Changeset 32 for doc/latex

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Timestamp:
03/03/08 13:00:32 (16 years ago)
Author:
smidl
Message:

test KF : estimation of R in KF is not possible! Likelihood of y_t is growing when R -> 0

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doc/latex
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1 added
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  • doc/latex/annotated.tex

    r22 r32  
    33\item\contentsline{section}{{\bf bilinfn} (Class representing function \$f(x,u) = Ax+Bu\$ )}{\pageref{classbilinfn}}{} 
    44\item\contentsline{section}{{\bf BM} (Bayesian Model of the world, i.e. all uncertainty is modeled by probabilities )}{\pageref{classBM}}{} 
     5\item\contentsline{section}{{\bf BMcond} (Conditional Bayesian Filter )}{\pageref{classBMcond}}{} 
    56\item\contentsline{section}{{\bf constfn} (Class representing function \$f(x) = a\$, here rv is empty )}{\pageref{classconstfn}}{} 
    67\item\contentsline{section}{{\bf diffbifn} (Class representing a differentiable function of two variables \$f(x,u)\$ )}{\pageref{classdiffbifn}}{} 
    78\item\contentsline{section}{{\bf DS} (Abstract class for discrete-time sources of data )}{\pageref{classDS}}{} 
    89\item\contentsline{section}{{\bf eEF} (General conjugate exponential family posterior density )}{\pageref{classeEF}}{} 
     10\item\contentsline{section}{{\bf eEmp} (Weighted empirical density )}{\pageref{classeEmp}}{} 
     11\item\contentsline{section}{{\bf egamma} (Gamma posterior density )}{\pageref{classegamma}}{} 
    912\item\contentsline{section}{{\bf EKF$<$ sq\_\-T $>$} (Extended \doxyref{Kalman}{p.}{classKalman} Filter )}{\pageref{classEKF}}{} 
     13\item\contentsline{section}{{\bf emix} (Weighted mixture of epdfs with external owned components )}{\pageref{classemix}}{} 
    1014\item\contentsline{section}{{\bf enorm$<$ sq\_\-T $>$} (Gaussian density with positive definite (decomposed) covariance matrix )}{\pageref{classenorm}}{} 
    1115\item\contentsline{section}{{\bf epdf} (Probability density function with numerical statistics, e.g. posterior density )}{\pageref{classepdf}}{} 
     16\item\contentsline{section}{{\bf euni} (Uniform distributed density on a rectangular support )}{\pageref{classeuni}}{} 
    1217\item\contentsline{section}{{\bf fnc} (Class representing function \$f(x)\$ of variable \$x\$ represented by {\tt rv} )}{\pageref{classfnc}}{} 
    1318\item\contentsline{section}{{\bf fsqmat} (Fake \doxyref{sqmat}{p.}{classsqmat}. This class maps \doxyref{sqmat}{p.}{classsqmat} operations to operations on full matrix )}{\pageref{classfsqmat}}{} 
     19\item\contentsline{section}{{\bf itpp::Gamma\_\-RNG} (Gamma distribution )}{\pageref{classitpp_1_1Gamma__RNG}}{} 
    1420\item\contentsline{section}{{\bf Kalman$<$ sq\_\-T $>$} (\doxyref{Kalman}{p.}{classKalman} filter with covariance matrices in square root form )}{\pageref{classKalman}}{} 
    1521\item\contentsline{section}{{\bf KalmanFull} (Basic \doxyref{Kalman}{p.}{classKalman} filter with full matrices (education purpose only)! Will be deleted soon! )}{\pageref{classKalmanFull}}{} 
     22\item\contentsline{section}{{\bf KFcondQR} (\doxyref{Kalman}{p.}{classKalman} Filter with conditional diagonal matrices R and Q )}{\pageref{classKFcondQR}}{} 
    1623\item\contentsline{section}{{\bf linfn} (Class representing function \$f(x) = Ax+B\$ )}{\pageref{classlinfn}}{} 
    1724\item\contentsline{section}{{\bf MemDS} (Class representing off-line data stored in memory )}{\pageref{classMemDS}}{} 
     25\item\contentsline{section}{{\bf mgamma} (Gamma random walk )}{\pageref{classmgamma}}{} 
     26\item\contentsline{section}{{\bf mlnorm$<$ sq\_\-T $>$} (Normal distributed linear function with linear function of mean value; )}{\pageref{classmlnorm}}{} 
    1827\item\contentsline{section}{{\bf mpdf} (Conditional probability density, e.g. modeling some dependencies )}{\pageref{classmpdf}}{} 
    19 \item\contentsline{section}{{\bf PF} (A Particle Filter prototype )}{\pageref{classPF}}{} 
     28\item\contentsline{section}{{\bf MPF$<$ BM\_\-T $>$} (Marginalized Particle filter )}{\pageref{classMPF}}{} 
     29\item\contentsline{section}{{\bf PF} (Trivial particle filter with proposal density equal to parameter evolution model )}{\pageref{classPF}}{} 
    2030\item\contentsline{section}{{\bf RV} (Class representing variables, most often random variables )}{\pageref{classRV}}{} 
    2131\item\contentsline{section}{{\bf sqmat} (Virtual class for representation of double symmetric matrices in square-root form )}{\pageref{classsqmat}}{} 
    22 \item\contentsline{section}{{\bf TrivialPF} (Trivial particle filter with proposal density that is not conditioned on the data )}{\pageref{classTrivialPF}}{} 
    2332\end{CompactList} 

  • doc/latex/classBM.tex

    r28 r32  
    1010\begin{center} 
    1111\leavevmode 
    12 \includegraphics[width=161pt]{classBM__inherit__graph} 
     12\includegraphics[width=142pt]{classBM__inherit__graph} 
     13\end{center} 
     14\end{figure} 
     15Collaboration diagram for BM:\nopagebreak 
     16\begin{figure}[H] 
     17\begin{center} 
     18\leavevmode 
     19\includegraphics[width=38pt]{classBM__coll__graph} 
    1320\end{center} 
    1421\end{figure} 
    … …  
    1623\begin{CompactItemize} 
    1724\item  
    18 {\bf BM} ()\label{classBM_ef32a12f4f89e4000bf5390ceda762ae} 
     25{\bf BM} (const {\bf RV} \&rv0)\label{classBM_605d28b426adb677c86a57ddb525132a} 
    1926 
    2027\begin{CompactList}\small\item\em Default constructor. \item\end{CompactList}\item  
    … …  
    2431 
    2532\begin{CompactList}\small\item\em Batch Bayes rule (columns of Dt are observations). \item\end{CompactList}\item  
    26 {\bf epdf} $\ast$ {\bf \_\-epdf} ()\label{classBM_a5b8f6c8a872738cfaa30ab010e8c077} 
     33virtual {\bf epdf} \& {\bf \_\-epdf} ()=0\label{classBM_3dc45554556926bde996a267636abe55} 
    2734 
    28 \begin{CompactList}\small\item\em Returns a pointer to the \doxyref{epdf}{p.}{classepdf} representing posterior density on parameters. Use with care! \item\end{CompactList}\end{CompactItemize} 
    29 \subsection*{Public Attributes} 
     35\begin{CompactList}\small\item\em Returns a pointer to the \doxyref{epdf}{p.}{classepdf} representing posterior density on parameters. Use with care! \item\end{CompactList}\item  
     36virtual {\bf $\sim$BM} ()\label{classBM_ca0f02b3b4144e0895cc14f7e0374bdd} 
     37 
     38\begin{CompactList}\small\item\em Destructor for future use;. \item\end{CompactList}\end{CompactItemize} 
     39\subsection*{Protected Attributes} 
    3040\begin{CompactItemize} 
    3141\item  
     42{\bf RV} {\bf rv}\label{classBM_af00f0612fabe66241dd507188cdbf88} 
     43 
     44\begin{CompactList}\small\item\em Random variable of the posterior. \item\end{CompactList}\item  
    3245double {\bf ll}\label{classBM_5623fef6572a08c2b53b8c87b82dc979} 
    3346 
    … …  
    5669 
    5770 
     71Implemented in {\bf Kalman$<$ sq\_\-T $>$} \doxyref{}{p.}{classKalman_7750ffd73f261828a32c18aaeb65c75c}, {\bf EKF$<$ sq\_\-T $>$} \doxyref{}{p.}{classEKF_c79c62c9b3e0b56b3aaa1b6f1d9a7af7}, {\bf PF} \doxyref{}{p.}{classPF_64f636bbd63bea9efd778214e6b631d3}, {\bf MPF$<$ BM\_\-T $>$} \doxyref{}{p.}{classMPF_55daf8e4b6553dd9f47c692de7931623}, and {\bf Kalman$<$ ldmat $>$} \doxyref{}{p.}{classKalman_7750ffd73f261828a32c18aaeb65c75c}. 
     72 
    5873The documentation for this class was generated from the following file:\begin{CompactItemize} 
    5974\item  

