| 45 | | <a name="l00052"></a>00052 <a class="code" href="classenorm.html" title="General exponential family density.">enorm</a>( <a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> &rv, vec &mu, sq_T &R ); |
| 46 | | <a name="l00053"></a>00053 <a class="code" href="classenorm.html" title="General exponential family density.">enorm</a>(); |
| 47 | | <a name="l00054"></a>00054 <span class="keywordtype">void</span> tupdate( <span class="keywordtype">double</span> phi, mat &vbar, <span class="keywordtype">double</span> nubar ); |
| 48 | | <a name="l00055"></a>00055 <span class="keywordtype">void</span> dupdate( mat &v,<span class="keywordtype">double</span> nu=1.0 ); |
| 49 | | <a name="l00056"></a>00056 vec <a class="code" href="classenorm.html#6020bcd89db2c9584bd8871001bd2023" title="Returns the required moment of the epdf.">sample</a>(); |
| 50 | | <a name="l00057"></a>00057 mat <a class="code" href="classenorm.html#6020bcd89db2c9584bd8871001bd2023" title="Returns the required moment of the epdf.">sample</a>(<span class="keywordtype">int</span> N); |
| 51 | | <a name="l00058"></a>00058 <span class="keywordtype">double</span> eval( <span class="keyword">const</span> vec &val ); |
| 52 | | <a name="l00059"></a>00059 Normal_RNG RNG; |
| 53 | | <a name="l00060"></a>00060 }; |
| 54 | | <a name="l00061"></a>00061 |
| 55 | | <a name="l00065"></a>00065 <span class="keyword">template</span><<span class="keyword">class</span> sq_T> |
| 56 | | <a name="l00066"></a>00066 <span class="keyword">class </span>mlnorm : <span class="keyword">public</span> mEF { |
| 57 | | <a name="l00067"></a>00067 <a class="code" href="classenorm.html" title="General exponential family density.">enorm<sq_T></a> <a class="code" href="classepdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a>; |
| 58 | | <a name="l00068"></a>00068 mat A; |
| 59 | | <a name="l00069"></a>00069 <span class="keyword">public</span>: |
| 60 | | <a name="l00071"></a>00071 mlnorm( <a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> &rv,<a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> &rvc, mat &A, sq_T &R ); |
| 61 | | <a name="l00073"></a>00073 vec samplecond( vec &cond, <span class="keywordtype">double</span> &lik ); |
| 62 | | <a name="l00074"></a>00074 mat samplecond( vec &cond, vec &lik, <span class="keywordtype">int</span> n ); |
| 63 | | <a name="l00075"></a>00075 <span class="keywordtype">void</span> condition( vec &cond ); |
| 64 | | <a name="l00076"></a>00076 }; |
| 65 | | <a name="l00077"></a>00077 |
| 66 | | <a name="l00079"></a>00079 |
| 67 | | <a name="l00080"></a>00080 <span class="keyword">template</span><<span class="keyword">class</span> sq_T> |
| 68 | | <a name="l00081"></a>00081 <a class="code" href="classenorm.html" title="General exponential family density.">enorm<sq_T>::enorm</a>( <a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> &rv, vec &mu0, sq_T &R0 ) { |
| 69 | | <a name="l00082"></a>00082 dim = rv.<a class="code" href="classRV.html#9dcaca7b87cfb0e24a19260067d62f04" title="Return length (number of scalars) of the RV.">count</a>(); |
| 70 | | <a name="l00083"></a>00083 mu = mu0; |
| 71 | | <a name="l00084"></a>00084 R = R0; |
| 72 | | <a name="l00085"></a>00085 }; |
| 73 | | <a name="l00086"></a>00086 |
| 74 | | <a name="l00087"></a>00087 <span class="keyword">template</span><<span class="keyword">class</span> sq_T> |
| 75 | | <a name="l00088"></a>00088 <span class="keywordtype">void</span> <a class="code" href="classenorm.html" title="General exponential family density.">enorm<sq_T>::dupdate</a>( mat &v, <span class="keywordtype">double</span> nu ) { |
