a name="l00312"></a><a class="code" href="classenorm.html#7b5cb487a2570e8109bfdc0df149aa06">00312</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() ) {}; 
    200 <a name="l00313"></a>00313  
    201 <a name="l00314"></a>00314 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt; 
    202 <a name="l00315"></a><a class="code" href="classenorm.html#1394a65caa6e00d42e00cc99b12227af">00315</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 ) { 
    203 <a name="l00316"></a>00316 <span class="comment">//Fixme test dimensions of mu0 and R0;</span> 
    204 <a name="l00317"></a>00317         <a class="code" href="classenorm.html#71fde0d54bba147e00f612577f95ad20" title="mean value">mu</a> = mu0; 
    205 <a name="l00318"></a>00318         <a class="code" href="classenorm.html#4ccc8d8514d644ef1c98d8ab023748a1" title="Covariance matrix in decomposed form.">R</a> = R0; 
    206 <a name="l00319"></a>00319 }; 
    207 <a name="l00320"></a>00320  
    208 <a name="l00321"></a>00321 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt; 
    209 <a name="l00322"></a><a class="code" href="classenorm.html#5bf185e31e5954fceb90ada3debd2ff2">00322</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 ) { 
    210 <a name="l00323"></a>00323         <span class="comment">//</span> 
    211 <a name="l00324"></a>00324 }; 
    212 <a name="l00325"></a>00325  
    213 <a name="l00326"></a>00326 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt; 
    214 <a name="l00327"></a><a class="code" href="classenorm.html#5b5fd142b6b17ea334597960e3fe126a">00327</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 ) { 
    215 <a name="l00328"></a>00328         <span class="comment">//</span> 
    216 <a name="l00329"></a>00329 }; 
    217 <a name="l00330"></a>00330  
    218 <a name="l00331"></a>00331 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt; 
    219 <a name="l00332"></a><a class="code" href="classenorm.html#60b47544f6181ffd4530d3e415ce12c5">00332</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>{ 
    220 <a name="l00333"></a>00333         vec x ( <a class="code" href="classenorm.html#6938fc390a19cdaf6ad4503fcbaada4e" title="dimension (redundant from rv.count() for easier coding )">dim</a> ); 
    221 <a name="l00334"></a>00334         NorRNG.sample_vector ( <a class="code" href="classenorm.html#6938fc390a19cdaf6ad4503fcbaada4e" title="dimension (redundant from rv.count() for easier coding )">dim</a>,x ); 
    222 <a name="l00335"></a>00335         vec smp = <a class="code" href="classenorm.html#4ccc8d8514d644ef1c98d8ab023748a1" title="Covariance matrix in decomposed form.">R</a>.sqrt_mult ( x ); 
    223 <a name="l00336"></a>00336  
    224 <a name="l00337"></a>00337         smp += <a class="code" href="classenorm.html#71fde0d54bba147e00f612577f95ad20" title="mean value">mu</a>; 
    225 <a name="l00338"></a>00338         <span class="keywordflow">return</span> smp; 
    226 <a name="l00339"></a>00339 }; 
    227 <a name="l00340"></a>00340  
    228 <a name="l00341"></a>00341 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt; 
    229 <a name="l00342"></a><a class="code" href="classenorm.html#60f0f3bfa53d6e65843eea9532b16d36">00342</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>{ 
    230 <a name="l00343"></a>00343         mat X ( <a class="code" href="classenorm.html#6938fc390a19cdaf6ad4503fcbaada4e" title="dimension (redundant from rv.count() for easier coding )">dim</a>,N ); 
    231 <a name="l00344"></a>00344         vec x ( <a class="code" href="classenorm.html#6938fc390a19cdaf6ad4503fcbaada4e" title="dimension (redundant from rv.count() for easier coding )">dim</a> ); 
    232 <a name="l00345"></a>00345         vec pom; 
    233 <a name="l00346"></a>00346         <span class="keywordtype">int</span> i; 
    234 <a name="l00347"></a>00347  
    235 <a name="l00348"></a>00348         <span class="keywordflow">for</span> ( i=0;i&lt;N;i++ ) { 
    236 <a name="l00349"></a>00349                 NorRNG.sample_vector ( <a class="code" href="classenorm.html#6938fc390a19cdaf6ad4503fcbaada4e" title="dimension (redundant from rv.count() for easier coding )">dim</a>,x ); 
    237 <a name="l00350"></a>00350                 pom = <a class="code" href="classenorm.html#4ccc8d8514d644ef1c98d8ab023748a1" title="Covariance matrix in decomposed form.">R</a>.sqrt_mult ( x ); 
    238 <a name="l00351"></a>00351                 pom +=<a class="code" href="classenorm.html#71fde0d54bba147e00f612577f95ad20" title="mean value">mu</a>; 
    239 <a name="l00352"></a>00352                 X.set_col ( i, pom ); 
    240 <a name="l00353"></a>00353         } 
    241 <a name="l00354"></a>00354  
    242 <a name="l00355"></a>00355         <span class="keywordflow">return</span> X; 
    243 <a name="l00356"></a>00356 }; 
    244 <a name="l00357"></a>00357  
    245 <a name="l00358"></a>00358 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt; 
    246 <a name="l00359"></a><a class="code" href="classenorm.html#b9e1dfd33692d7b3f1a59f17b0e61bd0">00359</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>{ 
    247 <a name="l00360"></a>00360         <span class="keywordtype">double</span> pdfl,e; 
    248 <a name="l00361"></a>00361         pdfl = <a class="code" href="classenorm.html#609a7c33dbb4fdfab050f3bdd1122401" title="Compute log-probability of argument val.">evalpdflog</a> ( val ); 