  • doc/latex/classKalman.tex

    r28 r32  
    1010\begin{center} 
    1111\leavevmode 
    12 \includegraphics[width=77pt]{classKalman__inherit__graph} 
     12\includegraphics[width=103pt]{classKalman__inherit__graph} 
    1313\end{center} 
    1414\end{figure} 
    … …  
    1717\begin{center} 
    1818\leavevmode 
    19 \includegraphics[width=70pt]{classKalman__coll__graph} 
     19\includegraphics[width=81pt]{classKalman__coll__graph} 
    2020\end{center} 
    2121\end{figure} 
    … …  
    2323\begin{CompactItemize} 
    2424\item  
    25 {\bf Kalman} (int dimx, int dimu, int dimy)\label{classKalman_96958a5ebfa966d892137987f265083a} 
     25{\bf Kalman} ({\bf RV} rvx0, {\bf RV} rvy0, {\bf RV} rvu0)\label{classKalman_3d56b0a97b8c1e25fdd3b10eef3c2ad3} 
    2626 
    2727\begin{CompactList}\small\item\em Default constructor. \item\end{CompactList}\item  
    28 {\bf Kalman} (mat A0, mat B0, mat C0, mat D0, sq\_\-T R0, sq\_\-T Q0, sq\_\-T P0, vec mu0)\label{classKalman_83118f4bd2ecbc70b03cfd573088ed6f} 
     28{\bf Kalman} (const {\bf Kalman}$<$ sq\_\-T $>$ \&K0)\label{classKalman_ce38e31810aea4db45a83ad05eaba009} 
    2929 
    30 \begin{CompactList}\small\item\em Full constructor. \item\end{CompactList}\item  
    31 void {\bf bayes} (const vec \&dt, bool {\bf evalll}=true)\label{classKalman_e945d9205ca14acbd83ba80ea6f72b8e} 
     30\begin{CompactList}\small\item\em Copy constructor. \item\end{CompactList}\item  
     31void {\bf set\_\-parameters} (const mat \&A0, const mat \&B0, const mat \&C0, const mat \&D0, const sq\_\-T \&R0, const sq\_\-T \&Q0)\label{classKalman_239b28a0380946f5749b2f8d2807f93a} 
     32 
     33\begin{CompactList}\small\item\em Set parameters with check of relevance. \item\end{CompactList}\item  
     34void {\bf set\_\-est} (const vec \&mu0, const sq\_\-T \&P0)\label{classKalman_80bcf29466d9a9dd2b8f74699807d0c0} 
     35 
     36\begin{CompactList}\small\item\em Set estimate values, used e.g. in initialization. \item\end{CompactList}\item  
     37void {\bf bayes} (const vec \&dt)\label{classKalman_7750ffd73f261828a32c18aaeb65c75c} 
    3238 
    3339\begin{CompactList}\small\item\em Here dt = [yt;ut] of appropriate dimensions. \item\end{CompactList}\item  
    34 virtual void {\bf bayes} (const vec \&dt)=0 
    35 \begin{CompactList}\small\item\em Incremental Bayes rule. \item\end{CompactList}\item  
     40{\bf epdf} \& {\bf \_\-epdf} ()\label{classKalman_a213c57aef55b2645e550bed81cfc0d4} 
     41 
     42\begin{CompactList}\small\item\em Returns a pointer to the \doxyref{epdf}{p.}{classepdf} representing posterior density on parameters. Use with care! \item\end{CompactList}\item  
    3643void {\bf bayes} (mat Dt)\label{classBM_87b07867fd4c133aa89a18543f68d9f9} 
    3744 
    38 \begin{CompactList}\small\item\em Batch Bayes rule (columns of Dt are observations). \item\end{CompactList}\item  
    39 {\bf epdf} $\ast$ {\bf \_\-epdf} ()\label{classBM_a5b8f6c8a872738cfaa30ab010e8c077} 
    40  
    41 \begin{CompactList}\small\item\em Returns a pointer to the \doxyref{epdf}{p.}{classepdf} representing posterior density on parameters. Use with care! \item\end{CompactList}\end{CompactItemize} 
    42 \subsection*{Public Attributes} 
     45\begin{CompactList}\small\item\em Batch Bayes rule (columns of Dt are observations). \item\end{CompactList}\end{CompactItemize} 
     46\subsection*{Protected Attributes} 
    4347\begin{CompactItemize} 
    4448\item  
    45 vec {\bf mu}\label{classKalman_3063a3f58a74cea672ae889971012eed} 
     49{\bf RV} \textbf{rvy}\label{classKalman_7501230c2fafa3655887d2da23b3184c} 
    4650 
    47 \begin{CompactList}\small\item\em Mean value of the posterior density. \item\end{CompactList}\item  
    48 sq\_\-T {\bf P}\label{classKalman_188cd5ac1c9e496b1a371eb7c57c97d3} 
     51\item  
     52{\bf RV} \textbf{rvu}\label{classKalman_44a16ffd5ac1e6e39bae34fea9e1e498} 
    4953 
    50 \begin{CompactList}\small\item\em Mean value of the posterior density. \item\end{CompactList}\item  
    51 double {\bf ll}\label{classBM_5623fef6572a08c2b53b8c87b82dc979} 
    52  
    53 \begin{CompactList}\small\item\em Logarithm of marginalized data likelihood. \item\end{CompactList}\item  
    54 bool {\bf evalll}\label{classBM_bf6fb59b30141074f8ee1e2f43d03129} 
    55  
    56 \begin{CompactList}\small\item\em If true, the filter will compute likelihood of the data record and store it in {\tt ll} . Set to false if you want to save time. \item\end{CompactList}\end{CompactItemize} 
    57 \subsection*{Protected Attributes} 
    58 \begin{CompactItemize} 
    5954\item  
    6055int \textbf{dimx}\label{classKalman_39c8c403b46fa3b8c7da77cb2e3729eb} 
    … …  
    8580 
    8681\item  
     82{\bf enorm}$<$ sq\_\-T $>$ {\bf est}\label{classKalman_5568c74bac67ae6d3b1061dba60c9424} 
     83 
     84\begin{CompactList}\small\item\em posterior density on \$x\_\-t\$ \item\end{CompactList}\item  
     85{\bf enorm}$<$ sq\_\-T $>$ {\bf fy}\label{classKalman_e580ab06483952bd03f2e651763e184f} 
     86 
     87\begin{CompactList}\small\item\em preditive density on \$y\_\-t\$ \item\end{CompactList}\item  
    8788mat \textbf{\_\-K}\label{classKalman_d422f51467c7a06174af2476d2826132} 
    8889 
    8990\item  
    90 vec \textbf{\_\-yp}\label{classKalman_30b7461989185d3d02cf42b8e2a37649} 
     91vec $\ast$ \textbf{\_\-yp}\label{classKalman_5188eb0329f8561f0b357af329769bf8} 
    9192 
    9293\item  
    93 sq\_\-T \textbf{\_\-Ry}\label{classKalman_477dca07d91ea1a1f41d51bb0229934f} 
     94sq\_\-T $\ast$ \textbf{\_\-Ry}\label{classKalman_e17dd745daa8a958035a334a56fa4674} 
    9495 
    9596\item  
    96 sq\_\-T \textbf{\_\-iRy}\label{classKalman_15f1a793210750a7e4642fcd948b24c5} 
     97sq\_\-T $\ast$ \textbf{\_\-iRy}\label{classKalman_fbbdf31365f5a5674099599200ea193b} 
    9798 
    98 \end{CompactItemize} 
    99 \subsection*{Friends} 
    100 \begin{CompactItemize} 
    10199\item  
    102 std::ostream \& \textbf{operator$<$$<$} (std::ostream \&os, const {\bf KalmanFull} \&kf)\label{classKalman_86ba216243ed95bb46d80d88775d16af} 
     100vec $\ast$ \textbf{\_\-mu}\label{classKalman_d1f669b5b3421a070cc75d77b55ba734} 
    103101 
    104 \end{CompactItemize} 
     102\item  
     103sq\_\-T $\ast$ \textbf{\_\-P}\label{classKalman_b3388218567128a797e69b109138271d} 
     104 
     105\item  
     106sq\_\-T $\ast$ \textbf{\_\-iP}\label{classKalman_b8bb7f870d69993493ba67ce40e7c3e9} 
     107 
     108\item  
     109{\bf RV} {\bf rv}\label{classBM_af00f0612fabe66241dd507188cdbf88} 
     110 
     111\begin{CompactList}\small\item\em Random variable of the posterior. \item\end{CompactList}\item  
     112double {\bf ll}\label{classBM_5623fef6572a08c2b53b8c87b82dc979} 
     113 
     114\begin{CompactList}\small\item\em Logarithm of marginalized data likelihood. \item\end{CompactList}\item  
     115bool {\bf evalll}\label{classBM_bf6fb59b30141074f8ee1e2f43d03129} 
     116 
     117\begin{CompactList}\small\item\em If true, the filter will compute likelihood of the data record and store it in {\tt ll} . Set to false if you want to save time. \item\end{CompactList}\end{CompactItemize} 
    105118 
    106119 
    … …  
    110123\doxyref{Kalman}{p.}{classKalman} filter with covariance matrices in square root form.  
    111124 
    112 \subsection{Member Function Documentation} 
    113 \index{Kalman@{Kalman}!bayes@{bayes}} 
    114 \index{bayes@{bayes}!Kalman@{Kalman}} 
    115 \subsubsection{\setlength{\rightskip}{0pt plus 5cm}virtual void BM::bayes (const vec \& {\em dt})\hspace{0.3cm}{\tt  [pure virtual, inherited]}}\label{classBM_a892eff438aab2dd1a9e2efcb7fb5bdf} 
    116  
    117  
    118 Incremental Bayes rule.  
    119  
    120 \begin{Desc} 
    121 \item[Parameters:] 
    122 \begin{description} 
    123 \item[{\em dt}]vector of input data \end{description} 
    124 \end{Desc} 
    125  
    126  
    127125The documentation for this class was generated from the following file:\begin{CompactItemize} 
    128126\item  