| 76 | | <a name="l00089"></a>00089 <span class="comment">//</span> |
| 77 | | <a name="l00090"></a>00090 }; |
| 78 | | <a name="l00091"></a>00091 |
| 79 | | <a name="l00092"></a>00092 <span class="keyword">template</span><<span class="keyword">class</span> sq_T> |
| 80 | | <a name="l00093"></a>00093 <span class="keywordtype">void</span> <a class="code" href="classenorm.html" title="General exponential family density.">enorm<sq_T>::tupdate</a>( <span class="keywordtype">double</span> phi, mat &vbar, <span class="keywordtype">double</span> nubar ) { |
| 81 | | <a name="l00094"></a>00094 <span class="comment">//</span> |
| 82 | | <a name="l00095"></a>00095 }; |
| 83 | | <a name="l00096"></a>00096 |
| 84 | | <a name="l00097"></a>00097 <span class="keyword">template</span><<span class="keyword">class</span> sq_T> |
| 85 | | <a name="l00098"></a><a class="code" href="classenorm.html#6020bcd89db2c9584bd8871001bd2023">00098</a> vec <a class="code" href="classenorm.html#6020bcd89db2c9584bd8871001bd2023" title="Returns the required moment of the epdf.">enorm<sq_T>::sample</a>() { |
| 86 | | <a name="l00099"></a>00099 vec x( dim ); |
| 87 | | <a name="l00100"></a>00100 RNG.sample_vector( dim,x ); |
| 88 | | <a name="l00101"></a>00101 vec smp = R.sqrt_mult( x ); |
| | 45 | <a name="l00052"></a>00052 <a class="code" href="classenorm.html" title="Gaussian density with positive definite (decomposed) covariance matrix.">enorm</a>( <a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> &rv, vec &mu, sq_T &R ); |
| | 46 | <a name="l00053"></a>00053 <a class="code" href="classenorm.html" title="Gaussian density with positive definite (decomposed) covariance matrix.">enorm</a>(); |
| | 47 | <a name="l00055"></a>00055 <span class="keywordtype">void</span> <a class="code" href="classenorm.html#2a1a522504c7788dfd7fb733157ee39e" title="tupdate used in KF">tupdate</a>( <span class="keywordtype">double</span> phi, mat &vbar, <span class="keywordtype">double</span> nubar ); |
| | 48 | <a name="l00056"></a>00056 <span class="keywordtype">void</span> <a class="code" href="classenorm.html#d1b0faf61260de09cf63bf823add5b32" title="dupdate used in KF">dupdate</a>( mat &v,<span class="keywordtype">double</span> nu=1.0 ); |
| | 49 | <a name="l00058"></a>00058 <span class="keywordtype">void</span> <a class="code" href="classenorm.html#2a1a522504c7788dfd7fb733157ee39e" title="tupdate used in KF">tupdate</a>(); |
| | 50 | <a name="l00060"></a>00060 <span class="keywordtype">double</span> <a class="code" href="classenorm.html#d1b0faf61260de09cf63bf823add5b32" title="dupdate used in KF">dupdate</a>(); |
| | 51 | <a name="l00061"></a>00061 |
| | 52 | <a name="l00062"></a>00062 vec <a class="code" href="classenorm.html#6020bcd89db2c9584bd8871001bd2023" title="Returns the required moment of the epdf.">sample</a>(); |
| | 53 | <a name="l00063"></a>00063 mat <a class="code" href="classenorm.html#6020bcd89db2c9584bd8871001bd2023" title="Returns the required moment of the epdf.">sample</a>(<span class="keywordtype">int</span> N); |
| | 54 | <a name="l00064"></a>00064 <span class="keywordtype">double</span> <a class="code" href="classenorm.html#93107f05a8e9b34b64853767200121a4" title="Compute probability of argument val.">eval</a>( <span class="keyword">const</span> vec &val ); |
| | 55 | <a name="l00065"></a>00065 Normal_RNG RNG; |
| | 56 | <a name="l00066"></a>00066 }; |
| | 57 | <a name="l00067"></a>00067 |
| | 58 | <a name="l00071"></a>00071 <span class="keyword">template</span><<span class="keyword">class</span> sq_T> |
