Changeset 219 for doc/latex

Timestamp:

12/18/08 20:38:46 (16 years ago)

Author:

smidl

Message:

doc

Location:

doc/latex

Files:

• classEKFful__unQR.tex (modified) (1 diff)
• classEKFfull.tex (modified) (1 diff)
• classKalmanCh.tex (modified) (1 diff)
• classMixEF.tex (modified) (1 diff)
• classPF.tex (modified) (1 diff)
• classRV.tex (modified) (3 diffs)
• classeDirich.tex (modified) (3 diffs)
• classeEF.tex (modified) (2 diffs)
• classeEmp.tex (modified) (2 diffs)
• classegamma.tex (modified) (3 diffs)
• classegiw.tex (modified) (3 diffs)
• classemix.tex (modified) (1 diff)
• classenorm.tex (modified) (4 diffs)
• classepdf.tex (modified) (1 diff)
• classeprod.tex (modified) (2 diffs)
• classeuni.tex (modified) (2 diffs)
• classfsqmat.tex (modified) (1 diff)
• classldmat.tex (modified) (5 diffs)
• classmEF.tex (modified) (4 diffs)
• classmepdf.tex (modified) (3 diffs)
• classmerger.tex (modified) (2 diffs)
• classmgamma.tex (modified) (3 diffs)
• classmgamma__fix.tex (modified) (3 diffs)
• classmlnorm.tex (modified) (3 diffs)
• classmlstudent.tex (modified) (3 diffs)
• classmmix.tex (modified) (3 diffs)
• classmpdf.tex (modified) (4 diffs)
• classmprod.tex (modified) (5 diffs)
• classmratio.tex (modified) (6 diffs)
• doxygen.sty (modified) (1 diff)
• group__core.tex (copied) (copied from doc/latex/libBM_8h.tex) (2 diffs)
• group__math.tex (added)
• libBM_8h.tex (modified) (1 diff)
• libDC_8h.tex (modified) (1 diff)
• modules.tex (added)
• refman.tex (modified) (3 diffs)

doc/latex/classEKFful__unQR.tex

@@ -60 +60 @@
 
 \begin{CompactList}\small\item\em Returns a pointer to the \hyperlink{classepdf}{epdf} representing posterior density on parameters. Use with care! \item\end{CompactList}\item 
+\hypertarget{classEKFfull_31f310660d78999286d2a4e9267e85fb}{
+const mat \textbf{\_\-R} ()}
+\label{classEKFfull_31f310660d78999286d2a4e9267e85fb}
+
+\item 
 \hypertarget{classBM_0186270f75189677f390fe088a9947e9}{
 virtual void \hyperlink{classBM_0186270f75189677f390fe088a9947e9}{bayesB} (const mat \&Dt)}

doc/latex/classEKFfull.tex

@@ -55 +55 @@
 
 \begin{CompactList}\small\item\em Returns a pointer to the \hyperlink{classepdf}{epdf} representing posterior density on parameters. Use with care! \item\end{CompactList}\item 
+\hypertarget{classEKFfull_31f310660d78999286d2a4e9267e85fb}{
+const mat \textbf{\_\-R} ()}
+\label{classEKFfull_31f310660d78999286d2a4e9267e85fb}
+
+\item 
 \hypertarget{classBM_0186270f75189677f390fe088a9947e9}{
 virtual void \hyperlink{classBM_0186270f75189677f390fe088a9947e9}{bayesB} (const mat \&Dt)}

doc/latex/classKalmanCh.tex

@@ -237 +237 @@
 Reimplemented in \hyperlink{classEKFCh_96f6edda324a0b7ef8b4e86cc7af60c1}{EKFCh}.
 
-References chmat::\_\-Ch(), Kalman$<$ chmat $>$::\_\-K, Kalman$<$ chmat $>$::\_\-mu, Kalman$<$ chmat $>$::\_\-P, Kalman$<$ chmat $>$::\_\-Ry, Kalman$<$ chmat $>$::\_\-yp, Kalman$<$ chmat $>$::A, Kalman$<$ chmat $>$::B, Kalman$<$ chmat $>$::C, Kalman$<$ chmat $>$::D, Kalman$<$ chmat $>$::dimu, Kalman$<$ chmat $>$::dimx, Kalman$<$ chmat $>$::dimy, BM::evalll, eEF::evalpdflog(), Kalman$<$ chmat $>$::fy, BM::ll, postA, preA, and chmat::to\_\-mat().\hypertarget{classBM_8a8ce6df431689964c41cc6c849cfd06}{
+References chmat::\_\-Ch(), Kalman$<$ chmat $>$::\_\-K, Kalman$<$ chmat $>$::\_\-mu, Kalman$<$ chmat $>$::\_\-P, Kalman$<$ chmat $>$::\_\-Ry, Kalman$<$ chmat $>$::\_\-yp, Kalman$<$ chmat $>$::A, Kalman$<$ chmat $>$::B, Kalman$<$ chmat $>$::C, Kalman$<$ chmat $>$::D, Kalman$<$ chmat $>$::dimu, Kalman$<$ chmat $>$::dimx, Kalman$<$ chmat $>$::dimy, BM::evalll, eEF::evallog(), Kalman$<$ chmat $>$::fy, BM::ll, postA, and preA.\hypertarget{classBM_8a8ce6df431689964c41cc6c849cfd06}{
 \index{KalmanCh@{KalmanCh}!logpred@{logpred}}
 \index{logpred@{logpred}!KalmanCh@{KalmanCh}}

doc/latex/classMixEF.tex

@@ -233 +233 @@
 References multiBM::\_\-epdf(), Coms, epdf::mean(), and weights.
 
-Referenced by merger::evalpdflog(), and merger::merge().
+Referenced by merger::evallog(), and merger::merge().
 
 The documentation for this class was generated from the following files:\begin{CompactItemize}

doc/latex/classPF.tex

@@ -157 +157 @@
 Reimplemented in \hyperlink{classMPF_55daf8e4b6553dd9f47c692de7931623}{MPF$<$ BM\_\-T $>$}.
 
-References \_\-samples, \_\-w, est, mpdf::evalcond(), n, obs, par, eEmp::resample(), and mpdf::samplecond().\hypertarget{classBM_8a8ce6df431689964c41cc6c849cfd06}{
+References \_\-samples, \_\-w, est, mpdf::evallogcond(), n, obs, par, eEmp::resample(), and mpdf::samplecond().\hypertarget{classBM_8a8ce6df431689964c41cc6c849cfd06}{
 \index{PF@{PF}!logpred@{logpred}}
 \index{logpred@{logpred}!PF@{PF}}

doc/latex/classRV.tex

@@ -201 +201 @@
 
 
-References findself(), ids, len, names, sizes, times, and tsize.
+References concat(), findself(), ids, len, names, sizes, times, and tsize.
 
 Referenced by concat(), compositepdf::getrv(), merger::merger(), MPF$<$ BM\_\-T $>$::MPF(), and compositepdf::setrvc().\hypertarget{classRV_bb724fa4e2d9ed7bfd0993b5975018a4}{
@@ -212 +212 @@
 when this rv is a part of bigger rv, this function returns indeces of self in the data vector of the bigger crv. Then, data can be copied via: data\_\-of\_\-this = cdata(ind); 
 
-References count(), ids, str::ids, len, times, str::times, tostr(), and tsize.
+References concat(), count(), ids, str::ids, len, times, str::times, tostr(), and tsize.
 
 Referenced by enorm$<$ sq\_\-T $>$::condition(), datalink\_\-m2e::datalink\_\-m2e(), datalink\_\-m2m::datalink\_\-m2m(), and enorm$<$ sq\_\-T $>$::marginal().\hypertarget{classRV_777a5d87f2b95a60a7de467d7817f16e}{
@@ -223 +223 @@
 generate mutual indeces when copying data betwenn self and crv. Data are copied via: data\_\-of\_\-this(selfi) = data\_\-of\_\-rv2(rv2i) 
 
-References findself(), ids, str::ids, len, length(), times, str::times, and tostr().
+References concat(), findself(), ids, str::ids, len, length(), times, str::times, and tostr().
 
 The documentation for this class was generated from the following files:\begin{CompactItemize}

doc/latex/classeDirich.tex

@@ -45 +45 @@
 
 \begin{CompactList}\small\item\em return expected value \item\end{CompactList}\item 
-\hypertarget{classeDirich_688a24f04be6d80d4769cf0e4ded7acc}{
-double \hyperlink{classeDirich_688a24f04be6d80d4769cf0e4ded7acc}{evalpdflog\_\-nn} (const vec \&val) const }
-\label{classeDirich_688a24f04be6d80d4769cf0e4ded7acc}
+\hypertarget{classeDirich_bb4b14ed7794777386de10608a83d142}{
+double \hyperlink{classeDirich_bb4b14ed7794777386de10608a83d142}{evallog\_\-nn} (const vec \&val) const }
+\label{classeDirich_bb4b14ed7794777386de10608a83d142}
 
 \begin{CompactList}\small\item\em In this instance, val is ... \item\end{CompactList}\item 
@@ -70 +70 @@
 
 \begin{CompactList}\small\item\em TODO decide if it is really needed. \item\end{CompactList}\item 
-\hypertarget{classeEF_6466e8d4aa9dd64698ed288cbb1afc03}{
-virtual double \hyperlink{classeEF_6466e8d4aa9dd64698ed288cbb1afc03}{evalpdflog} (const vec \&val) const }
-\label{classeEF_6466e8d4aa9dd64698ed288cbb1afc03}
+\hypertarget{classeEF_357512dd565e199904d367294b7dd862}{
+virtual double \hyperlink{classeEF_357512dd565e199904d367294b7dd862}{evallog} (const vec \&val) const }
+\label{classeEF_357512dd565e199904d367294b7dd862}
 
 \begin{CompactList}\small\item\em Evaluate normalized log-probability. \item\end{CompactList}\item 
-\hypertarget{classeEF_c71faf4b2d153efda14bf1f87dca1507}{
-virtual vec \hyperlink{classeEF_c71faf4b2d153efda14bf1f87dca1507}{evalpdflog} (const mat \&Val) const }
-\label{classeEF_c71faf4b2d153efda14bf1f87dca1507}
+\hypertarget{classeEF_cff03a658aec11b806c3e3d48f37b81f}{
+virtual vec \hyperlink{classeEF_cff03a658aec11b806c3e3d48f37b81f}{evallog} (const mat \&Val) const }
+\label{classeEF_cff03a658aec11b806c3e3d48f37b81f}
 
 \begin{CompactList}\small\item\em Evaluate normalized log-probability for many samples. \item\end{CompactList}\item 
@@ -90 +90 @@
 
 \begin{CompactList}\small\item\em Returns N samples from density $epdf(rv)$. \item\end{CompactList}\item 
-\hypertarget{classepdf_cebbdd7a85e6328f7358fc0ba8eee06c}{
-virtual vec \hyperlink{classepdf_cebbdd7a85e6328f7358fc0ba8eee06c}{evalpdflog\_\-m} (const mat \&Val) const }
-\label{classepdf_cebbdd7a85e6328f7358fc0ba8eee06c}
+\hypertarget{classepdf_2495a04bbacb9b55fe5a3a59b78affca}{
+virtual vec \hyperlink{classepdf_2495a04bbacb9b55fe5a3a59b78affca}{evallog\_\-m} (const mat \&Val) const }
+\label{classepdf_2495a04bbacb9b55fe5a3a59b78affca}
 
 \begin{CompactList}\small\item\em Compute log-probability of multiple values argument {\tt val}. \item\end{CompactList}\item 

doc/latex/classeEF.tex

@@ -40 +40 @@
 
 \begin{CompactList}\small\item\em TODO decide if it is really needed. \item\end{CompactList}\item 
-\hypertarget{classeEF_48cdd33d0e20d1a1aa45683c956bc61c}{
-virtual double \hyperlink{classeEF_48cdd33d0e20d1a1aa45683c956bc61c}{evalpdflog\_\-nn} (const vec \&val) const }
-\label{classeEF_48cdd33d0e20d1a1aa45683c956bc61c}
+\hypertarget{classeEF_41c70565b4d3fb424599817d008f0c71}{
+virtual double \hyperlink{classeEF_41c70565b4d3fb424599817d008f0c71}{evallog\_\-nn} (const vec \&val) const }
+\label{classeEF_41c70565b4d3fb424599817d008f0c71}
 
 \begin{CompactList}\small\item\em Evaluate normalized log-probability. \item\end{CompactList}\item 
-\hypertarget{classeEF_6466e8d4aa9dd64698ed288cbb1afc03}{
-virtual double \hyperlink{classeEF_6466e8d4aa9dd64698ed288cbb1afc03}{evalpdflog} (const vec \&val) const }
-\label{classeEF_6466e8d4aa9dd64698ed288cbb1afc03}
+\hypertarget{classeEF_357512dd565e199904d367294b7dd862}{
+virtual double \hyperlink{classeEF_357512dd565e199904d367294b7dd862}{evallog} (const vec \&val) const }
+\label{classeEF_357512dd565e199904d367294b7dd862}
 