  • doc/latex/classKalmanFull.tex

    r28 r32  
    66{\tt \#include $<$libKF.h$>$} 
    77 
    8 Inheritance diagram for KalmanFull:\nopagebreak 
    9 \begin{figure}[H] 
    10 \begin{center} 
    11 \leavevmode 
    12 \includegraphics[width=56pt]{classKalmanFull__inherit__graph} 
    13 \end{center} 
    14 \end{figure} 
    15 Collaboration diagram for KalmanFull:\nopagebreak 
    16 \begin{figure}[H] 
    17 \begin{center} 
    18 \leavevmode 
    19 \includegraphics[width=56pt]{classKalmanFull__coll__graph} 
    20 \end{center} 
    21 \end{figure} 
    228\subsection*{Public Member Functions} 
    239\begin{CompactItemize} 
    … …  
    2612 
    2713\begin{CompactList}\small\item\em Full constructor. \item\end{CompactList}\item  
    28 void {\bf bayes} (const vec \&dt, bool {\bf evalll}=true)\label{classKalmanFull_048b13739b94c331cda08249b278552b} 
     14void {\bf bayes} (const vec \&dt)\label{classKalmanFull_13a041cd98ff157703766be275a657bb} 
    2915 
    30 \begin{CompactList}\small\item\em Here dt = [yt;ut] of appropriate dimensions. \item\end{CompactList}\item  
    31 virtual void {\bf bayes} (const vec \&dt)=0 
    32 \begin{CompactList}\small\item\em Incremental Bayes rule. \item\end{CompactList}\item  
    33 void {\bf bayes} (mat Dt)\label{classBM_87b07867fd4c133aa89a18543f68d9f9} 
    34  
    35 \begin{CompactList}\small\item\em Batch Bayes rule (columns of Dt are observations). \item\end{CompactList}\item  
    36 {\bf epdf} $\ast$ {\bf \_\-epdf} ()\label{classBM_a5b8f6c8a872738cfaa30ab010e8c077} 
    37  
    38 \begin{CompactList}\small\item\em Returns a pointer to the \doxyref{epdf}{p.}{classepdf} representing posterior density on parameters. Use with care! \item\end{CompactList}\end{CompactItemize} 
     16\begin{CompactList}\small\item\em Here dt = [yt;ut] of appropriate dimensions. \item\end{CompactList}\end{CompactItemize} 
    3917\subsection*{Public Attributes} 
    4018\begin{CompactItemize} 
    … …  
    4523mat {\bf P}\label{classKalmanFull_b75dc059e84fa8ffc076203b30f926cc} 
    4624 
    47 \begin{CompactList}\small\item\em Variance of the posterior density. \item\end{CompactList}\item  
    48 double {\bf ll}\label{classBM_5623fef6572a08c2b53b8c87b82dc979} 
    49  
    50 \begin{CompactList}\small\item\em Logarithm of marginalized data likelihood. \item\end{CompactList}\item  
    51 bool {\bf evalll}\label{classBM_bf6fb59b30141074f8ee1e2f43d03129} 
    52  
    53 \begin{CompactList}\small\item\em If true, the filter will compute likelihood of the data record and store it in {\tt ll} . Set to false if you want to save time. \item\end{CompactList}\end{CompactItemize} 
     25\begin{CompactList}\small\item\em Variance of the posterior density. \item\end{CompactList}\end{CompactItemize} 
    5426\subsection*{Friends} 
    5527\begin{CompactItemize} 
    … …  
    6335Basic \doxyref{Kalman}{p.}{classKalman} filter with full matrices (education purpose only)! Will be deleted soon!  
    6436 
    65 \subsection{Member Function Documentation} 
    66 \index{KalmanFull@{KalmanFull}!bayes@{bayes}} 
    67 \index{bayes@{bayes}!KalmanFull@{KalmanFull}} 
    68 \subsubsection{\setlength{\rightskip}{0pt plus 5cm}virtual void BM::bayes (const vec \& {\em dt})\hspace{0.3cm}{\tt  [pure virtual, inherited]}}\label{classBM_a892eff438aab2dd1a9e2efcb7fb5bdf} 
    69  
    70  
    71 Incremental Bayes rule.  
    72  
    73 \begin{Desc} 
    74 \item[Parameters:] 
    75 \begin{description} 
    76 \item[{\em dt}]vector of input data \end{description} 
    77 \end{Desc} 
    78  
    79  
    8037The documentation for this class was generated from the following files:\begin{CompactItemize} 
    8138\item  