| | 59 | <a name="l00072"></a>00072 <span class="keyword">class </span>mlnorm : <span class="keyword">public</span> mEF { |
| | 60 | <a name="l00073"></a>00073 <a class="code" href="classenorm.html" title="Gaussian density with positive definite (decomposed) covariance matrix.">enorm<sq_T></a> <a class="code" href="classepdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a>; |
| | 61 | <a name="l00074"></a>00074 mat A; |
| | 62 | <a name="l00075"></a>00075 <span class="keyword">public</span>: |
| | 63 | <a name="l00077"></a>00077 mlnorm( <a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> &rv,<a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> &rvc, mat &A, sq_T &R ); |
| | 64 | <a name="l00079"></a>00079 vec samplecond( vec &cond, <span class="keywordtype">double</span> &lik ); |
| | 65 | <a name="l00080"></a>00080 mat samplecond( vec &cond, vec &lik, <span class="keywordtype">int</span> n ); |
| | 66 | <a name="l00081"></a>00081 <span class="keywordtype">void</span> condition( vec &cond ); |
| | 67 | <a name="l00082"></a>00082 }; |
| | 68 | <a name="l00083"></a>00083 |
| | 69 | <a name="l00085"></a>00085 |
| | 70 | <a name="l00086"></a>00086 <span class="keyword">template</span><<span class="keyword">class</span> sq_T> |
| | 71 | <a name="l00087"></a>00087 <a class="code" href="classenorm.html" title="Gaussian density with positive definite (decomposed) covariance matrix.">enorm<sq_T>::enorm</a>( <a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> &rv, vec &mu0, sq_T &R0 ) { |
| | 72 | <a name="l00088"></a>00088 dim = rv.<a class="code" href="classRV.html#f5c7b8bd589eef09ccdf3329a0addea0" title="Return length (number of scalars) of the RV.">count</a>(); |
| | 73 | <a name="l00089"></a>00089 mu = mu0; |
| | 74 | <a name="l00090"></a>00090 R = R0; |
| | 75 | <a name="l00091"></a>00091 }; |
| | 76 | <a name="l00092"></a>00092 |
| | 77 | <a name="l00093"></a>00093 <span class="keyword">template</span><<span class="keyword">class</span> sq_T> |
| | 78 | <a name="l00094"></a>00094 <span class="keywordtype">void</span> <a class="code" href="classenorm.html#d1b0faf61260de09cf63bf823add5b32" title="dupdate used in KF">enorm<sq_T>::dupdate</a>( mat &v, <span class="keywordtype">double</span> nu ) { |
| | 79 | <a name="l00095"></a>00095 <span class="comment">//</span> |
| | 80 | <a name="l00096"></a>00096 }; |
| | 81 | <a name="l00097"></a>00097 |
| | 82 | <a name="l00098"></a>00098 <span class="keyword">template</span><<span class="keyword">class</span> sq_T> |
| | 83 | <a name="l00099"></a><a class="code" href="classenorm.html#5b5fd142b6b17ea334597960e3fe126a">00099</a> <span class="keywordtype">void</span> <a class="code" href="classenorm.html#2a1a522504c7788dfd7fb733157ee39e" title="tupdate used in KF">enorm<sq_T>::tupdate</a>( <span class="keywordtype">double</span> phi, mat &vbar, <span class="keywordtype">double</span> nubar ) { |
| | 84 | <a name="l00100"></a>00100 <span class="comment">//</span> |
| | 85 | <a name="l00101"></a>00101 }; |
| 90 | | <a name="l00103"></a>00103 smp += mu; |
| 91 | | <a name="l00104"></a>00104 <span class="keywordflow">return</span> smp; |
| 92 | | <a name="l00105"></a>00105 }; |
| 93 | | <a name="l00106"></a>00106 |
| 94 | | <a name="l00107"></a>00107 <span class="keyword">template</span><<span class="keyword">class</span> sq_T> |
| 95 | | <a name="l00108"></a>00108 mat <a class="code" href="classenorm.html#6020bcd89db2c9584bd8871001bd2023" title="Returns the required moment of the epdf.">enorm<sq_T>::sample</a>( <span class="keywordtype">int</span> N ) { |