 \begin{CompactList}\small\item\em Evaluate normalized log-probability. \item\end{CompactList}\item 
-\hypertarget{classeEF_c71faf4b2d153efda14bf1f87dca1507}{
-virtual vec \hyperlink{classeEF_c71faf4b2d153efda14bf1f87dca1507}{evalpdflog} (const mat \&Val) const }
-\label{classeEF_c71faf4b2d153efda14bf1f87dca1507}
+\hypertarget{classeEF_cff03a658aec11b806c3e3d48f37b81f}{
+virtual vec \hyperlink{classeEF_cff03a658aec11b806c3e3d48f37b81f}{evallog} (const mat \&Val) const }
+\label{classeEF_cff03a658aec11b806c3e3d48f37b81f}
 
 \begin{CompactList}\small\item\em Evaluate normalized log-probability for many samples. \item\end{CompactList}\item 
@@ -70 +70 @@
 
 \begin{CompactList}\small\item\em Returns N samples from density $epdf(rv)$. \item\end{CompactList}\item 
-\hypertarget{classepdf_cebbdd7a85e6328f7358fc0ba8eee06c}{
-virtual vec \hyperlink{classepdf_cebbdd7a85e6328f7358fc0ba8eee06c}{evalpdflog\_\-m} (const mat \&Val) const }
-\label{classepdf_cebbdd7a85e6328f7358fc0ba8eee06c}
+\hypertarget{classepdf_2495a04bbacb9b55fe5a3a59b78affca}{
+virtual vec \hyperlink{classepdf_2495a04bbacb9b55fe5a3a59b78affca}{evallog\_\-m} (const mat \&Val) const }
+\label{classepdf_2495a04bbacb9b55fe5a3a59b78affca}
 
 \begin{CompactList}\small\item\em Compute log-probability of multiple values argument {\tt val}. \item\end{CompactList}\item 

doc/latex/classeEmp.tex

@@ -75 +75 @@
 
 \begin{CompactList}\small\item\em inherited operation : NOT implemneted \item\end{CompactList}\item 
-\hypertarget{classeEmp_23e7358995400865ad2e278945922fb3}{
-double \hyperlink{classeEmp_23e7358995400865ad2e278945922fb3}{evalpdflog} (const vec \&val) const }
-\label{classeEmp_23e7358995400865ad2e278945922fb3}
+\hypertarget{classeEmp_884f16c9fc1f888408686a660a95dacd}{
+double \hyperlink{classeEmp_884f16c9fc1f888408686a660a95dacd}{evallog} (const vec \&val) const }
+\label{classeEmp_884f16c9fc1f888408686a660a95dacd}
 
 \begin{CompactList}\small\item\em inherited operation : NOT implemneted \item\end{CompactList}\item 
@@ -90 +90 @@
 
 \begin{CompactList}\small\item\em Returns N samples from density $epdf(rv)$. \item\end{CompactList}\item 
-\hypertarget{classepdf_cebbdd7a85e6328f7358fc0ba8eee06c}{
-virtual vec \hyperlink{classepdf_cebbdd7a85e6328f7358fc0ba8eee06c}{evalpdflog\_\-m} (const mat \&Val) const }
-\label{classepdf_cebbdd7a85e6328f7358fc0ba8eee06c}
+\hypertarget{classepdf_2495a04bbacb9b55fe5a3a59b78affca}{
+virtual vec \hyperlink{classepdf_2495a04bbacb9b55fe5a3a59b78affca}{evallog\_\-m} (const mat \&Val) const }
+\label{classepdf_2495a04bbacb9b55fe5a3a59b78affca}
 
 \begin{CompactList}\small\item\em Compute log-probability of multiple values argument {\tt val}. \item\end{CompactList}\item 

doc/latex/classegamma.tex

@@ -40 +40 @@
 
 \begin{CompactList}\small\item\em Returns a sample, $x$ from density $epdf(rv)$. \item\end{CompactList}\item 
-\hypertarget{classegamma_de84faac8f9799dfe2777ddbedf997ef}{
-double \hyperlink{classegamma_de84faac8f9799dfe2777ddbedf997ef}{evalpdflog} (const vec \&val) const }
-\label{classegamma_de84faac8f9799dfe2777ddbedf997ef}
+\hypertarget{classegamma_74a49a4c696f44e54bb6b0515e155a9b}{
+double \hyperlink{classegamma_74a49a4c696f44e54bb6b0515e155a9b}{evallog} (const vec \&val) const }
+\label{classegamma_74a49a4c696f44e54bb6b0515e155a9b}
 
 \begin{CompactList}\small\item\em TODO: is it used anywhere? \item\end{CompactList}\item 
@@ -65 +65 @@
 
 \begin{CompactList}\small\item\em TODO decide if it is really needed. \item\end{CompactList}\item 
-\hypertarget{classeEF_48cdd33d0e20d1a1aa45683c956bc61c}{
-virtual double \hyperlink{classeEF_48cdd33d0e20d1a1aa45683c956bc61c}{evalpdflog\_\-nn} (const vec \&val) const }
-\label{classeEF_48cdd33d0e20d1a1aa45683c956bc61c}
+\hypertarget{classeEF_41c70565b4d3fb424599817d008f0c71}{
+virtual double \hyperlink{classeEF_41c70565b4d3fb424599817d008f0c71}{evallog\_\-nn} (const vec \&val) const }
+\label{classeEF_41c70565b4d3fb424599817d008f0c71}
 
 \begin{CompactList}\small\item\em Evaluate normalized log-probability. \item\end{CompactList}\item 
-\hypertarget{classeEF_c71faf4b2d153efda14bf1f87dca1507}{
-virtual vec \hyperlink{classeEF_c71faf4b2d153efda14bf1f87dca1507}{evalpdflog} (const mat \&Val) const }
-\label{classeEF_c71faf4b2d153efda14bf1f87dca1507}
+\hypertarget{classeEF_cff03a658aec11b806c3e3d48f37b81f}{
+virtual vec \hyperlink{classeEF_cff03a658aec11b806c3e3d48f37b81f}{evallog} (const mat \&Val) const }
+\label{classeEF_cff03a658aec11b806c3e3d48f37b81f}
 
 \begin{CompactList}\small\item\em Evaluate normalized log-probability for many samples. \item\end{CompactList}\item 
@@ -85 +85 @@
 
 \begin{CompactList}\small\item\em Returns N samples from density $epdf(rv)$. \item\end{CompactList}\item 
-\hypertarget{classepdf_cebbdd7a85e6328f7358fc0ba8eee06c}{
-virtual vec \hyperlink{classepdf_cebbdd7a85e6328f7358fc0ba8eee06c}{evalpdflog\_\-m} (const mat \&Val) const }
-\label{classepdf_cebbdd7a85e6328f7358fc0ba8eee06c}
+\hypertarget{classepdf_2495a04bbacb9b55fe5a3a59b78affca}{
+virtual vec \hyperlink{classepdf_2495a04bbacb9b55fe5a3a59b78affca}{evallog\_\-m} (const mat \&Val) const }
+\label{classepdf_2495a04bbacb9b55fe5a3a59b78affca}
 
 \begin{CompactList}\small\item\em Compute log-probability of multiple values argument {\tt val}. \item\end{CompactList}\item 

doc/latex/classegiw.tex

@@ -50 +50 @@
 
 \item 
-\hypertarget{classegiw_2ab1e525d692be8272a6f383d60b94cd}{
-double \hyperlink{classegiw_2ab1e525d692be8272a6f383d60b94cd}{evalpdflog\_\-nn} (const vec \&val) const }
-\label{classegiw_2ab1e525d692be8272a6f383d60b94cd}
+\hypertarget{classegiw_2d94daac10d66bb743e4ddc8c1ba7268}{
+double \hyperlink{classegiw_2d94daac10d66bb743e4ddc8c1ba7268}{evallog\_\-nn} (const vec \&val) const }
+\label{classegiw_2d94daac10d66bb743e4ddc8c1ba7268}
 
 \begin{CompactList}\small\item\em In this instance, val= \mbox{[}theta, r\mbox{]}. For multivariate instances, it is stored columnwise val = \mbox{[}theta\_\-1 theta\_\-2 ... r\_\-1 r\_\-2 \mbox{]}. \item\end{CompactList}\item 
@@ -90 +90 @@
 
 \begin{CompactList}\small\item\em TODO decide if it is really needed. \item\end{CompactList}\item 
-\hypertarget{classeEF_6466e8d4aa9dd64698ed288cbb1afc03}{
-virtual double \hyperlink{classeEF_6466e8d4aa9dd64698ed288cbb1afc03}{evalpdflog} (const vec \&val) const }
-\label{classeEF_6466e8d4aa9dd64698ed288cbb1afc03}
+\hypertarget{classeEF_357512dd565e199904d367294b7dd862}{
+virtual double \hyperlink{classeEF_357512dd565e199904d367294b7dd862}{evallog} (const vec \&val) const }
+\label{classeEF_357512dd565e199904d367294b7dd862}
 
 \begin{CompactList}\small\item\em Evaluate normalized log-probability. \item\end{CompactList}\item 
-\hypertarget{classeEF_c71faf4b2d153efda14bf1f87dca1507}{
-virtual vec \hyperlink{classeEF_c71faf4b2d153efda14bf1f87dca1507}{evalpdflog} (const mat \&Val) const }
-\label{classeEF_c71faf4b2d153efda14bf1f87dca1507}
+\hypertarget{classeEF_cff03a658aec11b806c3e3d48f37b81f}{
+virtual vec \hyperlink{classeEF_cff03a658aec11b806c3e3d48f37b81f}{evallog} (const mat \&Val) const }
+\label{classeEF_cff03a658aec11b806c3e3d48f37b81f}
 
 \begin{CompactList}\small\item\em Evaluate normalized log-probability for many samples. \item\end{CompactList}\item 
@@ -105 +105 @@
 
 \begin{CompactList}\small\item\em Returns N samples from density $epdf(rv)$. \item\end{CompactList}\item 
-\hypertarget{classepdf_cebbdd7a85e6328f7358fc0ba8eee06c}{
-virtual vec \hyperlink{classepdf_cebbdd7a85e6328f7358fc0ba8eee06c}{evalpdflog\_\-m} (const mat \&Val) const }
-\label{classepdf_cebbdd7a85e6328f7358fc0ba8eee06c}
+\hypertarget{classepdf_2495a04bbacb9b55fe5a3a59b78affca}{
+virtual vec \hyperlink{classepdf_2495a04bbacb9b55fe5a3a59b78affca}{evallog\_\-m} (const mat \&Val) const }
+\label{classepdf_2495a04bbacb9b55fe5a3a59b78affca}
 
 \begin{CompactList}\small\item\em Compute log-probability of multiple values argument {\tt val}. \item\end{CompactList}\item 

doc/latex/classemix.tex

@@ -42 +42 @@
 
 \begin{CompactList}\small\item\em return expected value \item\end{CompactList}\item 
-\hypertarget{classemix_469e910479b3402589104ef3bb1b5741}{
-double \hyperlink{classemix_469e910479b3402589104ef3bb1b5741}{evalpdflog} (const vec \&val) const }
-\label{classemix_469e910479b3402589104ef3bb1b5741}
+\hypertarget{classemix_82691a72b583dab957cbd60d9283e47a}{
+double \hyperlink{classemix_82691a72b583dab957cbd60d9283e47a}{evallog} (const vec \&val) const }
+\label{classemix_82691a72b583dab957cbd60d9283e47a}
 
 \begin{CompactList}\small\item\em Compute log-probability of argument {\tt val}. \item\end{CompactList}\item 
-\hypertarget{classemix_375bfba7c79915c88c2e612bcf83dacb}{
-vec \hyperlink{classemix_375bfba7c79915c88c2e612bcf83dacb}{evalpdflog\_\-m} (const mat \&Val) const }
-\label{classemix_375bfba7c79915c88c2e612bcf83dacb}
+\hypertarget{classemix_b3eb9e153e8bfdb6bb47adecc278cbca}{
+vec \hyperlink{classemix_b3eb9e153e8bfdb6bb47adecc278cbca}{evallog\_\-m} (const mat \&Val) const }
+\label{classemix_b3eb9e153e8bfdb6bb47adecc278cbca}
 
 \begin{CompactList}\small\item\em Compute log-probability of multiple values argument {\tt val}. \item\end{CompactList}\item 
-\hypertarget{classemix_07b5638de45d1fe83eb4da37594fcc68}{
-mat \textbf{evalpdflog\_\-M} (const mat \&Val) const }
-\label{classemix_07b5638de45d1fe83eb4da37594fcc68}
+\hypertarget{classemix_44ae2b86c650c2ccb967969c1859d268}{
+mat \hyperlink{classemix_44ae2b86c650c2ccb967969c1859d268}{evallog\_\-M} (const mat \&Val) const }
+\label{classemix_44ae2b86c650c2ccb967969c1859d268}
 