  • doc/latex/classPF.tex

    r28 r32  
    11\section{PF Class Reference} 
    22\label{classPF}\index{PF@{PF}} 
    3 A Particle Filter prototype.   
     3Trivial particle filter with proposal density equal to parameter evolution model.   
    44 
    55 
    … …  
    1010\begin{center} 
    1111\leavevmode 
    12 \includegraphics[width=49pt]{classPF__inherit__graph} 
     12\includegraphics[width=65pt]{classPF__inherit__graph} 
    1313\end{center} 
    1414\end{figure} 
    … …  
    1717\begin{center} 
    1818\leavevmode 
    19 \includegraphics[width=38pt]{classPF__coll__graph} 
     19\includegraphics[width=96pt]{classPF__coll__graph} 
    2020\end{center} 
    2121\end{figure} 
    … …  
    2323\begin{CompactItemize} 
    2424\item  
    25 ivec {\bf resample} (RESAMPLING\_\-METHOD method=SYSTEMATIC)\label{classPF_a0e26b2f6a5884aca49122f3e4f0cf19} 
    26  
    27 \begin{CompactList}\small\item\em Returns indexes of particles that should be resampled. The ordering MUST guarantee inplace replacement. (Important for MPF.). \item\end{CompactList}\item  
    28 \textbf{PF} (vec w)\label{classPF_c37f95f0c1661c7f1e3fccb31d39de73} 
     25\textbf{PF} (const {\bf RV} \&rv0, {\bf mpdf} \&par0, {\bf mpdf} \&obs0, int {\bf n})\label{classPF_e9604b7fc87ff5e61da4de4a04210bfc} 
    2926 
    3027\item  
    31 void \textbf{bayes} (const vec \&dt, bool evell)\label{classPF_eb06bd7d4325f22f54233967295793b9} 
     28void \textbf{set\_\-est} (const {\bf epdf} $\ast$\&epdf0)\label{classPF_c5caa2c15604338b773d7a8125e7a1b5} 
    3229 
    3330\item  
    34 virtual void {\bf bayes} (const vec \&dt)=0 
     31void {\bf bayes} (const vec \&dt) 
    3532\begin{CompactList}\small\item\em Incremental Bayes rule. \item\end{CompactList}\item  
    3633void {\bf bayes} (mat Dt)\label{classBM_87b07867fd4c133aa89a18543f68d9f9} 
    3734 
    3835\begin{CompactList}\small\item\em Batch Bayes rule (columns of Dt are observations). \item\end{CompactList}\item  
    39 {\bf epdf} $\ast$ {\bf \_\-epdf} ()\label{classBM_a5b8f6c8a872738cfaa30ab010e8c077} 
     36virtual {\bf epdf} \& {\bf \_\-epdf} ()=0\label{classBM_3dc45554556926bde996a267636abe55} 
    4037 
    4138\begin{CompactList}\small\item\em Returns a pointer to the \doxyref{epdf}{p.}{classepdf} representing posterior density on parameters. Use with care! \item\end{CompactList}\end{CompactItemize} 
    42 \subsection*{Public Attributes} 
     39\subsection*{Protected Attributes} 
    4340\begin{CompactItemize} 
    4441\item  
     42int {\bf n}\label{classPF_2c2f44ed7a4eaa42e07bdb58d503f280} 
     43 
     44\begin{CompactList}\small\item\em number of particles; \item\end{CompactList}\item  
     45{\bf eEmp} {\bf ePdf}\label{classPF_a2ac56d1e3ffbb4ff0b3f02e6399deb0} 
     46 
     47\begin{CompactList}\small\item\em posterior density \item\end{CompactList}\item  
     48vec \& {\bf w}\label{classPF_a97d12da4d1832c0b0c6ec5877f921f0} 
     49 
     50\begin{CompactList}\small\item\em pointer into {\tt \doxyref{eEmp}{p.}{classeEmp}} \item\end{CompactList}\item  
     51Array$<$ vec $>$ \& {\bf samples}\label{classPF_361743a0b5b89de1a29e91d1343b2565} 
     52 
     53\begin{CompactList}\small\item\em pointer into {\tt \doxyref{eEmp}{p.}{classeEmp}} \item\end{CompactList}\item  
     54{\bf mpdf} \& {\bf par}\label{classPF_d92ac103f88f8c21e197e90af5695a09} 
     55 
     56\begin{CompactList}\small\item\em Parameter evolution model. \item\end{CompactList}\item  
     57{\bf mpdf} \& {\bf obs}\label{classPF_dd0a687a4515333d6809147335854e77} 
     58 
     59\begin{CompactList}\small\item\em Observation model. \item\end{CompactList}\item  
     60{\bf RV} {\bf rv}\label{classBM_af00f0612fabe66241dd507188cdbf88} 
     61 
     62\begin{CompactList}\small\item\em Random variable of the posterior. \item\end{CompactList}\item  
    4563double {\bf ll}\label{classBM_5623fef6572a08c2b53b8c87b82dc979} 
    4664 
    … …  
    4967 
    5068\begin{CompactList}\small\item\em If true, the filter will compute likelihood of the data record and store it in {\tt ll} . Set to false if you want to save time. \item\end{CompactList}\end{CompactItemize} 
    51 \subsection*{Protected Attributes} 
    52 \begin{CompactItemize} 
    53 \item  
    54 int \textbf{n}\label{classPF_2c2f44ed7a4eaa42e07bdb58d503f280} 
    55  
    56 \item  
    57 vec \textbf{w}\label{classPF_f6bc92f7979af4513b06b161497ba868} 
    58  
    59 \item  
    60 Uniform\_\-RNG \textbf{URNG}\label{classPF_3568ca7c3b3175d98b548f496b4c34dd} 
    61  
    62 \end{CompactItemize} 
    6369 
    6470 
    6571\subsection{Detailed Description} 
    66 A Particle Filter prototype.  
     72Trivial particle filter with proposal density equal to parameter evolution model.  
    6773 
    68 Bayesian Filtering equations hold.  
     74Posterior density is represented by a weighted empirical density ({\tt \doxyref{eEmp}{p.}{classeEmp}} ).  
    6975 
    7076\subsection{Member Function Documentation} 
    7177\index{PF@{PF}!bayes@{bayes}} 
    7278\index{bayes@{bayes}!PF@{PF}} 
    73 \subsubsection{\setlength{\rightskip}{0pt plus 5cm}virtual void BM::bayes (const vec \& {\em dt})\hspace{0.3cm}{\tt  [pure virtual, inherited]}}\label{classBM_a892eff438aab2dd1a9e2efcb7fb5bdf} 
     79\subsubsection{\setlength{\rightskip}{0pt plus 5cm}void PF::bayes (const vec \& {\em dt})\hspace{0.3cm}{\tt  [virtual]}}\label{classPF_64f636bbd63bea9efd778214e6b631d3} 
    7480 
    7581 
    … …  
    8389 
    8490 
     91Implements {\bf BM} \doxyref{}{p.}{classBM_a892eff438aab2dd1a9e2efcb7fb5bdf}. 
     92 
     93Reimplemented in {\bf MPF$<$ BM\_\-T $>$} \doxyref{}{p.}{classMPF_55daf8e4b6553dd9f47c692de7931623}. 
     94 
    8595The documentation for this class was generated from the following files:\begin{CompactItemize} 
    8696\item  