| 96 | | <a name="l00109"></a>00109 mat X( dim,N ); |
| 97 | | <a name="l00110"></a>00110 vec x( dim ); |
| 98 | | <a name="l00111"></a>00111 vec pom; |
| 99 | | <a name="l00112"></a>00112 <span class="keywordtype">int</span> i; |
| 100 | | <a name="l00113"></a>00113 <span class="keywordflow">for</span> ( i=0;i<N;i++ ) { |
| 101 | | <a name="l00114"></a>00114 RNG.sample_vector( dim,x ); |
| 102 | | <a name="l00115"></a>00115 pom = R.sqrt_mult( x ); |
| 103 | | <a name="l00116"></a>00116 pom +=mu; |
| 104 | | <a name="l00117"></a>00117 X.set_col( i, pom); |
| 105 | | <a name="l00118"></a>00118 } |
| 106 | | <a name="l00119"></a>00119 <span class="keywordflow">return</span> X; |
| 107 | | <a name="l00120"></a>00120 }; |
| 108 | | <a name="l00121"></a>00121 |
| 109 | | <a name="l00122"></a>00122 <span class="keyword">template</span><<span class="keyword">class</span> sq_T> |
| 110 | | <a name="l00123"></a>00123 <span class="keywordtype">double</span> <a class="code" href="classenorm.html" title="General exponential family density.">enorm<sq_T>::eval</a>( <span class="keyword">const</span> vec &val ) { |
| 111 | | <a name="l00124"></a>00124 <span class="comment">//</span> |
| 112 | | <a name="l00125"></a>00125 }; |
| 113 | | <a name="l00126"></a>00126 |
| | 87 | <a name="l00103"></a>00103 <span class="keyword">template</span><<span class="keyword">class</span> sq_T> |
| | 88 | <a name="l00104"></a><a class="code" href="classenorm.html#6020bcd89db2c9584bd8871001bd2023">00104</a> vec <a class="code" href="classenorm.html#6020bcd89db2c9584bd8871001bd2023" title="Returns the required moment of the epdf.">enorm<sq_T>::sample</a>() { |
| | 89 | <a name="l00105"></a>00105 vec x( dim ); |
| | 90 | <a name="l00106"></a>00106 RNG.sample_vector( dim,x ); |
| | 91 | <a name="l00107"></a>00107 vec smp = R.sqrt_mult( x ); |
| | 92 | <a name="l00108"></a>00108 |
| | 93 | <a name="l00109"></a>00109 smp += mu; |
| | 94 | <a name="l00110"></a>00110 <span class="keywordflow">return</span> smp; |
| | 95 | <a name="l00111"></a>00111 }; |
| | 96 | <a name="l00112"></a>00112 |
| | 97 | <a name="l00113"></a>00113 <span class="keyword">template</span><<span class="keyword">class</span> sq_T> |
| | 98 | <a name="l00114"></a>00114 mat <a class="code" href="classenorm.html#6020bcd89db2c9584bd8871001bd2023" title="Returns the required moment of the epdf.">enorm<sq_T>::sample</a>( <span class="keywordtype">int</span> N ) { |
| | 99 | <a name="l00115"></a>00115 mat X( dim,N ); |
| | 100 | <a name="l00116"></a>00116 vec x( dim ); |
| | 101 | <a name="l00117"></a>00117 vec pom; |
| | 102 | <a name="l00118"></a>00118 <span class="keywordtype">int</span> i; |
| | 103 | <a name="l00119"></a>00119 <span class="keywordflow">for</span> ( i=0;i<N;i++ ) { |
| | 104 | <a name="l00120"></a>00120 RNG.sample_vector( dim,x ); |
| | 105 | <a name="l00121"></a>00121 pom = R.sqrt_mult( x ); |
| | 106 | <a name="l00122"></a>00122 pom +=mu; |
| | 107 | <a name="l00123"></a>00123 X.set_col( i, pom); |
| | 108 | <a name="l00124"></a>00124 } |
| | 109 | <a name="l00125"></a>00125 <span class="keywordflow">return</span> X; |
| | 110 | <a name="l00126"></a>00126 }; |
| 116 | | <a name="l00129"></a>00129 <a class="code" href="classenorm.html" title="General exponential family density.">enorm<sq_T>::enorm</a>() {}; |
| 117 | | <a name="l00130"></a>00130 |
| 118 | | <a name="l00131"></a>00131 <span class="keyword">template</span><<span class="keyword">class</span> sq_T> |