-\item 
+\begin{CompactList}\small\item\em Auxiliary function that returns pdflog for each component. \item\end{CompactList}\item 
 \hypertarget{classemix_33afde698093d458ce71875f7ee7384a}{
 \hyperlink{classemix}{emix} $\ast$ \hyperlink{classemix_33afde698093d458ce71875f7ee7384a}{marginal} (const \hyperlink{classRV}{RV} \&\hyperlink{classepdf_74da992e3f5d598da8850b646b79b9d9}{rv}) const }

doc/latex/classenorm.tex

@@ -50 +50 @@
 
 \begin{CompactList}\small\item\em TODO is it used? \item\end{CompactList}\item 
-\hypertarget{classenorm_b9e1dfd33692d7b3f1a59f17b0e61bd0}{
-double \textbf{eval} (const vec \&val) const }
-\label{classenorm_b9e1dfd33692d7b3f1a59f17b0e61bd0}
-
-\item 
-\hypertarget{classenorm_c1e3dcba256b0153cfdb286120e110be}{
-double \hyperlink{classenorm_c1e3dcba256b0153cfdb286120e110be}{evalpdflog\_\-nn} (const vec \&val) const }
-\label{classenorm_c1e3dcba256b0153cfdb286120e110be}
+\hypertarget{classenorm_50cb0a083d97a7adbbd97c92e712c46c}{
+double \hyperlink{classenorm_50cb0a083d97a7adbbd97c92e712c46c}{evallog\_\-nn} (const vec \&val) const }
+\label{classenorm_50cb0a083d97a7adbbd97c92e712c46c}
 
 \begin{CompactList}\small\item\em Evaluate normalized log-probability. \item\end{CompactList}\item 
@@ -95 +90 @@
 
 \begin{CompactList}\small\item\em returns pointers to the internal variance and its inverse. Use with Care! \item\end{CompactList}\item 
+\hypertarget{classenorm_d01385983048ece700b426549bbaee56}{
+const sq\_\-T \& \textbf{\_\-R} () const }
+\label{classenorm_d01385983048ece700b426549bbaee56}
+
+\item 
 \hypertarget{classeEF_a89bef8996410609004fa019b5b48964}{
 virtual void \hyperlink{classeEF_a89bef8996410609004fa019b5b48964}{dupdate} (mat \&v)}
@@ -100 +100 @@
 
 \begin{CompactList}\small\item\em TODO decide if it is really needed. \item\end{CompactList}\item 
-\hypertarget{classeEF_6466e8d4aa9dd64698ed288cbb1afc03}{
-virtual double \hyperlink{classeEF_6466e8d4aa9dd64698ed288cbb1afc03}{evalpdflog} (const vec \&val) const }
-\label{classeEF_6466e8d4aa9dd64698ed288cbb1afc03}
+\hypertarget{classeEF_357512dd565e199904d367294b7dd862}{
+virtual double \hyperlink{classeEF_357512dd565e199904d367294b7dd862}{evallog} (const vec \&val) const }
+\label{classeEF_357512dd565e199904d367294b7dd862}
 
 \begin{CompactList}\small\item\em Evaluate normalized log-probability. \item\end{CompactList}\item 
-\hypertarget{classeEF_c71faf4b2d153efda14bf1f87dca1507}{
-virtual vec \hyperlink{classeEF_c71faf4b2d153efda14bf1f87dca1507}{evalpdflog} (const mat \&Val) const }
-\label{classeEF_c71faf4b2d153efda14bf1f87dca1507}
+\hypertarget{classeEF_cff03a658aec11b806c3e3d48f37b81f}{
+virtual vec \hyperlink{classeEF_cff03a658aec11b806c3e3d48f37b81f}{evallog} (const mat \&Val) const }
+\label{classeEF_cff03a658aec11b806c3e3d48f37b81f}
 
 \begin{CompactList}\small\item\em Evaluate normalized log-probability for many samples. \item\end{CompactList}\item 
@@ -120 +120 @@
 
 \begin{CompactList}\small\item\em Returns N samples from density $epdf(rv)$. \item\end{CompactList}\item 
-\hypertarget{classepdf_cebbdd7a85e6328f7358fc0ba8eee06c}{
-virtual vec \hyperlink{classepdf_cebbdd7a85e6328f7358fc0ba8eee06c}{evalpdflog\_\-m} (const mat \&Val) const }
-\label{classepdf_cebbdd7a85e6328f7358fc0ba8eee06c}
+\hypertarget{classepdf_2495a04bbacb9b55fe5a3a59b78affca}{
+virtual vec \hyperlink{classepdf_2495a04bbacb9b55fe5a3a59b78affca}{evallog\_\-m} (const mat \&Val) const }
+\label{classepdf_2495a04bbacb9b55fe5a3a59b78affca}
 
 \begin{CompactList}\small\item\em Compute log-probability of multiple values argument {\tt val}. \item\end{CompactList}\item 

doc/latex/classepdf.tex

@@ -45 +45 @@
 
 \begin{CompactList}\small\item\em Returns N samples from density $epdf(rv)$. \item\end{CompactList}\item 
-\hypertarget{classepdf_6aef3eca74899692503769c18add1a4c}{
-virtual double \hyperlink{classepdf_6aef3eca74899692503769c18add1a4c}{evalpdflog} (const vec \&val) const =0}
-\label{classepdf_6aef3eca74899692503769c18add1a4c}
+\hypertarget{classepdf_e1996af1da1fa1214270066a96ca113e}{
+virtual double \hyperlink{classepdf_e1996af1da1fa1214270066a96ca113e}{evallog} (const vec \&val) const =0}
+\label{classepdf_e1996af1da1fa1214270066a96ca113e}
 
 \begin{CompactList}\small\item\em Compute log-probability of argument {\tt val}. \item\end{CompactList}\item 
-\hypertarget{classepdf_cebbdd7a85e6328f7358fc0ba8eee06c}{
-virtual vec \hyperlink{classepdf_cebbdd7a85e6328f7358fc0ba8eee06c}{evalpdflog\_\-m} (const mat \&Val) const }
-\label{classepdf_cebbdd7a85e6328f7358fc0ba8eee06c}
+\hypertarget{classepdf_2495a04bbacb9b55fe5a3a59b78affca}{
+virtual vec \hyperlink{classepdf_2495a04bbacb9b55fe5a3a59b78affca}{evallog\_\-m} (const mat \&Val) const }
+\label{classepdf_2495a04bbacb9b55fe5a3a59b78affca}
 
 \begin{CompactList}\small\item\em Compute log-probability of multiple values argument {\tt val}. \item\end{CompactList}\item 

doc/latex/classeprod.tex

@@ -40 +40 @@
 
 \begin{CompactList}\small\item\em Returns a sample, $x$ from density $epdf(rv)$. \item\end{CompactList}\item 
-\hypertarget{classeprod_5adef154e3655a872c284b02635b8b35}{
-double \hyperlink{classeprod_5adef154e3655a872c284b02635b8b35}{evalpdflog} (const vec \&val) const }
-\label{classeprod_5adef154e3655a872c284b02635b8b35}
+\hypertarget{classeprod_0af49e491414d6f270dc347bcb054eb6}{
+double \hyperlink{classeprod_0af49e491414d6f270dc347bcb054eb6}{evallog} (const vec \&val) const }
+\label{classeprod_0af49e491414d6f270dc347bcb054eb6}
 
 \begin{CompactList}\small\item\em Compute log-probability of argument {\tt val}. \item\end{CompactList}\item 
@@ -60 +60 @@
 
 \begin{CompactList}\small\item\em Returns N samples from density $epdf(rv)$. \item\end{CompactList}\item 
-\hypertarget{classepdf_cebbdd7a85e6328f7358fc0ba8eee06c}{
-virtual vec \hyperlink{classepdf_cebbdd7a85e6328f7358fc0ba8eee06c}{evalpdflog\_\-m} (const mat \&Val) const }
-\label{classepdf_cebbdd7a85e6328f7358fc0ba8eee06c}
+\hypertarget{classepdf_2495a04bbacb9b55fe5a3a59b78affca}{
+virtual vec \hyperlink{classepdf_2495a04bbacb9b55fe5a3a59b78affca}{evallog\_\-m} (const mat \&Val) const }
+\label{classepdf_2495a04bbacb9b55fe5a3a59b78affca}
 
 \begin{CompactList}\small\item\em Compute log-probability of multiple values argument {\tt val}. \item\end{CompactList}\item 

doc/latex/classeuni.tex

@@ -35 +35 @@
 
 \item 
-\hypertarget{classeuni_06af95d514a6623ad4688bd2ad50ad71}{
-double \hyperlink{classeuni_06af95d514a6623ad4688bd2ad50ad71}{evalpdflog} (const vec \&val) const }
-\label{classeuni_06af95d514a6623ad4688bd2ad50ad71}
+\hypertarget{classeuni_357b36417ef4c9211d12e7a4a602fd6a}{
+double \hyperlink{classeuni_357b36417ef4c9211d12e7a4a602fd6a}{evallog} (const vec \&val) const }
+\label{classeuni_357b36417ef4c9211d12e7a4a602fd6a}
 
 \begin{CompactList}\small\item\em Compute log-probability of argument {\tt val}. \item\end{CompactList}\item 
@@ -60 +60 @@
 
 \begin{CompactList}\small\item\em Returns N samples from density $epdf(rv)$. \item\end{CompactList}\item 
-\hypertarget{classepdf_cebbdd7a85e6328f7358fc0ba8eee06c}{
-virtual vec \hyperlink{classepdf_cebbdd7a85e6328f7358fc0ba8eee06c}{evalpdflog\_\-m} (const mat \&Val) const }
-\label{classepdf_cebbdd7a85e6328f7358fc0ba8eee06c}
+\hypertarget{classepdf_2495a04bbacb9b55fe5a3a59b78affca}{
+virtual vec \hyperlink{classepdf_2495a04bbacb9b55fe5a3a59b78affca}{evallog\_\-m} (const mat \&Val) const }
+\label{classepdf_2495a04bbacb9b55fe5a3a59b78affca}
 
 \begin{CompactList}\small\item\em Compute log-probability of multiple values argument {\tt val}. \item\end{CompactList}\item 

doc/latex/classfsqmat.tex

@@ -246 +246 @@
 References M.
 
-Referenced by EKF$<$ sq\_\-T $>$::bayes(), and egiw::evalpdflog\_\-nn().\hypertarget{classfsqmat_842a774077ee34ac3c36d180ab33e103}{
+Referenced by EKF$<$ sq\_\-T $>$::bayes(), and egiw::evallog\_\-nn().\hypertarget{classfsqmat_842a774077ee34ac3c36d180ab33e103}{
 \index{fsqmat@{fsqmat}!sqrt\_\-mult@{sqrt\_\-mult}}
 \index{sqrt\_\-mult@{sqrt\_\-mult}!fsqmat@{fsqmat}}

doc/latex/classldmat.tex

@@ -96 +96 @@
 
 \begin{CompactList}\small\item\em Clearing matrix so that it corresponds to zeros. \item\end{CompactList}\item 
-\hypertarget{classldmat_0fceb6b5b637cec89bb0a3d2e6be1306}{
-int \hyperlink{classldmat_0fceb6b5b637cec89bb0a3d2e6be1306}{cols} () const }
-\label{classldmat_0fceb6b5b637cec89bb0a3d2e6be1306}
+\hypertarget{group__math_g0fceb6b5b637cec89bb0a3d2e6be1306}{
+int \hyperlink{group__math_g0fceb6b5b637cec89bb0a3d2e6be1306}{cols} () const }
+\label{group__math_g0fceb6b5b637cec89bb0a3d2e6be1306}
 
 \begin{CompactList}\small\item\em access function \item\end{CompactList}\item 
-\hypertarget{classldmat_96dfb21865db4f5bd36fa70f9b0b1163}{
-int \hyperlink{classldmat_96dfb21865db4f5bd36fa70f9b0b1163}{rows} () const }
-\label{classldmat_96dfb21865db4f5bd36fa70f9b0b1163}
+\hypertarget{group__math_g96dfb21865db4f5bd36fa70f9b0b1163}{
+int \hyperlink{group__math_g96dfb21865db4f5bd36fa70f9b0b1163}{rows} () const }
+\label{group__math_g96dfb21865db4f5bd36fa70f9b0b1163}
 
 \begin{CompactList}\small\item\em access function \item\end{CompactList}\item 
@@ -141 +141 @@
 
 \begin{CompactList}\small\item\em Access functions. \item\end{CompactList}\item 
-\hyperlink{classldmat}{ldmat} \& \hyperlink{classldmat_ca445ee152a56043af946ea095b2d8f8}{operator+=} (const \hyperlink{classldmat}{ldmat} \&ldA)
+\hyperlink{classldmat}{ldmat} \& \hyperlink{group__math_gca445ee152a56043af946ea095b2d8f8}{operator+=} (const \hyperlink{classldmat}{ldmat} \&ldA)
 \begin{CompactList}\small\item\em add another \hyperlink{classldmat}{ldmat} matrix \item\end{CompactList}\item 
-\hyperlink{classldmat}{ldmat} \& \hyperlink{classldmat_e3f4d2d85ab1ba384c852329aa31d0fb}{operator-=} (const \hyperlink{classldmat}{ldmat} \&ldA)
+\hyperlink{classldmat}{ldmat} \& \hyperlink{group__math_ge3f4d2d85ab1ba384c852329aa31d0fb}{operator-=} (const \hyperlink{classldmat}{ldmat} \&ldA)
 \begin{CompactList}\small\item\em subtract another \hyperlink{classldmat}{ldmat} matrix \item\end{CompactList}\item 
 \hypertarget{classldmat_875b7e6dcf73ae7001329099019fdb1d}{
@@ -195 +195 @@
 Implements \hyperlink{classsqmat_b223484796661f2dadb5607a86ce0581}{sqmat}.
 
-References D, sqmat::dim, and L.
+References D, sqmat::dim, dydr(), and L.
 