  • doc/latex/classRV.tex

    r22 r32  
    2424 
    2525\begin{CompactList}\small\item\em Find indexes of another rv in self. \item\end{CompactList}\item  
    26 {\bf RV} {\bf add} ({\bf RV} rv2)\label{classRV_f068a86abb5a6e46fcf76c939d2ed2ec} 
     26{\bf RV} {\bf add} (const {\bf RV} \&rv2)\label{classRV_18fa114b92017f7f80301a4f8d3a6382} 
    2727 
    2828\begin{CompactList}\small\item\em Add (concat) another variable to the current one. \item\end{CompactList}\item  
    … …  
    4242 
    4343\begin{CompactList}\small\item\em generate a list of indeces, i.e. which \item\end{CompactList}\end{CompactItemize} 
     44\subsection*{Protected Attributes} 
     45\begin{CompactItemize} 
     46\item  
     47int {\bf size}\label{classRV_0cae53d262be90a775a99a198e17fa58} 
     48 
     49\begin{CompactList}\small\item\em size = sum of sizes \item\end{CompactList}\item  
     50int {\bf len}\label{classRV_0d7b36e2bbccf880c8fcf1e8cc43c1a9} 
     51 
     52\begin{CompactList}\small\item\em len = number of individual rvs \item\end{CompactList}\item  
     53ivec \textbf{ids}\label{classRV_1bd7165140f4b880a7f344bbb1c433f9} 
     54 
     55\item  
     56ivec \textbf{sizes}\label{classRV_c878aab13f34b420e1eb5b485563682b} 
     57 
     58\item  
     59ivec \textbf{times}\label{classRV_646e530c47a2dd38254b778d9f11ac89} 
     60 
     61\item  
     62ivec \textbf{obs}\label{classRV_2999743deec9b4cdb7ce51747bc53319} 
     63 
     64\item  
     65Array$<$ std::string $>$ \textbf{names}\label{classRV_df5d0030b277a1db2f1fd5fb79152acb} 
     66 
     67\end{CompactItemize} 
    4468\subsection*{Friends} 
    4569\begin{CompactItemize} 

  • doc/latex/classTrivialPF.tex

    r28 r32  
    3535 
    3636\begin{CompactList}\small\item\em Returns indexes of particles that should be resampled. The ordering MUST guarantee inplace replacement. (Important for MPF.). \item\end{CompactList}\item  
    37 virtual void {\bf bayes} (const vec \&dt)=0 
     37void {\bf bayes} (const vec \&dt) 
    3838\begin{CompactList}\small\item\em Incremental Bayes rule. \item\end{CompactList}\item  
    3939void {\bf bayes} (mat Dt)\label{classBM_87b07867fd4c133aa89a18543f68d9f9} 
    4040 
    4141\begin{CompactList}\small\item\em Batch Bayes rule (columns of Dt are observations). \item\end{CompactList}\item  
    42 {\bf epdf} $\ast$ {\bf \_\-epdf} ()\label{classBM_a5b8f6c8a872738cfaa30ab010e8c077} 
     42{\bf epdf} $\ast$ {\bf \_\-epdf} ()\label{classPF_53b7cc5a0709b0d40fb68408437c0aa2} 
    4343 
    4444\begin{CompactList}\small\item\em Returns a pointer to the \doxyref{epdf}{p.}{classepdf} representing posterior density on parameters. Use with care! \item\end{CompactList}\end{CompactItemize} 
    … …  
    7272\index{TrivialPF@{TrivialPF}!bayes@{bayes}} 
    7373\index{bayes@{bayes}!TrivialPF@{TrivialPF}} 
    74 \subsubsection{\setlength{\rightskip}{0pt plus 5cm}virtual void BM::bayes (const vec \& {\em dt})\hspace{0.3cm}{\tt  [pure virtual, inherited]}}\label{classBM_a892eff438aab2dd1a9e2efcb7fb5bdf} 
     74\subsubsection{\setlength{\rightskip}{0pt plus 5cm}void PF::bayes (const vec \& {\em dt})\hspace{0.3cm}{\tt  [inline, virtual, inherited]}}\label{classPF_64f636bbd63bea9efd778214e6b631d3} 
    7575 
    7676 
    … …  
    8484 
    8585 
     86Implements {\bf BM} \doxyref{}{p.}{classBM_a892eff438aab2dd1a9e2efcb7fb5bdf}. 
     87 
    8688The documentation for this class was generated from the following files:\begin{CompactItemize} 
    8789\item  

  • doc/latex/classeEF.tex

    r28 r32  
    1010\begin{center} 
    1111\leavevmode 
    12 \includegraphics[width=67pt]{classeEF__inherit__graph} 
     12\includegraphics[width=127pt]{classeEF__inherit__graph} 
    1313\end{center} 
    1414\end{figure} 
    … …  
    2323\begin{CompactItemize} 
    2424\item  
     25{\bf eEF} ()\label{classeEF_702e24158366430bc24d57c7f64e1e9e} 
     26 
     27\begin{CompactList}\small\item\em default constructor \item\end{CompactList}\item  
     28\textbf{eEF} (const {\bf RV} \&rv)\label{classeEF_7e3c63655e8375c76bf1f421245427a7} 
     29 
     30\item  
    2531virtual void \textbf{tupdate} (double phi, mat \&vbar, double nubar)\label{classeEF_fd88bc35550ec8fe9281d358216d0fcf} 
    2632 
    … …  
    3339virtual double {\bf eval} (const vec \&val)\label{classepdf_f333ceeb88ebc37d81fcd4cea4526bfc} 
    3440 
    35 \begin{CompactList}\small\item\em Compute probability of argument {\tt val}. \item\end{CompactList}\end{CompactItemize} 
     41\begin{CompactList}\small\item\em Compute probability of argument {\tt val}. \item\end{CompactList}\item  
     42virtual double {\bf evalpdflog} (const vec \&val)\label{classepdf_113c76c61d20e3f2a24ba322a73dfc51} 
     43 
     44\begin{CompactList}\small\item\em Compute log-probability of argument {\tt val}. \item\end{CompactList}\item  
     45virtual vec {\bf mean} ()=0\label{classepdf_5b61fae74d370d2216576d598c1a74ef} 
     46 
     47\begin{CompactList}\small\item\em return expected value \item\end{CompactList}\end{CompactItemize} 
     48\subsection*{Protected Attributes} 
     49\begin{CompactItemize} 
     50\item  
     51{\bf RV} \textbf{rv}\label{classepdf_74da992e3f5d598da8850b646b79b9d9} 
     52 
     53\end{CompactItemize} 
    3654 
    3755 
    … …  
    5169Returns a sample from the density, $x \sim epdf(rv)$  
    5270 
    53 Implemented in {\bf enorm$<$ sq\_\-T $>$} \doxyref{}{p.}{classenorm_6020bcd89db2c9584bd8871001bd2023}. 
     71Implemented in {\bf enorm$<$ sq\_\-T $>$} \doxyref{}{p.}{classenorm_6020bcd89db2c9584bd8871001bd2023}, {\bf egamma} \doxyref{}{p.}{classegamma_0a2186a586432c2c3f22d09c5341890f}, {\bf emix} \doxyref{}{p.}{classemix_3eb9a8e12ce1c5c8a3ddb245354b6941}, {\bf euni} \doxyref{}{p.}{classeuni_0f71562e3e919aba823cb7d9d420ad4c}, {\bf eEmp} \doxyref{}{p.}{classeEmp_c9b44099a400579b88aff9f5afaf9c13}, and {\bf enorm$<$ ldmat $>$} \doxyref{}{p.}{classenorm_6020bcd89db2c9584bd8871001bd2023}. 
    5472 
    5573The documentation for this class was generated from the following file:\begin{CompactItemize} 