| 119 | | <a name="l00132"></a>00132 mlnorm<sq_T>::mlnorm( <a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> &rv,<a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> &rvc, mat &A, sq_T &R ) { |
| 120 | | <a name="l00133"></a>00133 <span class="keywordtype">int</span> dim = rv.<a class="code" href="classRV.html#9dcaca7b87cfb0e24a19260067d62f04" title="Return length (number of scalars) of the RV.">count</a>(); |
| 121 | | <a name="l00134"></a>00134 vec mu( dim ); |
| 122 | | <a name="l00135"></a>00135 |
| 123 | | <a name="l00136"></a>00136 <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" title="General exponential family density.">enorm<sq_T></a>( rv,mu,R ); |
| 124 | | <a name="l00137"></a>00137 } |
| 125 | | <a name="l00138"></a>00138 |
| 126 | | <a name="l00139"></a>00139 <span class="keyword">template</span><<span class="keyword">class</span> sq_T> |
| 127 | | <a name="l00140"></a>00140 vec mlnorm<sq_T>::samplecond( vec &cond, <span class="keywordtype">double</span> &lik ) { |
| 128 | | <a name="l00141"></a>00141 this->condition( cond ); |
| 129 | | <a name="l00142"></a>00142 vec smp = <a class="code" href="classepdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a>.sample(); |
| 130 | | <a name="l00143"></a>00143 lik = <a class="code" href="classepdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a>.eval( smp ); |
| 131 | | <a name="l00144"></a>00144 <span class="keywordflow">return</span> smp; |
| 132 | | <a name="l00145"></a>00145 } |
| 133 | | <a name="l00146"></a>00146 |
| 134 | | <a name="l00147"></a>00147 <span class="keyword">template</span><<span class="keyword">class</span> sq_T> |
| 135 | | <a name="l00148"></a>00148 mat mlnorm<sq_T>::samplecond( vec &cond, vec &lik, <span class="keywordtype">int</span> n ) { |
| 136 | | <a name="l00149"></a>00149 <span class="keywordtype">int</span> i; |
| 137 | | <a name="l00150"></a>00150 <span class="keywordtype">int</span> dim = rv.<a class="code" href="classRV.html#9dcaca7b87cfb0e24a19260067d62f04" title="Return length (number of scalars) of the RV.">count</a>(); |
| 138 | | <a name="l00151"></a>00151 mat Smp( dim,n ); |
| 139 | | <a name="l00152"></a>00152 vec smp( dim ); |
| 140 | | <a name="l00153"></a>00153 this->condition( cond ); |
| 141 | | <a name="l00154"></a>00154 <span class="keywordflow">for</span> ( i=0; i<dim; i++ ) { |
| 142 | | <a name="l00155"></a>00155 smp = <a class="code" href="classepdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a>.sample(); |
| 143 | | <a name="l00156"></a>00156 lik( i ) = <a class="code" href="classepdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a>.eval( smp ); |
| 144 | | <a name="l00157"></a>00157 Smp.set_col( i ,smp ); |
| 145 | | <a name="l00158"></a>00158 } |
| 146 | | <a name="l00159"></a>00159 <span class="keywordflow">return</span> Smp; |
| 147 | | <a name="l00160"></a>00160 } |
| 148 | | <a name="l00161"></a>00161 |
| 149 | | <a name="l00162"></a>00162 <span class="keyword">template</span><<span class="keyword">class</span> sq_T> |
| 150 | | <a name="l00163"></a>00163 <span class="keywordtype">void</span> mlnorm<sq_T>::condition( vec &cond ) { |
| 151 | | <a name="l00164"></a>00164 <a class="code" href="classepdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a>.mu = A*cond; |
| 152 | | <a name="l00165"></a>00165 <span class="comment">//R is already assigned;</span> |
| | 113 | <a name="l00129"></a><a class="code" href="classenorm.html#93107f05a8e9b34b64853767200121a4">00129</a> <span class="keywordtype">double</span> <a class="code" href="classenorm.html#93107f05a8e9b34b64853767200121a4" title="Compute probability of argument val.">enorm<sq_T>::eval</a>( <span class="keyword">const</span> vec &val ) { |