 Referenced by add(), ARX::bayes(), and ARX::logpred().\hypertarget{classldmat_e967b9425007f0cb6cd59b845f9756d8}{
@@ -262 +262 @@
 
 
-References clear(), D, L, and ldform().\hypertarget{classldmat_e7207748909325bb0f99b43f090a2b7e}{
+References clear(), D, L, ldform(), and ltuinv().\hypertarget{classldmat_e7207748909325bb0f99b43f090a2b7e}{
 \index{ldmat@{ldmat}!mult\_\-sym@{mult\_\-sym}}
 \index{mult\_\-sym@{mult\_\-sym}!ldmat@{ldmat}}
@@ -312 +312 @@
 References D, sqmat::dim, and L.
 
-Referenced by inv(), ldmat(), mult\_\-sym(), and mult\_\-sym\_\-t().\hypertarget{classldmat_ca445ee152a56043af946ea095b2d8f8}{
-\index{ldmat@{ldmat}!operator+=@{operator+=}}
-\index{operator+=@{operator+=}!ldmat@{ldmat}}
-\subsubsection[operator+=]{\setlength{\rightskip}{0pt plus 5cm}{\bf ldmat} \& ldmat::operator+= (const {\bf ldmat} \& {\em ldA})\hspace{0.3cm}{\tt  \mbox{[}inline\mbox{]}}}}
-\label{classldmat_ca445ee152a56043af946ea095b2d8f8}
-
-
-add another \hyperlink{classldmat}{ldmat} matrix 
-
-Operations: mapping of add operation to operators \hypertarget{classldmat_e3f4d2d85ab1ba384c852329aa31d0fb}{
-\index{ldmat@{ldmat}!operator-=@{operator-=}}
-\index{operator-=@{operator-=}!ldmat@{ldmat}}
-\subsubsection[operator-=]{\setlength{\rightskip}{0pt plus 5cm}{\bf ldmat} \& ldmat::operator-= (const {\bf ldmat} \& {\em ldA})\hspace{0.3cm}{\tt  \mbox{[}inline\mbox{]}}}}
-\label{classldmat_e3f4d2d85ab1ba384c852329aa31d0fb}
-
-
-subtract another \hyperlink{classldmat}{ldmat} matrix 
-
-mapping of negative add operation to operators 
+Referenced by inv(), ldmat(), mult\_\-sym(), and mult\_\-sym\_\-t().
 
 The documentation for this class was generated from the following files:\begin{CompactItemize}

doc/latex/classmEF.tex

@@ -32 +32 @@
 virtual vec \hyperlink{classmpdf_3f172b79ec4a5ebc87898a5381141f1b}{samplecond} (const vec \&cond, double \&ll)
 \begin{CompactList}\small\item\em Returns the required moment of the \hyperlink{classepdf}{epdf}. \item\end{CompactList}\item 
-virtual mat \hyperlink{classmpdf_0e37163660f93df2a4d723cedb1da89c}{samplecond} (const vec \&cond, vec \&ll, int N)
+virtual mat \hyperlink{classmpdf_b1dae6171ee39a6a05976c7b1007a3c5}{samplecond\_\-m} (const vec \&cond, vec \&ll, int N)
 \begin{CompactList}\small\item\em Returns. \item\end{CompactList}\item 
 \hypertarget{classmpdf_0f95a0cc6ab40611f46804682446ed83}{
@@ -39 +39 @@
 
 \begin{CompactList}\small\item\em Update {\tt ep} so that it represents this \hyperlink{classmpdf}{mpdf} conditioned on {\tt rvc} = cond. \item\end{CompactList}\item 
-\hypertarget{classmpdf_80b738ece5bd4f8c4edaee4b38906f91}{
-virtual double \hyperlink{classmpdf_80b738ece5bd4f8c4edaee4b38906f91}{evalcond} (const vec \&dt, const vec \&cond)}
-\label{classmpdf_80b738ece5bd4f8c4edaee4b38906f91}
+\hypertarget{classmpdf_2ef8a6374029d990a678782f6decebbe}{
+virtual double \hyperlink{classmpdf_2ef8a6374029d990a678782f6decebbe}{evallogcond} (const vec \&dt, const vec \&cond)}
+\label{classmpdf_2ef8a6374029d990a678782f6decebbe}
 
 \begin{CompactList}\small\item\em Shortcut for conditioning and evaluation of the internal \hyperlink{classepdf}{epdf}. In some cases, this operation can be implemented efficiently. \item\end{CompactList}\item 
-\hypertarget{classmpdf_b7b2da35080cd15f1be365b805e7277e}{
-virtual vec \textbf{evalcond\_\-m} (const mat \&Dt, const vec \&cond)}
-\label{classmpdf_b7b2da35080cd15f1be365b805e7277e}
+\hypertarget{classmpdf_95fcff214848f66f1b489459370573fa}{
+virtual vec \hyperlink{classmpdf_95fcff214848f66f1b489459370573fa}{evallogcond\_\-m} (const mat \&Dt, const vec \&cond)}
+\label{classmpdf_95fcff214848f66f1b489459370573fa}
 
-\item 
+\begin{CompactList}\small\item\em Matrix version of evallogcond. \item\end{CompactList}\item 
 \hypertarget{classmpdf_15ef062183b1ccdf794732d5fa0b77cd}{
 \hyperlink{classRV}{RV} \hyperlink{classmpdf_15ef062183b1ccdf794732d5fa0b77cd}{\_\-rvc} () const }
@@ -108 +108 @@
 Reimplemented in \hyperlink{classmprod_a48887eb8738a9e5550bfc38eb8e9d68}{mprod}.
 
-References mpdf::condition(), mpdf::ep, epdf::evalpdflog(), and epdf::sample().
+References mpdf::condition(), mpdf::ep, epdf::evallog(), and epdf::sample().
 
-Referenced by MPF$<$ BM\_\-T $>$::bayes(), and PF::bayes().\hypertarget{classmpdf_0e37163660f93df2a4d723cedb1da89c}{
-\index{mEF@{mEF}!samplecond@{samplecond}}
-\index{samplecond@{samplecond}!mEF@{mEF}}
-\subsubsection[samplecond]{\setlength{\rightskip}{0pt plus 5cm}virtual mat mpdf::samplecond (const vec \& {\em cond}, \/  vec \& {\em ll}, \/  int {\em N})\hspace{0.3cm}{\tt  \mbox{[}inline, virtual, inherited\mbox{]}}}}
-\label{classmpdf_0e37163660f93df2a4d723cedb1da89c}
+Referenced by MPF$<$ BM\_\-T $>$::bayes(), and PF::bayes().\hypertarget{classmpdf_b1dae6171ee39a6a05976c7b1007a3c5}{
+\index{mEF@{mEF}!samplecond\_\-m@{samplecond\_\-m}}
+\index{samplecond\_\-m@{samplecond\_\-m}!mEF@{mEF}}
+\subsubsection[samplecond\_\-m]{\setlength{\rightskip}{0pt plus 5cm}virtual mat mpdf::samplecond\_\-m (const vec \& {\em cond}, \/  vec \& {\em ll}, \/  int {\em N})\hspace{0.3cm}{\tt  \mbox{[}inline, virtual, inherited\mbox{]}}}}
+\label{classmpdf_b1dae6171ee39a6a05976c7b1007a3c5}
 
 
@@ -126 +126 @@
 
 
-Reimplemented in \hyperlink{classmprod_e171c40e210539c2af01d6237785620b}{mprod}.
-
-References mpdf::condition(), RV::count(), mpdf::ep, epdf::evalpdflog(), mpdf::rv, and epdf::sample().
+References mpdf::condition(), RV::count(), mpdf::ep, epdf::evallog(), mpdf::rv, and epdf::sample().
 
 The documentation for this class was generated from the following file:\begin{CompactItemize}

doc/latex/classmepdf.tex

@@ -37 +37 @@
 virtual vec \hyperlink{classmpdf_3f172b79ec4a5ebc87898a5381141f1b}{samplecond} (const vec \&cond, double \&ll)
 \begin{CompactList}\small\item\em Returns the required moment of the \hyperlink{classepdf}{epdf}. \item\end{CompactList}\item 
-virtual mat \hyperlink{classmpdf_0e37163660f93df2a4d723cedb1da89c}{samplecond} (const vec \&cond, vec \&ll, int N)
+virtual mat \hyperlink{classmpdf_b1dae6171ee39a6a05976c7b1007a3c5}{samplecond\_\-m} (const vec \&cond, vec \&ll, int N)
 \begin{CompactList}\small\item\em Returns. \item\end{CompactList}\item 
-\hypertarget{classmpdf_80b738ece5bd4f8c4edaee4b38906f91}{
-virtual double \hyperlink{classmpdf_80b738ece5bd4f8c4edaee4b38906f91}{evalcond} (const vec \&dt, const vec \&cond)}
-\label{classmpdf_80b738ece5bd4f8c4edaee4b38906f91}
+\hypertarget{classmpdf_2ef8a6374029d990a678782f6decebbe}{
+virtual double \hyperlink{classmpdf_2ef8a6374029d990a678782f6decebbe}{evallogcond} (const vec \&dt, const vec \&cond)}
+\label{classmpdf_2ef8a6374029d990a678782f6decebbe}
 
 \begin{CompactList}\small\item\em Shortcut for conditioning and evaluation of the internal \hyperlink{classepdf}{epdf}. In some cases, this operation can be implemented efficiently. \item\end{CompactList}\item 
-\hypertarget{classmpdf_b7b2da35080cd15f1be365b805e7277e}{
-virtual vec \textbf{evalcond\_\-m} (const mat \&Dt, const vec \&cond)}
-\label{classmpdf_b7b2da35080cd15f1be365b805e7277e}
+\hypertarget{classmpdf_95fcff214848f66f1b489459370573fa}{
+virtual vec \hyperlink{classmpdf_95fcff214848f66f1b489459370573fa}{evallogcond\_\-m} (const mat \&Dt, const vec \&cond)}
+\label{classmpdf_95fcff214848f66f1b489459370573fa}
 
-\item 
+\begin{CompactList}\small\item\em Matrix version of evallogcond. \item\end{CompactList}\item 
 \hypertarget{classmpdf_15ef062183b1ccdf794732d5fa0b77cd}{
 \hyperlink{classRV}{RV} \hyperlink{classmpdf_15ef062183b1ccdf794732d5fa0b77cd}{\_\-rvc} () const }
@@ -108 +108 @@
 Reimplemented in \hyperlink{classmprod_a48887eb8738a9e5550bfc38eb8e9d68}{mprod}.
 
-References mpdf::condition(), mpdf::ep, epdf::evalpdflog(), and epdf::sample().
+References mpdf::condition(), mpdf::ep, epdf::evallog(), and epdf::sample().
 
-Referenced by MPF$<$ BM\_\-T $>$::bayes(), and PF::bayes().\hypertarget{classmpdf_0e37163660f93df2a4d723cedb1da89c}{
-\index{mepdf@{mepdf}!samplecond@{samplecond}}
-\index{samplecond@{samplecond}!mepdf@{mepdf}}
-\subsubsection[samplecond]{\setlength{\rightskip}{0pt plus 5cm}virtual mat mpdf::samplecond (const vec \& {\em cond}, \/  vec \& {\em ll}, \/  int {\em N})\hspace{0.3cm}{\tt  \mbox{[}inline, virtual, inherited\mbox{]}}}}
-\label{classmpdf_0e37163660f93df2a4d723cedb1da89c}
+Referenced by MPF$<$ BM\_\-T $>$::bayes(), and PF::bayes().\hypertarget{classmpdf_b1dae6171ee39a6a05976c7b1007a3c5}{
+\index{mepdf@{mepdf}!samplecond\_\-m@{samplecond\_\-m}}
+\index{samplecond\_\-m@{samplecond\_\-m}!mepdf@{mepdf}}
+\subsubsection[samplecond\_\-m]{\setlength{\rightskip}{0pt plus 5cm}virtual mat mpdf::samplecond\_\-m (const vec \& {\em cond}, \/  vec \& {\em ll}, \/  int {\em N})\hspace{0.3cm}{\tt  \mbox{[}inline, virtual, inherited\mbox{]}}}}
+\label{classmpdf_b1dae6171ee39a6a05976c7b1007a3c5}
 
 
@@ -126 +126 @@
 
 
-Reimplemented in \hyperlink{classmprod_e171c40e210539c2af01d6237785620b}{mprod}.
-
-References mpdf::condition(), RV::count(), mpdf::ep, epdf::evalpdflog(), mpdf::rv, and epdf::sample().
+References mpdf::condition(), RV::count(), mpdf::ep, epdf::evallog(), mpdf::rv, and epdf::sample().
 