  • doc/latex/classenorm.tex

    r22 r32  
    1010\begin{center} 
    1111\leavevmode 
    12 \includegraphics[width=67pt]{classenorm__inherit__graph} 
     12\includegraphics[width=71pt]{classenorm__inherit__graph} 
    1313\end{center} 
    1414\end{figure} 
    … …  
    2323\begin{CompactItemize} 
    2424\item  
    25 \textbf{enorm} ({\bf RV} \&rv, vec \&mu, sq\_\-T \&R)\label{classenorm_183891111686898adef0f6ca292e600d} 
     25\textbf{enorm} ({\bf RV} \&rv)\label{classenorm_7b5cb487a2570e8109bfdc0df149aa06} 
     26 
     27\item  
     28void \textbf{set\_\-parameters} (const vec \&{\bf mu}, const sq\_\-T \&{\bf R})\label{classenorm_1394a65caa6e00d42e00cc99b12227af} 
    2629 
    2730\item  
    … …  
    3235 
    3336\item  
    34 void {\bf tupdate} ()\label{classenorm_2a1a522504c7788dfd7fb733157ee39e} 
    35  
    36 \begin{CompactList}\small\item\em tupdate used in KF \item\end{CompactList}\item  
    37 double {\bf dupdate} ()\label{classenorm_d1b0faf61260de09cf63bf823add5b32} 
    38  
    39 \begin{CompactList}\small\item\em dupdate used in KF \item\end{CompactList}\item  
    4037vec {\bf sample} () 
    4138\begin{CompactList}\small\item\em Returns the required moment of the \doxyref{epdf}{p.}{classepdf}. \item\end{CompactList}\item  
    … …  
    4542double {\bf eval} (const vec \&val)\label{classenorm_93107f05a8e9b34b64853767200121a4} 
    4643 
    47 \begin{CompactList}\small\item\em Compute probability of argument {\tt val}. \item\end{CompactList}\end{CompactItemize} 
    48 \subsection*{Public Attributes} 
     44\begin{CompactList}\small\item\em Compute probability of argument {\tt val}. \item\end{CompactList}\item  
     45double {\bf evalpdflog} (const vec \&val)\label{classenorm_9517594915e897584eaebbb057ed8881} 
     46 
     47\begin{CompactList}\small\item\em Compute log-probability of argument {\tt val}. \item\end{CompactList}\item  
     48vec {\bf mean} ()\label{classenorm_191c1220c3ddd0c5f54e78f19b57ebd5} 
     49 
     50\begin{CompactList}\small\item\em return expected value \item\end{CompactList}\item  
     51vec $\ast$ {\bf \_\-mu} ()\label{classenorm_3be0cb541ec9b88e5aa3f60307bbc753} 
     52 
     53\begin{CompactList}\small\item\em returns a pointer to the internal mean value. Use with Care! \item\end{CompactList}\item  
     54void {\bf \_\-R} (sq\_\-T $\ast$\&pR, sq\_\-T $\ast$\&piR)\label{classenorm_8725c534863c4fc2bddef0edfb95a740} 
     55 
     56\begin{CompactList}\small\item\em returns pointers to the internal variance and its inverse. Use with Care! \item\end{CompactList}\item  
     57void {\bf \_\-cached} (bool what)\label{classenorm_c9ca4f2ca42568e40ca146168e7f3247} 
     58 
     59\begin{CompactList}\small\item\em set cache as inconsistent \item\end{CompactList}\end{CompactItemize} 
     60\subsection*{Protected Attributes} 
    4961\begin{CompactItemize} 
    5062\item  
    51 Normal\_\-RNG \textbf{RNG}\label{classenorm_a4de82a0d7ba9eaf31206318ae35d0d5} 
     63vec {\bf mu}\label{classenorm_71fde0d54bba147e00f612577f95ad20} 
     64 
     65\begin{CompactList}\small\item\em mean value \item\end{CompactList}\item  
     66sq\_\-T {\bf R}\label{classenorm_4ccc8d8514d644ef1c98d8ab023748a1} 
     67 
     68\begin{CompactList}\small\item\em Covariance matrix in decomposed form. \item\end{CompactList}\item  
     69sq\_\-T {\bf \_\-iR}\label{classenorm_82f39ac49911d7097f4bfe385deba355} 
     70 
     71\begin{CompactList}\small\item\em Cache: \_\-iR = inv(R);. \item\end{CompactList}\item  
     72bool {\bf cached}\label{classenorm_ae12db77283a96e0f14a3eae93dc3bf1} 
     73 
     74\begin{CompactList}\small\item\em indicator if {\tt \_\-iR} is chached \item\end{CompactList}\item  
     75int {\bf dim}\label{classenorm_6938fc390a19cdaf6ad4503fcbaada4e} 
     76 
     77\begin{CompactList}\small\item\em dimension (redundant from rv.count() for easier coding ) \item\end{CompactList}\item  
     78{\bf RV} \textbf{rv}\label{classepdf_74da992e3f5d598da8850b646b79b9d9} 
    5279 
    5380\end{CompactItemize} 