| | 114 | <a name="l00130"></a>00130 <span class="comment">//</span> |
| | 115 | <a name="l00131"></a>00131 }; |
| | 116 | <a name="l00132"></a>00132 |
| | 117 | <a name="l00133"></a>00133 |
| | 118 | <a name="l00134"></a>00134 <span class="keyword">template</span><<span class="keyword">class</span> sq_T> |
| | 119 | <a name="l00135"></a>00135 <a class="code" href="classenorm.html" title="Gaussian density with positive definite (decomposed) covariance matrix.">enorm<sq_T>::enorm</a>() {}; |
| | 120 | <a name="l00136"></a>00136 |
| | 121 | <a name="l00137"></a>00137 <span class="keyword">template</span><<span class="keyword">class</span> sq_T> |
| | 122 | <a name="l00138"></a>00138 mlnorm<sq_T>::mlnorm( <a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> &rv,<a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> &rvc, mat &A, sq_T &R ) { |
| | 123 | <a name="l00139"></a>00139 <span class="keywordtype">int</span> dim = rv.<a class="code" href="classRV.html#f5c7b8bd589eef09ccdf3329a0addea0" title="Return length (number of scalars) of the RV.">count</a>(); |
| | 124 | <a name="l00140"></a>00140 vec mu( dim ); |
| | 125 | <a name="l00141"></a>00141 |
| | 126 | <a name="l00142"></a>00142 <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" title="Gaussian density with positive definite (decomposed) covariance matrix.">enorm<sq_T></a>( rv,mu,R ); |
| | 127 | <a name="l00143"></a>00143 } |
| | 128 | <a name="l00144"></a>00144 |
| | 129 | <a name="l00145"></a>00145 <span class="keyword">template</span><<span class="keyword">class</span> sq_T> |
| | 130 | <a name="l00146"></a>00146 vec mlnorm<sq_T>::samplecond( vec &cond, <span class="keywordtype">double</span> &lik ) { |
| | 131 | <a name="l00147"></a>00147 this->condition( cond ); |
| | 132 | <a name="l00148"></a>00148 vec smp = <a class="code" href="classepdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a>.sample(); |
| | 133 | <a name="l00149"></a>00149 lik = <a class="code" href="classepdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a>.eval( smp ); |
| | 134 | <a name="l00150"></a>00150 <span class="keywordflow">return</span> smp; |
| | 135 | <a name="l00151"></a>00151 } |
| | 136 | <a name="l00152"></a>00152 |
| | 137 | <a name="l00153"></a>00153 <span class="keyword">template</span><<span class="keyword">class</span> sq_T> |
| | 138 | <a name="l00154"></a>00154 mat mlnorm<sq_T>::samplecond( vec &cond, vec &lik, <span class="keywordtype">int</span> n ) { |
| | 139 | <a name="l00155"></a>00155 <span class="keywordtype">int</span> i; |
| | 140 | <a name="l00156"></a>00156 <span class="keywordtype">int</span> dim = rv.<a class="code" href="classRV.html#f5c7b8bd589eef09ccdf3329a0addea0" title="Return length (number of scalars) of the RV.">count</a>(); |
| | 141 | <a name="l00157"></a>00157 mat Smp( dim,n ); |
| | 142 | <a name="l00158"></a>00158 vec smp( dim ); |
| | 143 | <a name="l00159"></a>00159 this->condition( cond ); |
| | 144 | <a name="l00160"></a>00160 <span class="keywordflow">for</span> ( i=0; i<dim; i++ ) { |
| | 145 | <a name="l00161"></a>00161 smp = <a class="code" href="classepdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a>.sample(); |
| | 146 | <a name="l00162"></a>00162 lik( i ) = <a class="code" href="classepdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a>.eval( smp ); |
| | 147 | <a name="l00163"></a>00163 Smp.set_col( i ,smp ); |
| | 148 | <a name="l00164"></a>00164 } |
| | 149 | <a name="l00165"></a>00165 <span class="keywordflow">return</span> Smp; |