 The documentation for this class was generated from the following file:\begin{CompactItemize}

doc/latex/classmerger.tex

@@ -57 +57 @@
 vec \hyperlink{classmerger_379198c3d2063bfa63f5d1245a2511ba}{sample} () const 
 \item 
-\hypertarget{classmerger_8c37688902b1a1e9fa32edc5709e5a00}{
-double \hyperlink{classmerger_8c37688902b1a1e9fa32edc5709e5a00}{evalpdflog} (const vec \&dt) const }
-\label{classmerger_8c37688902b1a1e9fa32edc5709e5a00}
+\hypertarget{classmerger_632cd7e0bcd149c0dc85042063364f6b}{
+double \hyperlink{classmerger_632cd7e0bcd149c0dc85042063364f6b}{evallog} (const vec \&dt) const }
+\label{classmerger_632cd7e0bcd149c0dc85042063364f6b}
 
 \begin{CompactList}\small\item\em Compute log-probability of argument {\tt val}. \item\end{CompactList}\item 
@@ -99 +99 @@
 
 \begin{CompactList}\small\item\em Returns N samples from density $epdf(rv)$. \item\end{CompactList}\item 
-\hypertarget{classepdf_cebbdd7a85e6328f7358fc0ba8eee06c}{
-virtual vec \hyperlink{classepdf_cebbdd7a85e6328f7358fc0ba8eee06c}{evalpdflog\_\-m} (const mat \&Val) const }
-\label{classepdf_cebbdd7a85e6328f7358fc0ba8eee06c}
+\hypertarget{classepdf_2495a04bbacb9b55fe5a3a59b78affca}{
+virtual vec \hyperlink{classepdf_2495a04bbacb9b55fe5a3a59b78affca}{evallog\_\-m} (const mat \&Val) const }
+\label{classepdf_2495a04bbacb9b55fe5a3a59b78affca}
 
 \begin{CompactList}\small\item\em Compute log-probability of multiple values argument {\tt val}. \item\end{CompactList}\item 

doc/latex/classmgamma.tex

@@ -42 +42 @@
 virtual vec \hyperlink{classmpdf_3f172b79ec4a5ebc87898a5381141f1b}{samplecond} (const vec \&cond, double \&ll)
 \begin{CompactList}\small\item\em Returns the required moment of the \hyperlink{classepdf}{epdf}. \item\end{CompactList}\item 
-virtual mat \hyperlink{classmpdf_0e37163660f93df2a4d723cedb1da89c}{samplecond} (const vec \&cond, vec \&ll, int N)
+virtual mat \hyperlink{classmpdf_b1dae6171ee39a6a05976c7b1007a3c5}{samplecond\_\-m} (const vec \&cond, vec \&ll, int N)
 \begin{CompactList}\small\item\em Returns. \item\end{CompactList}\item 
-\hypertarget{classmpdf_80b738ece5bd4f8c4edaee4b38906f91}{
-virtual double \hyperlink{classmpdf_80b738ece5bd4f8c4edaee4b38906f91}{evalcond} (const vec \&dt, const vec \&cond)}
-\label{classmpdf_80b738ece5bd4f8c4edaee4b38906f91}
+\hypertarget{classmpdf_2ef8a6374029d990a678782f6decebbe}{
+virtual double \hyperlink{classmpdf_2ef8a6374029d990a678782f6decebbe}{evallogcond} (const vec \&dt, const vec \&cond)}
+\label{classmpdf_2ef8a6374029d990a678782f6decebbe}
 
 \begin{CompactList}\small\item\em Shortcut for conditioning and evaluation of the internal \hyperlink{classepdf}{epdf}. In some cases, this operation can be implemented efficiently. \item\end{CompactList}\item 
-\hypertarget{classmpdf_b7b2da35080cd15f1be365b805e7277e}{
-virtual vec \textbf{evalcond\_\-m} (const mat \&Dt, const vec \&cond)}
-\label{classmpdf_b7b2da35080cd15f1be365b805e7277e}
+\hypertarget{classmpdf_95fcff214848f66f1b489459370573fa}{
+virtual vec \hyperlink{classmpdf_95fcff214848f66f1b489459370573fa}{evallogcond\_\-m} (const mat \&Dt, const vec \&cond)}
+\label{classmpdf_95fcff214848f66f1b489459370573fa}
 
-\item 
+\begin{CompactList}\small\item\em Matrix version of evallogcond. \item\end{CompactList}\item 
 \hypertarget{classmpdf_15ef062183b1ccdf794732d5fa0b77cd}{
 \hyperlink{classRV}{RV} \hyperlink{classmpdf_15ef062183b1ccdf794732d5fa0b77cd}{\_\-rvc} () const }
@@ -130 +130 @@
 Reimplemented in \hyperlink{classmprod_a48887eb8738a9e5550bfc38eb8e9d68}{mprod}.
 
-References mpdf::condition(), mpdf::ep, epdf::evalpdflog(), and epdf::sample().
+References mpdf::condition(), mpdf::ep, epdf::evallog(), and epdf::sample().
 
-Referenced by MPF$<$ BM\_\-T $>$::bayes(), and PF::bayes().\hypertarget{classmpdf_0e37163660f93df2a4d723cedb1da89c}{
-\index{mgamma@{mgamma}!samplecond@{samplecond}}
-\index{samplecond@{samplecond}!mgamma@{mgamma}}
-\subsubsection[samplecond]{\setlength{\rightskip}{0pt plus 5cm}virtual mat mpdf::samplecond (const vec \& {\em cond}, \/  vec \& {\em ll}, \/  int {\em N})\hspace{0.3cm}{\tt  \mbox{[}inline, virtual, inherited\mbox{]}}}}
-\label{classmpdf_0e37163660f93df2a4d723cedb1da89c}
+Referenced by MPF$<$ BM\_\-T $>$::bayes(), and PF::bayes().\hypertarget{classmpdf_b1dae6171ee39a6a05976c7b1007a3c5}{
+\index{mgamma@{mgamma}!samplecond\_\-m@{samplecond\_\-m}}
+\index{samplecond\_\-m@{samplecond\_\-m}!mgamma@{mgamma}}
+\subsubsection[samplecond\_\-m]{\setlength{\rightskip}{0pt plus 5cm}virtual mat mpdf::samplecond\_\-m (const vec \& {\em cond}, \/  vec \& {\em ll}, \/  int {\em N})\hspace{0.3cm}{\tt  \mbox{[}inline, virtual, inherited\mbox{]}}}}
+\label{classmpdf_b1dae6171ee39a6a05976c7b1007a3c5}
 
 
@@ -148 +148 @@
 
 
-Reimplemented in \hyperlink{classmprod_e171c40e210539c2af01d6237785620b}{mprod}.
-
-References mpdf::condition(), RV::count(), mpdf::ep, epdf::evalpdflog(), mpdf::rv, and epdf::sample().
+References mpdf::condition(), RV::count(), mpdf::ep, epdf::evallog(), mpdf::rv, and epdf::sample().
 
 The documentation for this class was generated from the following files:\begin{CompactItemize}

doc/latex/classmgamma__fix.tex

@@ -47 +47 @@
 virtual vec \hyperlink{classmpdf_3f172b79ec4a5ebc87898a5381141f1b}{samplecond} (const vec \&cond, double \&ll)
 \begin{CompactList}\small\item\em Returns the required moment of the \hyperlink{classepdf}{epdf}. \item\end{CompactList}\item 
-virtual mat \hyperlink{classmpdf_0e37163660f93df2a4d723cedb1da89c}{samplecond} (const vec \&cond, vec \&ll, int N)
+virtual mat \hyperlink{classmpdf_b1dae6171ee39a6a05976c7b1007a3c5}{samplecond\_\-m} (const vec \&cond, vec \&ll, int N)
 \begin{CompactList}\small\item\em Returns. \item\end{CompactList}\item 
-\hypertarget{classmpdf_80b738ece5bd4f8c4edaee4b38906f91}{
-virtual double \hyperlink{classmpdf_80b738ece5bd4f8c4edaee4b38906f91}{evalcond} (const vec \&dt, const vec \&cond)}
-\label{classmpdf_80b738ece5bd4f8c4edaee4b38906f91}
+\hypertarget{classmpdf_2ef8a6374029d990a678782f6decebbe}{
+virtual double \hyperlink{classmpdf_2ef8a6374029d990a678782f6decebbe}{evallogcond} (const vec \&dt, const vec \&cond)}
+\label{classmpdf_2ef8a6374029d990a678782f6decebbe}
 
 \begin{CompactList}\small\item\em Shortcut for conditioning and evaluation of the internal \hyperlink{classepdf}{epdf}. In some cases, this operation can be implemented efficiently. \item\end{CompactList}\item 
-\hypertarget{classmpdf_b7b2da35080cd15f1be365b805e7277e}{
-virtual vec \textbf{evalcond\_\-m} (const mat \&Dt, const vec \&cond)}
-\label{classmpdf_b7b2da35080cd15f1be365b805e7277e}
+\hypertarget{classmpdf_95fcff214848f66f1b489459370573fa}{
+virtual vec \hyperlink{classmpdf_95fcff214848f66f1b489459370573fa}{evallogcond\_\-m} (const mat \&Dt, const vec \&cond)}
+\label{classmpdf_95fcff214848f66f1b489459370573fa}
 
-\item 
+\begin{CompactList}\small\item\em Matrix version of evallogcond. \item\end{CompactList}\item 
 \hypertarget{classmpdf_15ef062183b1ccdf794732d5fa0b77cd}{
 \hyperlink{classRV}{RV} \hyperlink{classmpdf_15ef062183b1ccdf794732d5fa0b77cd}{\_\-rvc} () const }
@@ -147 +147 @@
 Reimplemented in \hyperlink{classmprod_a48887eb8738a9e5550bfc38eb8e9d68}{mprod}.
 
-References mpdf::condition(), mpdf::ep, epdf::evalpdflog(), and epdf::sample().
+References mpdf::condition(), mpdf::ep, epdf::evallog(), and epdf::sample().
 
-Referenced by MPF$<$ BM\_\-T $>$::bayes(), and PF::bayes().\hypertarget{classmpdf_0e37163660f93df2a4d723cedb1da89c}{
-\index{mgamma\_\-fix@{mgamma\_\-fix}!samplecond@{samplecond}}
-\index{samplecond@{samplecond}!mgamma_fix@{mgamma\_\-fix}}
-\subsubsection[samplecond]{\setlength{\rightskip}{0pt plus 5cm}virtual mat mpdf::samplecond (const vec \& {\em cond}, \/  vec \& {\em ll}, \/  int {\em N})\hspace{0.3cm}{\tt  \mbox{[}inline, virtual, inherited\mbox{]}}}}
-\label{classmpdf_0e37163660f93df2a4d723cedb1da89c}
+Referenced by MPF$<$ BM\_\-T $>$::bayes(), and PF::bayes().\hypertarget{classmpdf_b1dae6171ee39a6a05976c7b1007a3c5}{
+\index{mgamma\_\-fix@{mgamma\_\-fix}!samplecond\_\-m@{samplecond\_\-m}}
+\index{samplecond\_\-m@{samplecond\_\-m}!mgamma_fix@{mgamma\_\-fix}}
+\subsubsection[samplecond\_\-m]{\setlength{\rightskip}{0pt plus 5cm}virtual mat mpdf::samplecond\_\-m (const vec \& {\em cond}, \/  vec \& {\em ll}, \/  int {\em N})\hspace{0.3cm}{\tt  \mbox{[}inline, virtual, inherited\mbox{]}}}}
+\label{classmpdf_b1dae6171ee39a6a05976c7b1007a3c5}
 
 
@@ -165 +165 @@
 
 
-Reimplemented in \hyperlink{classmprod_e171c40e210539c2af01d6237785620b}{mprod}.
-
-References mpdf::condition(), RV::count(), mpdf::ep, epdf::evalpdflog(), mpdf::rv, and epdf::sample().
+References mpdf::condition(), RV::count(), mpdf::ep, epdf::evallog(), mpdf::rv, and epdf::sample().
 
 The documentation for this class was generated from the following file:\begin{CompactItemize}

doc/latex/classmlnorm.tex

@@ -57 +57 @@
 virtual vec \hyperlink{classmpdf_3f172b79ec4a5ebc87898a5381141f1b}{samplecond} (const vec \&cond, double \&ll)
 \begin{CompactList}\small\item\em Returns the required moment of the \hyperlink{classepdf}{epdf}. \item\end{CompactList}\item 
-virtual mat \hyperlink{classmpdf_0e37163660f93df2a4d723cedb1da89c}{samplecond} (const vec \&cond, vec \&ll, int N)
+virtual mat \hyperlink{classmpdf_b1dae6171ee39a6a05976c7b1007a3c5}{samplecond\_\-m} (const vec \&cond, vec \&ll, int N)
 \begin{CompactList}\small\item\em Returns. \item\end{CompactList}\item 
-\hypertarget{classmpdf_80b738ece5bd4f8c4edaee4b38906f91}{
-virtual double \hyperlink{classmpdf_80b738ece5bd4f8c4edaee4b38906f91}{evalcond} (const vec \&dt, const vec \&cond)}
-\label{classmpdf_80b738ece5bd4f8c4edaee4b38906f91}
+\hypertarget{classmpdf_2ef8a6374029d990a678782f6decebbe}{
+virtual double \hyperlink{classmpdf_2ef8a6374029d990a678782f6decebbe}{evallogcond} (const vec \&dt, const vec \&cond)}
+\label{classmpdf_2ef8a6374029d990a678782f6decebbe}
 
 \begin{CompactList}\small\item\em Shortcut for conditioning and evaluation of the internal \hyperlink{classepdf}{epdf}. In some cases, this operation can be implemented efficiently. \item\end{CompactList}\item 
-\hypertarget{classmpdf_b7b2da35080cd15f1be365b805e7277e}{
-virtual vec \textbf{evalcond\_\-m} (const mat \&Dt, const vec \&cond)}
-\label{classmpdf_b7b2da35080cd15f1be365b805e7277e}
+\hypertarget{classmpdf_95fcff214848f66f1b489459370573fa}{
+virtual vec \hyperlink{classmpdf_95fcff214848f66f1b489459370573fa}{evallogcond\_\-m} (const mat \&Dt, const vec \&cond)}
+\label{classmpdf_95fcff214848f66f1b489459370573fa}
 
-\item 
+\begin{CompactList}\small\item\em Matrix version of evallogcond. \item\end{CompactList}\item 
 \hypertarget{classmpdf_15ef062183b1ccdf794732d5fa0b77cd}{
 \hyperlink{classRV}{RV} \hyperlink{classmpdf_15ef062183b1ccdf794732d5fa0b77cd}{\_\-rvc} () const }
@@ -158 +158 @@
 Reimplemented in \hyperlink{classmprod_a48887eb8738a9e5550bfc38eb8e9d68}{mprod}.
 