  • doc/latex/classepdf.tex

    r22 r32  
    1010\begin{center} 
    1111\leavevmode 
    12 \includegraphics[width=67pt]{classepdf__inherit__graph} 
     12\includegraphics[width=179pt]{classepdf__inherit__graph} 
    1313\end{center} 
    1414\end{figure} 
    … …  
    2323\begin{CompactItemize} 
    2424\item  
     25{\bf epdf} ()\label{classepdf_d8eb760037b3bad5a0d64081606697cd} 
     26 
     27\begin{CompactList}\small\item\em default constructor \item\end{CompactList}\item  
     28{\bf epdf} (const {\bf RV} \&rv0)\label{classepdf_c95b1a27a8dd9507bb9a5a3cb2809c7a} 
     29 
     30\begin{CompactList}\small\item\em default constructor \item\end{CompactList}\item  
    2531virtual vec {\bf sample} ()=0 
    2632\begin{CompactList}\small\item\em Returns the required moment of the \doxyref{epdf}{p.}{classepdf}. \item\end{CompactList}\item  
    2733virtual double {\bf eval} (const vec \&val)\label{classepdf_f333ceeb88ebc37d81fcd4cea4526bfc} 
    2834 
    29 \begin{CompactList}\small\item\em Compute probability of argument {\tt val}. \item\end{CompactList}\end{CompactItemize} 
     35\begin{CompactList}\small\item\em Compute probability of argument {\tt val}. \item\end{CompactList}\item  
     36virtual double {\bf evalpdflog} (const vec \&val)\label{classepdf_113c76c61d20e3f2a24ba322a73dfc51} 
     37 
     38\begin{CompactList}\small\item\em Compute log-probability of argument {\tt val}. \item\end{CompactList}\item  
     39virtual vec {\bf mean} ()=0\label{classepdf_5b61fae74d370d2216576d598c1a74ef} 
     40 
     41\begin{CompactList}\small\item\em return expected value \item\end{CompactList}\item  
     42virtual {\bf $\sim$epdf} ()\label{classepdf_0a322dd106f04c0a2915e3d4f4227396} 
     43 
     44\begin{CompactList}\small\item\em Destructor for future use;. \item\end{CompactList}\end{CompactItemize} 
     45\subsection*{Protected Attributes} 
     46\begin{CompactItemize} 
     47\item  
     48{\bf RV} \textbf{rv}\label{classepdf_74da992e3f5d598da8850b646b79b9d9} 
     49 
     50\end{CompactItemize} 
    3051 
    3152 
    … …  
    4364Returns a sample from the density, $x \sim epdf(rv)$  
    4465 
    45 Implemented in {\bf enorm$<$ sq\_\-T $>$} \doxyref{}{p.}{classenorm_6020bcd89db2c9584bd8871001bd2023}. 
     66Implemented in {\bf enorm$<$ sq\_\-T $>$} \doxyref{}{p.}{classenorm_6020bcd89db2c9584bd8871001bd2023}, {\bf egamma} \doxyref{}{p.}{classegamma_0a2186a586432c2c3f22d09c5341890f}, {\bf emix} \doxyref{}{p.}{classemix_3eb9a8e12ce1c5c8a3ddb245354b6941}, {\bf euni} \doxyref{}{p.}{classeuni_0f71562e3e919aba823cb7d9d420ad4c}, {\bf eEmp} \doxyref{}{p.}{classeEmp_c9b44099a400579b88aff9f5afaf9c13}, and {\bf enorm$<$ ldmat $>$} \doxyref{}{p.}{classenorm_6020bcd89db2c9584bd8871001bd2023}. 
    4667 
    4768The documentation for this class was generated from the following file:\begin{CompactItemize} 

  • doc/latex/classfnc.tex

    r28 r32  
    2121int {\bf \_\-dimy} () const \label{classfnc_a8891973d0ca48ce38e1886df45ca298} 
    2222 
    23 \begin{CompactList}\small\item\em access function \item\end{CompactList}\end{CompactItemize} 
     23\begin{CompactList}\small\item\em access function \item\end{CompactList}\item  
     24virtual {\bf $\sim$fnc} ()\label{classfnc_17164c202f6feee3d708b8caab6306ab} 
     25 
     26\begin{CompactList}\small\item\em Destructor for future use;. \item\end{CompactList}\end{CompactItemize} 
    2427\subsection*{Protected Attributes} 
    2528\begin{CompactItemize} 