    249 <a name="l00362"></a>00362         e = exp ( pdfl ); 
    250 <a name="l00363"></a>00363         <span class="keywordflow">return</span> e; 
     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> 
    251238<a name="l00364"></a>00364 }; 
    252239<a name="l00365"></a>00365  
    253240<a name="l00366"></a>00366 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt; 
    254 <a name="l00367"></a><a class="code" href="classenorm.html#609a7c33dbb4fdfab050f3bdd1122401">00367</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>{ 
    255 <a name="l00368"></a>00368         <span class="comment">// 1.83787706640935 = log(2pi)</span> 
    256 <a name="l00369"></a>00369         <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() +<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 ) ); 
    257 <a name="l00370"></a>00370 }; 
     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 ); 
    258245<a name="l00371"></a>00371  
    259 <a name="l00372"></a>00372  
    260 <a name="l00373"></a>00373 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt; 
    261 <a name="l00374"></a><a class="code" href="classmlnorm.html#f927203b3f31171c5c10ffc7caa797f5">00374</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>()) { 
    262 <a name="l00375"></a>00375 } 
    263 <a name="l00376"></a>00376  
    264 <a name="l00377"></a>00377 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt; 
    265 <a name="l00378"></a><a class="code" href="classmlnorm.html#b6749030c5d5abcb3eb6898f74cea3c0">00378</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 ) { 
    266 <a name="l00379"></a>00379         <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 ); 
    267 <a name="l00380"></a>00380         A = A0; 
    268 <a name="l00381"></a>00381 } 
     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; 
    269256<a name="l00382"></a>00382  
    270 <a name="l00383"></a>00383 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt; 
    271 <a name="l00384"></a><a class="code" href="classmlnorm.html#decf3e3b5c8e0812e5b4dbe94fa2ae18">00384</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 ) { 
    272 <a name="l00385"></a>00385         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 ); 
    273 <a name="l00386"></a>00386         vec smp = <a class="code" href="classepdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a>.sample(); 
    274 <a name="l00387"></a>00387         lik = <a class="code" href="classepdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a>.eval ( smp ); 
    275 <a name="l00388"></a>00388         <span class="keywordflow">return</span> smp; 
    276 <a name="l00389"></a>00389 } 
    277 <a name="l00390"></a>00390  
    278 <a name="l00391"></a>00391 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt; 
    279 <a name="l00392"></a><a class="code" href="classmlnorm.html#215fb88cc8b95d64cdefd6849abdd1e8">00392</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 ) { 
    280 <a name="l00393"></a>00393         <span class="keywordtype">int</span> i; 
    281 <a name="l00394"></a>00394         <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>(); 
    282 <a name="l00395"></a>00395         mat Smp ( dim,n ); 
    283 <a name="l00396"></a>00396         vec smp ( dim ); 
    284 <a name="l00397"></a>00397         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 ); 
    285 <a name="l00398"></a>00398  
    286 <a name="l00399"></a>00399         <span class="keywordflow">for</span> ( i=0; i&lt;n; i++ ) { 
    287 <a name="l00400"></a>00400                 smp = <a class="code" href="classepdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a>.sample(); 
    288 <a name="l00401"></a>00401                 lik ( i ) = <a class="code" href="classepdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a>.eval ( smp ); 
    289 <a name="l00402"></a>00402                 Smp.set_col ( i ,smp ); 
    290 <a name="l00403"></a>00403         } 
    291 <a name="l00404"></a>00404  
    292 <a name="l00405"></a>00405         <span class="keywordflow">return</span> Smp; 
    293 <a name="l00406"></a>00406 } 
    294 <a name="l00407"></a>00407  
    295 <a name="l00408"></a>00408 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt; 
    296 <a name="l00409"></a><a class="code" href="classmlnorm.html#5232fc7e305eceab4e2bd6a8daa44195">00409</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 ) { 
    297 <a name="l00410"></a>00410         _mu = A*cond; 
    298 <a name="l00411"></a>00411 <span class="comment">//R is already assigned;</span> 
    299 <a name="l00412"></a>00412 } 
    300 <a name="l00413"></a>00413  
    301 <a name="l00415"></a>00415  
     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 } 
    302290<a name="l00416"></a>00416  
    303 <a name="l00417"></a>00417 <span class="preprocessor">#endif //EF_H</span> 
     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> 
    304331</pre></div></div> 
    305 <hr size="1"><address style="text-align: right;"><small>Generated on Tue Apr 29 20:46:25 2008 for mixpp by&nbsp; 
     332<hr size="1"><address style="text-align: right;"><small>Generated on Fri May 9 16:15:21 2008 for mixpp by&nbsp; 
    306333<a href="http://www.doxygen.org/index.html"> 
    307334<img src="doxygen.png" alt="doxygen" align="middle" border="0"></a> 1.5.5 </small></address>