-References mpdf::condition(), mpdf::ep, epdf::evalpdflog(), and epdf::sample().
+References mpdf::condition(), mpdf::ep, epdf::evallog(), and epdf::sample().
 
-Referenced by MPF$<$ BM\_\-T $>$::bayes(), and PF::bayes().\hypertarget{classmpdf_0e37163660f93df2a4d723cedb1da89c}{
-\index{mlnorm@{mlnorm}!samplecond@{samplecond}}
-\index{samplecond@{samplecond}!mlnorm@{mlnorm}}
-\subsubsection[samplecond]{\setlength{\rightskip}{0pt plus 5cm}virtual mat mpdf::samplecond (const vec \& {\em cond}, \/  vec \& {\em ll}, \/  int {\em N})\hspace{0.3cm}{\tt  \mbox{[}inline, virtual, inherited\mbox{]}}}}
-\label{classmpdf_0e37163660f93df2a4d723cedb1da89c}
+Referenced by MPF$<$ BM\_\-T $>$::bayes(), and PF::bayes().\hypertarget{classmpdf_b1dae6171ee39a6a05976c7b1007a3c5}{
+\index{mlnorm@{mlnorm}!samplecond\_\-m@{samplecond\_\-m}}
+\index{samplecond\_\-m@{samplecond\_\-m}!mlnorm@{mlnorm}}
+\subsubsection[samplecond\_\-m]{\setlength{\rightskip}{0pt plus 5cm}virtual mat mpdf::samplecond\_\-m (const vec \& {\em cond}, \/  vec \& {\em ll}, \/  int {\em N})\hspace{0.3cm}{\tt  \mbox{[}inline, virtual, inherited\mbox{]}}}}
+\label{classmpdf_b1dae6171ee39a6a05976c7b1007a3c5}
 
 
@@ -176 +176 @@
 
 
-Reimplemented in \hyperlink{classmprod_e171c40e210539c2af01d6237785620b}{mprod}.
-
-References mpdf::condition(), RV::count(), mpdf::ep, epdf::evalpdflog(), mpdf::rv, and epdf::sample().
+References mpdf::condition(), RV::count(), mpdf::ep, epdf::evallog(), mpdf::rv, and epdf::sample().
 
 The documentation for this class was generated from the following file:\begin{CompactItemize}

doc/latex/classmlstudent.tex

@@ -59 +59 @@
 virtual vec \hyperlink{classmpdf_3f172b79ec4a5ebc87898a5381141f1b}{samplecond} (const vec \&cond, double \&ll)
 \begin{CompactList}\small\item\em Returns the required moment of the \hyperlink{classepdf}{epdf}. \item\end{CompactList}\item 
-virtual mat \hyperlink{classmpdf_0e37163660f93df2a4d723cedb1da89c}{samplecond} (const vec \&cond, vec \&ll, int N)
+virtual mat \hyperlink{classmpdf_b1dae6171ee39a6a05976c7b1007a3c5}{samplecond\_\-m} (const vec \&cond, vec \&ll, int N)
 \begin{CompactList}\small\item\em Returns. \item\end{CompactList}\item 
-\hypertarget{classmpdf_80b738ece5bd4f8c4edaee4b38906f91}{
-virtual double \hyperlink{classmpdf_80b738ece5bd4f8c4edaee4b38906f91}{evalcond} (const vec \&dt, const vec \&cond)}
-\label{classmpdf_80b738ece5bd4f8c4edaee4b38906f91}
+\hypertarget{classmpdf_2ef8a6374029d990a678782f6decebbe}{
+virtual double \hyperlink{classmpdf_2ef8a6374029d990a678782f6decebbe}{evallogcond} (const vec \&dt, const vec \&cond)}
+\label{classmpdf_2ef8a6374029d990a678782f6decebbe}
 
 \begin{CompactList}\small\item\em Shortcut for conditioning and evaluation of the internal \hyperlink{classepdf}{epdf}. In some cases, this operation can be implemented efficiently. \item\end{CompactList}\item 
-\hypertarget{classmpdf_b7b2da35080cd15f1be365b805e7277e}{
-virtual vec \textbf{evalcond\_\-m} (const mat \&Dt, const vec \&cond)}
-\label{classmpdf_b7b2da35080cd15f1be365b805e7277e}
+\hypertarget{classmpdf_95fcff214848f66f1b489459370573fa}{
+virtual vec \hyperlink{classmpdf_95fcff214848f66f1b489459370573fa}{evallogcond\_\-m} (const mat \&Dt, const vec \&cond)}
+\label{classmpdf_95fcff214848f66f1b489459370573fa}
 
-\item 
+\begin{CompactList}\small\item\em Matrix version of evallogcond. \item\end{CompactList}\item 
 \hypertarget{classmpdf_15ef062183b1ccdf794732d5fa0b77cd}{
 \hyperlink{classRV}{RV} \hyperlink{classmpdf_15ef062183b1ccdf794732d5fa0b77cd}{\_\-rvc} () const }
@@ -171 +171 @@
 Reimplemented in \hyperlink{classmprod_a48887eb8738a9e5550bfc38eb8e9d68}{mprod}.
 
-References mpdf::condition(), mpdf::ep, epdf::evalpdflog(), and epdf::sample().
+References mpdf::condition(), mpdf::ep, epdf::evallog(), and epdf::sample().
 
-Referenced by MPF$<$ BM\_\-T $>$::bayes(), and PF::bayes().\hypertarget{classmpdf_0e37163660f93df2a4d723cedb1da89c}{
-\index{mlstudent@{mlstudent}!samplecond@{samplecond}}
-\index{samplecond@{samplecond}!mlstudent@{mlstudent}}
-\subsubsection[samplecond]{\setlength{\rightskip}{0pt plus 5cm}virtual mat mpdf::samplecond (const vec \& {\em cond}, \/  vec \& {\em ll}, \/  int {\em N})\hspace{0.3cm}{\tt  \mbox{[}inline, virtual, inherited\mbox{]}}}}
-\label{classmpdf_0e37163660f93df2a4d723cedb1da89c}
+Referenced by MPF$<$ BM\_\-T $>$::bayes(), and PF::bayes().\hypertarget{classmpdf_b1dae6171ee39a6a05976c7b1007a3c5}{
+\index{mlstudent@{mlstudent}!samplecond\_\-m@{samplecond\_\-m}}
+\index{samplecond\_\-m@{samplecond\_\-m}!mlstudent@{mlstudent}}
+\subsubsection[samplecond\_\-m]{\setlength{\rightskip}{0pt plus 5cm}virtual mat mpdf::samplecond\_\-m (const vec \& {\em cond}, \/  vec \& {\em ll}, \/  int {\em N})\hspace{0.3cm}{\tt  \mbox{[}inline, virtual, inherited\mbox{]}}}}
+\label{classmpdf_b1dae6171ee39a6a05976c7b1007a3c5}
 
 
@@ -189 +189 @@
 
 
-Reimplemented in \hyperlink{classmprod_e171c40e210539c2af01d6237785620b}{mprod}.
-
-References mpdf::condition(), RV::count(), mpdf::ep, epdf::evalpdflog(), mpdf::rv, and epdf::sample().
+References mpdf::condition(), RV::count(), mpdf::ep, epdf::evallog(), mpdf::rv, and epdf::sample().
 
 The documentation for this class was generated from the following file:\begin{CompactItemize}

doc/latex/classmmix.tex

@@ -42 +42 @@
 virtual vec \hyperlink{classmpdf_3f172b79ec4a5ebc87898a5381141f1b}{samplecond} (const vec \&cond, double \&ll)
 \begin{CompactList}\small\item\em Returns the required moment of the \hyperlink{classepdf}{epdf}. \item\end{CompactList}\item 
-virtual mat \hyperlink{classmpdf_0e37163660f93df2a4d723cedb1da89c}{samplecond} (const vec \&cond, vec \&ll, int N)
+virtual mat \hyperlink{classmpdf_b1dae6171ee39a6a05976c7b1007a3c5}{samplecond\_\-m} (const vec \&cond, vec \&ll, int N)
 \begin{CompactList}\small\item\em Returns. \item\end{CompactList}\item 
-\hypertarget{classmpdf_80b738ece5bd4f8c4edaee4b38906f91}{
-virtual double \hyperlink{classmpdf_80b738ece5bd4f8c4edaee4b38906f91}{evalcond} (const vec \&dt, const vec \&cond)}
-\label{classmpdf_80b738ece5bd4f8c4edaee4b38906f91}
+\hypertarget{classmpdf_2ef8a6374029d990a678782f6decebbe}{
+virtual double \hyperlink{classmpdf_2ef8a6374029d990a678782f6decebbe}{evallogcond} (const vec \&dt, const vec \&cond)}
+\label{classmpdf_2ef8a6374029d990a678782f6decebbe}
 
 \begin{CompactList}\small\item\em Shortcut for conditioning and evaluation of the internal \hyperlink{classepdf}{epdf}. In some cases, this operation can be implemented efficiently. \item\end{CompactList}\item 
-\hypertarget{classmpdf_b7b2da35080cd15f1be365b805e7277e}{
-virtual vec \textbf{evalcond\_\-m} (const mat \&Dt, const vec \&cond)}
-\label{classmpdf_b7b2da35080cd15f1be365b805e7277e}
+\hypertarget{classmpdf_95fcff214848f66f1b489459370573fa}{
+virtual vec \hyperlink{classmpdf_95fcff214848f66f1b489459370573fa}{evallogcond\_\-m} (const mat \&Dt, const vec \&cond)}
+\label{classmpdf_95fcff214848f66f1b489459370573fa}
 
-\item 
+\begin{CompactList}\small\item\em Matrix version of evallogcond. \item\end{CompactList}\item 
 \hypertarget{classmpdf_15ef062183b1ccdf794732d5fa0b77cd}{
 \hyperlink{classRV}{RV} \hyperlink{classmpdf_15ef062183b1ccdf794732d5fa0b77cd}{\_\-rvc} () const }
@@ -123 +123 @@
 Reimplemented in \hyperlink{classmprod_a48887eb8738a9e5550bfc38eb8e9d68}{mprod}.
 
-References mpdf::condition(), mpdf::ep, epdf::evalpdflog(), and epdf::sample().
+References mpdf::condition(), mpdf::ep, epdf::evallog(), and epdf::sample().
 
-Referenced by MPF$<$ BM\_\-T $>$::bayes(), and PF::bayes().\hypertarget{classmpdf_0e37163660f93df2a4d723cedb1da89c}{
-\index{mmix@{mmix}!samplecond@{samplecond}}
-\index{samplecond@{samplecond}!mmix@{mmix}}
-\subsubsection[samplecond]{\setlength{\rightskip}{0pt plus 5cm}virtual mat mpdf::samplecond (const vec \& {\em cond}, \/  vec \& {\em ll}, \/  int {\em N})\hspace{0.3cm}{\tt  \mbox{[}inline, virtual, inherited\mbox{]}}}}
-\label{classmpdf_0e37163660f93df2a4d723cedb1da89c}
+Referenced by MPF$<$ BM\_\-T $>$::bayes(), and PF::bayes().\hypertarget{classmpdf_b1dae6171ee39a6a05976c7b1007a3c5}{
+\index{mmix@{mmix}!samplecond\_\-m@{samplecond\_\-m}}
+\index{samplecond\_\-m@{samplecond\_\-m}!mmix@{mmix}}
+\subsubsection[samplecond\_\-m]{\setlength{\rightskip}{0pt plus 5cm}virtual mat mpdf::samplecond\_\-m (const vec \& {\em cond}, \/  vec \& {\em ll}, \/  int {\em N})\hspace{0.3cm}{\tt  \mbox{[}inline, virtual, inherited\mbox{]}}}}
+\label{classmpdf_b1dae6171ee39a6a05976c7b1007a3c5}
 
 
@@ -141 +141 @@
 
 
-Reimplemented in \hyperlink{classmprod_e171c40e210539c2af01d6237785620b}{mprod}.
-
-References mpdf::condition(), RV::count(), mpdf::ep, epdf::evalpdflog(), mpdf::rv, and epdf::sample().
+References mpdf::condition(), RV::count(), mpdf::ep, epdf::evallog(), mpdf::rv, and epdf::sample().
 
 The documentation for this class was generated from the following file:\begin{CompactItemize}

doc/latex/classmpdf.tex

@@ -27 +27 @@
 virtual vec \hyperlink{classmpdf_3f172b79ec4a5ebc87898a5381141f1b}{samplecond} (const vec \&cond, double \&ll)
 \begin{CompactList}\small\item\em Returns the required moment of the \hyperlink{classepdf}{epdf}. \item\end{CompactList}\item 
-virtual mat \hyperlink{classmpdf_0e37163660f93df2a4d723cedb1da89c}{samplecond} (const vec \&cond, vec \&ll, int N)
+virtual mat \hyperlink{classmpdf_b1dae6171ee39a6a05976c7b1007a3c5}{samplecond\_\-m} (const vec \&cond, vec \&ll, int N)
 \begin{CompactList}\small\item\em Returns. \item\end{CompactList}\item 
 \hypertarget{classmpdf_0f95a0cc6ab40611f46804682446ed83}{
@@ -34 +34 @@
 
 \begin{CompactList}\small\item\em Update {\tt ep} so that it represents this \hyperlink{classmpdf}{mpdf} conditioned on {\tt rvc} = cond. \item\end{CompactList}\item 
-\hypertarget{classmpdf_80b738ece5bd4f8c4edaee4b38906f91}{
-virtual double \hyperlink{classmpdf_80b738ece5bd4f8c4edaee4b38906f91}{evalcond} (const vec \&dt, const vec \&cond)}
-\label{classmpdf_80b738ece5bd4f8c4edaee4b38906f91}
+\hypertarget{classmpdf_2ef8a6374029d990a678782f6decebbe}{
+virtual double \hyperlink{classmpdf_2ef8a6374029d990a678782f6decebbe}{evallogcond} (const vec \&dt, const vec \&cond)}
+\label{classmpdf_2ef8a6374029d990a678782f6decebbe}
 
 \begin{CompactList}\small\item\em Shortcut for conditioning and evaluation of the internal \hyperlink{classepdf}{epdf}. In some cases, this operation can be implemented efficiently. \item\end{CompactList}\item 
-\hypertarget{classmpdf_b7b2da35080cd15f1be365b805e7277e}{
-virtual vec \textbf{evalcond\_\-m} (const mat \&Dt, const vec \&cond)}
-\label{classmpdf_b7b2da35080cd15f1be365b805e7277e}
+\hypertarget{classmpdf_95fcff214848f66f1b489459370573fa}{
+virtual vec \hyperlink{classmpdf_95fcff214848f66f1b489459370573fa}{evallogcond\_\-m} (const mat \&Dt, const vec \&cond)}
+\label{classmpdf_95fcff214848f66f1b489459370573fa}
 
-\item 
+\begin{CompactList}\small\item\em Matrix version of evallogcond. \item\end{CompactList}\item 
 \hypertarget{classmpdf_6788be9f3a888796499c5293a318fcfb}{
 virtual \hyperlink{classmpdf_6788be9f3a888796499c5293a318fcfb}{$\sim$mpdf} ()}
@@ -111 +111 @@
 Reimplemented in \hyperlink{classmprod_a48887eb8738a9e5550bfc38eb8e9d68}{mprod}.
 
-References condition(), ep, epdf::evalpdflog(), and epdf::sample().
+References condition(), ep, epdf::evallog(), and epdf::sample().
 
-Referenced by MPF$<$ BM\_\-T $>$::bayes(), and PF::bayes().\hypertarget{classmpdf_0e37163660f93df2a4d723cedb1da89c}{
-\index{mpdf@{mpdf}!samplecond@{samplecond}}
-\index{samplecond@{samplecond}!mpdf@{mpdf}}
-\subsubsection[samplecond]{\setlength{\rightskip}{0pt plus 5cm}virtual mat mpdf::samplecond (const vec \& {\em cond}, \/  vec \& {\em ll}, \/  int {\em N})\hspace{0.3cm}{\tt  \mbox{[}inline, virtual\mbox{]}}}}
-\label{classmpdf_0e37163660f93df2a4d723cedb1da89c}
+Referenced by MPF$<$ BM\_\-T $>$::bayes(), and PF::bayes().\hypertarget{classmpdf_b1dae6171ee39a6a05976c7b1007a3c5}{
+\index{mpdf@{mpdf}!samplecond\_\-m@{samplecond\_\-m}}
+\index{samplecond\_\-m@{samplecond\_\-m}!mpdf@{mpdf}}
+\subsubsection[samplecond\_\-m]{\setlength{\rightskip}{0pt plus 5cm}virtual mat mpdf::samplecond\_\-m (const vec \& {\em cond}, \/  vec \& {\em ll}, \/  int {\em N})\hspace{0.3cm}{\tt  \mbox{[}inline, virtual\mbox{]}}}}
+\label{classmpdf_b1dae6171ee39a6a05976c7b1007a3c5}
 
 
@@ -129 +129 @@
 
 
-Reimplemented in \hyperlink{classmprod_e171c40e210539c2af01d6237785620b}{mprod}.
-
-References condition(), RV::count(), ep, epdf::evalpdflog(), rv, and epdf::sample().
+References condition(), RV::count(), ep, epdf::evallog(), rv, and epdf::sample().
 
 The documentation for this class was generated from the following file:\begin{CompactItemize}

doc/latex/classmprod.tex

@@ -30 +30 @@
 
 \begin{CompactList}\small\item\em Constructor from list of mFacs,. \item\end{CompactList}\item 
-\hypertarget{classmprod_1e662c8d90a96bf19235a05373d6887a}{
-double \hyperlink{classmprod_1e662c8d90a96bf19235a05373d6887a}{evalcond} (const vec \&val, const vec \&cond)}
-\label{classmprod_1e662c8d90a96bf19235a05373d6887a}
+\hypertarget{classmprod_f5e1075f133f203113d92084b4a47c28}{
+double \hyperlink{classmprod_f5e1075f133f203113d92084b4a47c28}{evallogcond} (const vec \&val, const vec \&cond)}
+\label{classmprod_f5e1075f133f203113d92084b4a47c28}
 
 \begin{CompactList}\small\item\em Shortcut for conditioning and evaluation of the internal \hyperlink{classepdf}{epdf}. In some cases, this operation can be implemented efficiently. \item\end{CompactList}\item 
 vec \hyperlink{classmprod_a48887eb8738a9e5550bfc38eb8e9d68}{samplecond} (const vec \&cond, double \&ll)
 \begin{CompactList}\small\item\em Returns the required moment of the \hyperlink{classepdf}{epdf}. \item\end{CompactList}\item 
-mat \hyperlink{classmprod_e171c40e210539c2af01d6237785620b}{samplecond} (const vec \&cond, vec \&ll, int N)
-\begin{CompactList}\small\item\em Returns. \item\end{CompactList}\item 
+\hypertarget{classmprod_e171c40e210539c2af01d6237785620b}{
+mat \textbf{samplecond} (const vec \&cond, vec \&ll, int N)}
+\label{classmprod_e171c40e210539c2af01d6237785620b}
+
+\item 
 \hyperlink{classRV}{RV} \hyperlink{classcompositepdf_635d219fb3e32852400d6f98aa4bdc93}{getrv} (bool checkoverlap=false)
 \begin{CompactList}\small\item\em find common rv, flag \item\end{CompactList}\item 
@@ -46 +49 @@
 
 \begin{CompactList}\small\item\em common rvc of all mpdfs is written to rvc \item\end{CompactList}\item 
+virtual mat \hyperlink{classmpdf_b1dae6171ee39a6a05976c7b1007a3c5}{samplecond\_\-m} (const vec \&cond, vec \&ll, int N)
+\begin{CompactList}\small\item\em Returns. \item\end{CompactList}\item 
 \hypertarget{classmpdf_0f95a0cc6ab40611f46804682446ed83}{
 virtual void \hyperlink{classmpdf_0f95a0cc6ab40611f46804682446ed83}{condition} (const vec \&cond)}
@@ -51 +56 @@
 
 \begin{CompactList}\small\item\em Update {\tt ep} so that it represents this \hyperlink{classmpdf}{mpdf} conditioned on {\tt rvc} = cond. \item\end{CompactList}\item 
-\hypertarget{classmpdf_b7b2da35080cd15f1be365b805e7277e}{
-virtual vec \textbf{evalcond\_\-m} (const mat \&Dt, const vec \&cond)}
-\label{classmpdf_b7b2da35080cd15f1be365b805e7277e}
+\hypertarget{classmpdf_95fcff214848f66f1b489459370573fa}{
+virtual vec \hyperlink{classmpdf_95fcff214848f66f1b489459370573fa}{evallogcond\_\-m} (const mat \&Dt, const vec \&cond)}
+\label{classmpdf_95fcff214848f66f1b489459370573fa}
 
-\item 
+\begin{CompactList}\small\item\em Matrix version of evallogcond. \item\end{CompactList}\item 
 \hypertarget{classmpdf_15ef062183b1ccdf794732d5fa0b77cd}{
 \hyperlink{classRV}{RV} \hyperlink{classmpdf_15ef062183b1ccdf794732d5fa0b77cd}{\_\-rvc} () const }
@@ -135 +140 @@
 Reimplemented from \hyperlink{classmpdf_3f172b79ec4a5ebc87898a5381141f1b}{mpdf}.
 
-References RV::count(), dls, epdfs, compositepdf::mpdfs, compositepdf::n, and mpdf::rv.
-
-Referenced by samplecond().\hypertarget{classmprod_e171c40e210539c2af01d6237785620b}{
-\index{mprod@{mprod}!samplecond@{samplecond}}
-\index{samplecond@{samplecond}!mprod@{mprod}}
-\subsubsection[samplecond]{\setlength{\rightskip}{0pt plus 5cm}mat mprod::samplecond (const vec \& {\em cond}, \/  vec \& {\em ll}, \/  int {\em N})\hspace{0.3cm}{\tt  \mbox{[}inline, virtual\mbox{]}}}}
-\label{classmprod_e171c40e210539c2af01d6237785620b}
-
-
-Returns. 
-
-\begin{Desc}
-\item[Parameters:]
-\begin{description}
-\item[{\em N}]samples from the density conditioned on {\tt cond}, $x \sim epdf(rv|cond)$. \item[{\em cond}]is numeric value of {\tt rv} \item[{\em ll}]is a return value of log-likelihood of the sample. \end{description}
-\end{Desc}
-
-
-Reimplemented from \hyperlink{classmpdf_0e37163660f93df2a4d723cedb1da89c}{mpdf}.
-
-References RV::count(), mpdf::rv, and samplecond().\hypertarget{classcompositepdf_635d219fb3e32852400d6f98aa4bdc93}{
+References RV::count(), dls, epdfs, compositepdf::mpdfs, compositepdf::n, and mpdf::rv.\hypertarget{classcompositepdf_635d219fb3e32852400d6f98aa4bdc93}{
 \index{mprod@{mprod}!getrv@{getrv}}
 \index{getrv@{getrv}!mprod@{mprod}}
@@ -171 +156 @@
 
 
-References RV::add(), compositepdf::mpdfs, and compositepdf::n.
+References RV::add(), compositepdf::mpdfs, and compositepdf::n.\hypertarget{classmpdf_b1dae6171ee39a6a05976c7b1007a3c5}{
+\index{mprod@{mprod}!samplecond\_\-m@{samplecond\_\-m}}
+\index{samplecond\_\-m@{samplecond\_\-m}!mprod@{mprod}}
+\subsubsection[samplecond\_\-m]{\setlength{\rightskip}{0pt plus 5cm}virtual mat mpdf::samplecond\_\-m (const vec \& {\em cond}, \/  vec \& {\em ll}, \/  int {\em N})\hspace{0.3cm}{\tt  \mbox{[}inline, virtual, inherited\mbox{]}}}}
+\label{classmpdf_b1dae6171ee39a6a05976c7b1007a3c5}
+
+
+Returns. 
+
+\begin{Desc}
+\item[Parameters:]
+\begin{description}
+\item[{\em N}]samples from the density conditioned on {\tt cond}, $x \sim epdf(rv|cond)$. \item[{\em cond}]is numeric value of {\tt rv} \item[{\em ll}]is a return value of log-likelihood of the sample. \end{description}
+\end{Desc}
+
+
+References mpdf::condition(), RV::count(), mpdf::ep, epdf::evallog(), mpdf::rv, and epdf::sample().
 
 The documentation for this class was generated from the following file:\begin{CompactItemize}

doc/latex/classmratio.tex

@@ -27 +27 @@
 \hyperlink{classmratio_c2452f4fc3046cfe8f2453deb343b3ac}{mratio} (const \hyperlink{classepdf}{epdf} $\ast$nom0, const \hyperlink{classRV}{RV} \&\hyperlink{classmpdf_f6687c07ff07d47812dd565368ca59eb}{rv}, bool copy=false)
 \item 
-\hypertarget{classmratio_6d440ca39571004425c2bffbc227d3dc}{
-double \hyperlink{classmratio_6d440ca39571004425c2bffbc227d3dc}{evalcond} (const vec \&val, const vec \&cond)}
-\label{classmratio_6d440ca39571004425c2bffbc227d3dc}
+\hypertarget{classmratio_9fb0df09a2e975e8b9f7ce41ecd65a09}{
+double \hyperlink{classmratio_9fb0df09a2e975e8b9f7ce41ecd65a09}{evallogcond} (const vec \&val, const vec \&cond)}
+\label{classmratio_9fb0df09a2e975e8b9f7ce41ecd65a09}
 
 \begin{CompactList}\small\item\em Shortcut for conditioning and evaluation of the internal \hyperlink{classepdf}{epdf}. In some cases, this operation can be implemented efficiently. \item\end{CompactList}\item 
@@ -44 +44 @@
 virtual vec \hyperlink{classmpdf_3f172b79ec4a5ebc87898a5381141f1b}{samplecond} (const vec \&cond, double \&ll)
 \begin{CompactList}\small\item\em Returns the required moment of the \hyperlink{classepdf}{epdf}. \item\end{CompactList}\item 
-virtual mat \hyperlink{classmpdf_0e37163660f93df2a4d723cedb1da89c}{samplecond} (const vec \&cond, vec \&ll, int N)
+virtual mat \hyperlink{classmpdf_b1dae6171ee39a6a05976c7b1007a3c5}{samplecond\_\-m} (const vec \&cond, vec \&ll, int N)
 \begin{CompactList}\small\item\em Returns. \item\end{CompactList}\item 
 \hypertarget{classmpdf_0f95a0cc6ab40611f46804682446ed83}{
@@ -51 +51 @@
 
 \begin{CompactList}\small\item\em Update {\tt ep} so that it represents this \hyperlink{classmpdf}{mpdf} conditioned on {\tt rvc} = cond. \item\end{CompactList}\item 
-\hypertarget{classmpdf_b7b2da35080cd15f1be365b805e7277e}{
-virtual vec \textbf{evalcond\_\-m} (const mat \&Dt, const vec \&cond)}
-\label{classmpdf_b7b2da35080cd15f1be365b805e7277e}
+\hypertarget{classmpdf_95fcff214848f66f1b489459370573fa}{
+virtual vec \hyperlink{classmpdf_95fcff214848f66f1b489459370573fa}{evallogcond\_\-m} (const mat \&Dt, const vec \&cond)}
+\label{classmpdf_95fcff214848f66f1b489459370573fa}
 
-\item 
+\begin{CompactList}\small\item\em Matrix version of evallogcond. \item\end{CompactList}\item 
 \hypertarget{classmpdf_15ef062183b1ccdf794732d5fa0b77cd}{
 \hyperlink{classRV}{RV} \hyperlink{classmpdf_15ef062183b1ccdf794732d5fa0b77cd}{\_\-rvc} () const }
@@ -116 +116 @@
 In particular this type of arise by conditioning of a mixture model.
 
-At present the only supported operation is \hyperlink{classmratio_6d440ca39571004425c2bffbc227d3dc}{evalcond()}. 
+At present the only supported operation is \hyperlink{classmratio_9fb0df09a2e975e8b9f7ce41ecd65a09}{evallogcond()}. 
 
 \subsection{Constructor \& Destructor Documentation}
@@ -149 +149 @@
 Reimplemented in \hyperlink{classmprod_a48887eb8738a9e5550bfc38eb8e9d68}{mprod}.
 
-References mpdf::condition(), mpdf::ep, epdf::evalpdflog(), and epdf::sample().
+References mpdf::condition(), mpdf::ep, epdf::evallog(), and epdf::sample().
 
-Referenced by MPF$<$ BM\_\-T $>$::bayes(), and PF::bayes().\hypertarget{classmpdf_0e37163660f93df2a4d723cedb1da89c}{
-\index{mratio@{mratio}!samplecond@{samplecond}}
-\index{samplecond@{samplecond}!mratio@{mratio}}
-\subsubsection[samplecond]{\setlength{\rightskip}{0pt plus 5cm}virtual mat mpdf::samplecond (const vec \& {\em cond}, \/  vec \& {\em ll}, \/  int {\em N})\hspace{0.3cm}{\tt  \mbox{[}inline, virtual, inherited\mbox{]}}}}
-\label{classmpdf_0e37163660f93df2a4d723cedb1da89c}
+Referenced by MPF$<$ BM\_\-T $>$::bayes(), and PF::bayes().\hypertarget{classmpdf_b1dae6171ee39a6a05976c7b1007a3c5}{
+\index{mratio@{mratio}!samplecond\_\-m@{samplecond\_\-m}}
+\index{samplecond\_\-m@{samplecond\_\-m}!mratio@{mratio}}
+\subsubsection[samplecond\_\-m]{\setlength{\rightskip}{0pt plus 5cm}virtual mat mpdf::samplecond\_\-m (const vec \& {\em cond}, \/  vec \& {\em ll}, \/  int {\em N})\hspace{0.3cm}{\tt  \mbox{[}inline, virtual, inherited\mbox{]}}}}
+\label{classmpdf_b1dae6171ee39a6a05976c7b1007a3c5}
 
 
@@ -167 +167 @@
 
 
-Reimplemented in \hyperlink{classmprod_e171c40e210539c2af01d6237785620b}{mprod}.
-
-References mpdf::condition(), RV::count(), mpdf::ep, epdf::evalpdflog(), mpdf::rv, and epdf::sample().
+References mpdf::condition(), RV::count(), mpdf::ep, epdf::evallog(), mpdf::rv, and epdf::sample().
 
 The documentation for this class was generated from the following file:\begin{CompactItemize}

doc/latex/doxygen.sty

@@ -11 +11 @@
 \rhead[\fancyplain{}{\bfseries\leftmark}]
         {\fancyplain{}{\bfseries\thepage}}
-\rfoot[\fancyplain{}{\bfseries\scriptsize Generated on Wed Nov 12 20:46:05 2008 for mixpp by Doxygen }]{}
-\lfoot[]{\fancyplain{}{\bfseries\scriptsize Generated on Wed Nov 12 20:46:05 2008 for mixpp by Doxygen }}
+\rfoot[\fancyplain{}{\bfseries\scriptsize Generated on Thu Dec 4 14:42:12 2008 for mixpp by Doxygen }]{}
+\lfoot[]{\fancyplain{}{\bfseries\scriptsize Generated on Thu Dec 4 14:42:12 2008 for mixpp by Doxygen }}
 \cfoot{}
 \newenvironment{Code}

doc/latex/group__core.tex

@@ -1 @@
-\hypertarget{libBM_8h}{
-\section{work/git/mixpp/bdm/stat/libBM.h File Reference}
-\label{libBM_8h}\index{work/git/mixpp/bdm/stat/libBM.h@{work/git/mixpp/bdm/stat/libBM.h}}
+\hypertarget{group__core}{
+\section{Core BDM classes}
+\label{group__core}\index{Core BDM classes@{Core BDM classes}}
 }
-Bayesian Models (bm) that use Bayes rule to learn from observations. 
-
-{\tt \#include $<$itpp/itbase.h$>$}\par
-{\tt \#include \char`\"{}../itpp\_\-ext.h\char`\"{}}\par
-
-
-Include dependency graph for libBM.h:\nopagebreak
-\begin{figure}[H]
-\begin{center}
-\leavevmode
-\includegraphics[width=106pt]{libBM_8h__incl}
-\end{center}
-\end{figure}
-
-
-This graph shows which files directly or indirectly include this file:\nopagebreak
-\begin{figure}[H]
-\begin{center}
-\leavevmode
-\includegraphics[width=420pt]{libBM_8h__dep__incl}
-\end{center}
-\end{figure}
 \subsection*{Classes}
 \begin{CompactItemize}
@@ -57 +35 @@
 \begin{CompactItemize}
 \item 
-\hypertarget{libBM_8h_33c114e83980d883c5b211c47d5322a4}{
-\hyperlink{classRV}{RV} \hyperlink{libBM_8h_33c114e83980d883c5b211c47d5322a4}{concat} (const \hyperlink{classRV}{RV} \&rv1, const \hyperlink{classRV}{RV} \&rv2)}
-\label{libBM_8h_33c114e83980d883c5b211c47d5322a4}
+\hypertarget{group__core_g33c114e83980d883c5b211c47d5322a4}{
+\hyperlink{classRV}{RV} \hyperlink{group__core_g33c114e83980d883c5b211c47d5322a4}{concat} (const \hyperlink{classRV}{RV} \&rv1, const \hyperlink{classRV}{RV} \&rv2)}
+\label{group__core_g33c114e83980d883c5b211c47d5322a4}
 
 \begin{CompactList}\small\item\em Concat two random variables. \item\end{CompactList}\end{CompactItemize}
+\subsection*{Variables}
+\begin{CompactItemize}
+\item 
+\hypertarget{group__core_g9ea0562597470f6058ec209ee72db5fa}{
+\hyperlink{classRV}{RV} \hyperlink{group__core_g9ea0562597470f6058ec209ee72db5fa}{RV0}}
+\label{group__core_g9ea0562597470f6058ec209ee72db5fa}
 
-
-\subsection{Detailed Description}
-Bayesian Models (bm) that use Bayes rule to learn from observations. 
-
-\begin{Desc}
-\item[Author:]Vaclav Smidl.\end{Desc}
------------------------------------ BDM++ - C++ library for Bayesian Decision Making under Uncertainty
-
-Using IT++ for numerical operations ----------------------------------- 
+\begin{CompactList}\small\item\em Default empty \hyperlink{classRV}{RV} that can be used as default argument. \item\end{CompactList}\end{CompactItemize}

doc/latex/libBM_8h.tex

@@ -57 +57 @@
 \begin{CompactItemize}
 \item 
-\hypertarget{libBM_8h_33c114e83980d883c5b211c47d5322a4}{
-\hyperlink{classRV}{RV} \hyperlink{libBM_8h_33c114e83980d883c5b211c47d5322a4}{concat} (const \hyperlink{classRV}{RV} \&rv1, const \hyperlink{classRV}{RV} \&rv2)}
-\label{libBM_8h_33c114e83980d883c5b211c47d5322a4}
+\hypertarget{group__core_g33c114e83980d883c5b211c47d5322a4}{
+\hyperlink{classRV}{RV} \hyperlink{group__core_g33c114e83980d883c5b211c47d5322a4}{concat} (const \hyperlink{classRV}{RV} \&rv1, const \hyperlink{classRV}{RV} \&rv2)}
+\label{group__core_g33c114e83980d883c5b211c47d5322a4}
 
 \begin{CompactList}\small\item\em Concat two random variables. \item\end{CompactList}\end{CompactItemize}
+\subsection*{Variables}
+\begin{CompactItemize}
+\item 
+\hypertarget{group__core_g9ea0562597470f6058ec209ee72db5fa}{
+\hyperlink{classRV}{RV} \hyperlink{group__core_g9ea0562597470f6058ec209ee72db5fa}{RV0}}
+\label{group__core_g9ea0562597470f6058ec209ee72db5fa}
+
+\begin{CompactList}\small\item\em Default empty \hyperlink{classRV}{RV} that can be used as default argument. \item\end{CompactList}\end{CompactItemize}
 
 

doc/latex/libDC_8h.tex

@@ -37 +37 @@
 \begin{CompactItemize}
 \item 
-\hypertarget{libDC_8h_4ed56e73b49db8e7f4a63fa926a8dca4}{
-void \hyperlink{libDC_8h_4ed56e73b49db8e7f4a63fa926a8dca4}{dydr} (double $\ast$r, double $\ast$f, double $\ast$Dr, double $\ast$Df, double $\ast$R, int jl, int jh, double $\ast$kr, int m, int mx)}
-\label{libDC_8h_4ed56e73b49db8e7f4a63fa926a8dca4}
+\hypertarget{group__math_g4ed56e73b49db8e7f4a63fa926a8dca4}{
+void \hyperlink{group__math_g4ed56e73b49db8e7f4a63fa926a8dca4}{dydr} (double $\ast$r, double $\ast$f, double $\ast$Dr, double $\ast$Df, double $\ast$R, int jl, int jh, double $\ast$kr, int m, int mx)}
+\label{group__math_g4ed56e73b49db8e7f4a63fa926a8dca4}
 
 \begin{CompactList}\small\item\em Auxiliary function dydr; dyadic reduction. \item\end{CompactList}\item 
-\hypertarget{libDC_8h_6715d039e6d5d97005cf9e2522dfa474}{
-mat \hyperlink{libDC_8h_6715d039e6d5d97005cf9e2522dfa474}{ltuinv} (const mat \&L)}
-\label{libDC_8h_6715d039e6d5d97005cf9e2522dfa474}
+\hypertarget{group__math_g6715d039e6d5d97005cf9e2522dfa474}{
+mat \hyperlink{group__math_g6715d039e6d5d97005cf9e2522dfa474}{ltuinv} (const mat \&L)}
+\label{group__math_g6715d039e6d5d97005cf9e2522dfa474}
 
 \begin{CompactList}\small\item\em Auxiliary function ltuinv; inversion of a triangular matrix;. \item\end{CompactList}\end{CompactItemize}

doc/latex/refman.tex

@@ -39 +39 @@
 {\large Generated by Doxygen 1.5.6}\\
 \vspace*{0.5cm}
-{\small Wed Nov 12 20:46:05 2008}\\
+{\small Thu Dec 4 14:42:13 2008}\\
 \end{center}
 \end{titlepage}
@@ -53 +53 @@
 \hypertarget{codingrules}{}
 \include{codingrules}
-\chapter{Introduction to Bayesian Decision Making Toolbox BDM}
-\label{intro}
-\hypertarget{intro}{}
-\include{intro}
+\chapter{Module Index}
+\input{modules}
 \chapter{Class Index}
 \input{hierarchy}
@@ -63 +61 @@
 \chapter{File Index}
 \input{files}
+\chapter{Module Documentation}
+\input{group__math}
+\include{group__core}
 \chapter{Class Documentation}
 \input{classARX}