  • doc/latex/classfsqmat.tex

    r28 r32  
    2828 
    2929\begin{CompactList}\small\item\em Conversion to full matrix. \item\end{CompactList}\item  
    30 void {\bf mult\_\-sym} (const mat \&C, bool trans=false) 
     30void {\bf mult\_\-sym} (const mat \&C) 
    3131\begin{CompactList}\small\item\em Inplace symmetric multiplication by a SQUARE matrix \$C\$, i.e. \$V = C$\ast$V$\ast$C'\$. \item\end{CompactList}\item  
    32 void \textbf{mult\_\-sym} (const mat \&C, {\bf fsqmat} \&U, bool trans=false)\label{classfsqmat_ccf5ad8fb038f82e9d2201c0606b65fa} 
     32void {\bf mult\_\-sym\_\-t} (const mat \&C) 
     33\begin{CompactList}\small\item\em Inplace symmetric multiplication by a SQUARE transpose of matrix \$C\$, i.e. \$V = C'$\ast$V$\ast$C\$. \item\end{CompactList}\item  
     34void \textbf{mult\_\-sym} (const mat \&C, {\bf fsqmat} \&U)\label{classfsqmat_cfea3618d426e2b8232f09aa0070266f} 
     35 
     36\item  
     37void \textbf{mult\_\-sym\_\-t} (const mat \&C, {\bf fsqmat} \&U)\label{classfsqmat_7ca865c68989d22903efe97045cb6c9a} 
    3338 
    3439\item  
    … …  
    3641 
    3742\begin{CompactList}\small\item\em Clearing matrix so that it corresponds to zeros. \item\end{CompactList}\item  
     43{\bf fsqmat} ()\label{classfsqmat_79e3f73e0ccd663c7f7e08083d272940} 
     44 
     45\begin{CompactList}\small\item\em Default initialization. \item\end{CompactList}\item  
     46{\bf fsqmat} (const int dim0)\label{classfsqmat_40eae99305e7c7240fa95cfec125b06f} 
     47 
     48\begin{CompactList}\small\item\em Default initialization with proper size. \item\end{CompactList}\item  
    3849{\bf fsqmat} (const mat \&M)\label{classfsqmat_1929fbc9fe375f1d67f979d0d302336f} 
    3950 
    4051\begin{CompactList}\small\item\em Constructor. \item\end{CompactList}\item  
     52virtual {\bf $\sim$fsqmat} ()\label{classfsqmat_2a8f104e4befbc2aa90d8b11edfedb2e} 
     53 
     54\begin{CompactList}\small\item\em Destructor for future use;. \item\end{CompactList}\item  
    4155virtual void {\bf inv} ({\bf fsqmat} \&Inv) 
    4256\begin{CompactList}\small\item\em Matrix inversion preserving the chosen form. \item\end{CompactList}\item  
    43 double {\bf logdet} ()\label{classfsqmat_bf212272ec195ad2706e2bf4d8e7c9b3} 
     57double {\bf logdet} () const \label{classfsqmat_eb0d1358f536e4453b5f99d0418ca1e5} 
    4458 
    4559\begin{CompactList}\small\item\em Logarithm of a determinant. \item\end{CompactList}\item  
    46 double {\bf qform} (vec \&v)\label{classfsqmat_6d047b9f7a27dfc093303a13cc9b1fba} 
     60double {\bf qform} (const vec \&v)\label{classfsqmat_1eec8762a2299d83c7b7cd6bf6cbc1ad} 
    4761 
    4862\begin{CompactList}\small\item\em Evaluates quadratic form \$x= v'$\ast$V$\ast$v\$;. \item\end{CompactList}\item  
    49 vec {\bf sqrt\_\-mult} (vec \&v) 
     63vec {\bf sqrt\_\-mult} (const vec \&v) 
    5064\begin{CompactList}\small\item\em Multiplies square root of \$V\$ by vector \$x\$. \item\end{CompactList}\item  
    5165{\bf fsqmat} \& \textbf{operator+=} (const {\bf fsqmat} \&A)\label{classfsqmat_514d1fdd8a382dbd6a774f2cf1ebd3de} 
    … …  
    7387 
    7488\end{CompactItemize} 
     89\subsection*{Friends} 
     90\begin{CompactItemize} 
     91\item  
     92std::ostream \& \textbf{operator$<$$<$} (std::ostream \&os, const {\bf fsqmat} \&sq)\label{classfsqmat_e06aba54d61e807b41bd68b5ee6ac22f} 
     93 
     94\end{CompactItemize} 
    7595 
    7696 
    … …  
    95115Implements {\bf sqmat} \doxyref{}{p.}{classsqmat_b223484796661f2dadb5607a86ce0581}.\index{fsqmat@{fsqmat}!mult_sym@{mult\_\-sym}} 
    96116\index{mult_sym@{mult\_\-sym}!fsqmat@{fsqmat}} 
    97 \subsubsection{\setlength{\rightskip}{0pt plus 5cm}void fsqmat::mult\_\-sym (const mat \& {\em C}, bool {\em trans} = {\tt false})\hspace{0.3cm}{\tt  [virtual]}}\label{classfsqmat_acc5d2d0a243f1de6d0106065f01f518} 
     117\subsubsection{\setlength{\rightskip}{0pt plus 5cm}void fsqmat::mult\_\-sym (const mat \& {\em C})\hspace{0.3cm}{\tt  [virtual]}}\label{classfsqmat_5530d2756b5d991de755e6121c9a452e} 
    98118 
    99119 
    … …  
    103123\item[Parameters:] 
    104124\begin{description} 
    105 \item[{\em C}]multiplying matrix, \item[{\em trans}]if true, product \$V = C'$\ast$V$\ast$C\$ will be computed instead; \end{description} 
     125\item[{\em C}]multiplying matrix, \end{description} 
    106126\end{Desc} 
    107127 
    108128 
    109 Implements {\bf sqmat} \doxyref{}{p.}{classsqmat_faa3bc90be142adde9cf74f573c70157}.\index{fsqmat@{fsqmat}!inv@{inv}} 
     129Implements {\bf sqmat} \doxyref{}{p.}{classsqmat_60fbbfa9e483b8187c135f787ee53afa}.\index{fsqmat@{fsqmat}!mult_sym_t@{mult\_\-sym\_\-t}} 
     130\index{mult_sym_t@{mult\_\-sym\_\-t}!fsqmat@{fsqmat}} 
     131\subsubsection{\setlength{\rightskip}{0pt plus 5cm}void fsqmat::mult\_\-sym\_\-t (const mat \& {\em C})\hspace{0.3cm}{\tt  [virtual]}}\label{classfsqmat_92052a8adc2054b63e42d1373d145c89} 
     132 
     133 
     134Inplace symmetric multiplication by a SQUARE transpose of matrix \$C\$, i.e. \$V = C'$\ast$V$\ast$C\$.  
     135 
     136\begin{Desc} 
     137\item[Parameters:] 
     138\begin{description} 
     139\item[{\em C}]multiplying matrix, \end{description} 
     140\end{Desc} 
     141 
     142 
     143Implements {\bf sqmat} \doxyref{}{p.}{classsqmat_6909e906da17725b1b80f3cae7cf3325}.\index{fsqmat@{fsqmat}!inv@{inv}} 
    110144\index{inv@{inv}!fsqmat@{fsqmat}} 
    111145\subsubsection{\setlength{\rightskip}{0pt plus 5cm}void fsqmat::inv ({\bf fsqmat} \& {\em Inv})\hspace{0.3cm}{\tt  [virtual]}}\label{classfsqmat_9fa853e1ca28f2a1a1c43377e798ecb1} 
    … …  
    121155\index{fsqmat@{fsqmat}!sqrt_mult@{sqrt\_\-mult}} 
    122156\index{sqrt_mult@{sqrt\_\-mult}!fsqmat@{fsqmat}} 
    123 \subsubsection{\setlength{\rightskip}{0pt plus 5cm}vec fsqmat::sqrt\_\-mult (vec \& {\em v})\hspace{0.3cm}{\tt  [inline, virtual]}}\label{classfsqmat_6648dd4291b809cce14e8497d0433ad3} 
     157\subsubsection{\setlength{\rightskip}{0pt plus 5cm}vec fsqmat::sqrt\_\-mult (const vec \& {\em v})\hspace{0.3cm}{\tt  [inline, virtual]}}\label{classfsqmat_2288389e2d47bd9df112815ef570c5c9} 
    124158 
    125159 
    … …  
    128162Used e.g. in generating normal samples.  
    129163 
    130 Implements {\bf sqmat} \doxyref{}{p.}{classsqmat_b5236c8a050199e1a9d338b0da1a08d2}. 
     164Implements {\bf sqmat} \doxyref{}{p.}{classsqmat_975ddc7e8035d8d4e6cbd52dd99c248c}. 
    131165 
    132166The documentation for this class was generated from the following files:\begin{CompactItemize} 

  • doc/latex/classmpdf.tex

    r19 r32  
    1717\begin{center} 
    1818\leavevmode 
    19 \includegraphics[width=43pt]{classmpdf__coll__graph} 
     19\includegraphics[width=60pt]{classmpdf__coll__graph} 
    2020\end{center} 
    2121\end{figure} 
    … …  
    2525virtual vec {\bf samplecond} (vec \&cond, double lik) 
    2626\begin{CompactList}\small\item\em Returns the required moment of the \doxyref{epdf}{p.}{classepdf}. \item\end{CompactList}\item  
    27 virtual void \textbf{condition} (vec \&cond)\label{classmpdf_cfb3dffef7c03598622e414668bb0588} 
     27virtual void \textbf{condition} (const vec \&cond)\label{classmpdf_0f95a0cc6ab40611f46804682446ed83} 
    2828 
    29 \end{CompactItemize} 
     29\item  
     30virtual double \textbf{evalcond} (const vec \&dt, const vec \&cond)\label{classmpdf_80b738ece5bd4f8c4edaee4b38906f91} 
     31 
     32\item  
     33virtual {\bf $\sim$mpdf} ()\label{classmpdf_6788be9f3a888796499c5293a318fcfb} 
     34 
     35\begin{CompactList}\small\item\em Destructor for future use;. \item\end{CompactList}\item  
     36{\bf mpdf} (const {\bf RV} \&rv0, const {\bf RV} \&rvc0)\label{classmpdf_581ecf362185d37c08bb31cb9d046d6f} 
     37 
     38\begin{CompactList}\small\item\em Default constructor. \item\end{CompactList}\end{CompactItemize} 
     39\subsection*{Protected Attributes} 
     40\begin{CompactItemize} 
     41\item  
     42{\bf RV} {\bf rv}\label{classmpdf_f6687c07ff07d47812dd565368ca59eb} 
     43 
     44\begin{CompactList}\small\item\em modeled random variable \item\end{CompactList}\item  
     45{\bf RV} {\bf rvc}\label{classmpdf_acb7dda792b3cd5576f39fa3129abbab} 
     46 
     47\begin{CompactList}\small\item\em random variable in condition \item\end{CompactList}\item  
     48{\bf epdf} $\ast$ {\bf ep}\label{classmpdf_7aa894208a32f3487827df6d5054424c} 
     49 
     50\begin{CompactList}\small\item\em pointer to internal \doxyref{epdf}{p.}{classepdf} \item\end{CompactList}\end{CompactItemize} 
    3051 
    3152 
    … …  
    4162Returns the required moment of the \doxyref{epdf}{p.}{classepdf}.  
    4263 
    43 Returns a sample from the density conditioned on {\tt cond}, \$x  \doxyref{epdf}{p.}{classepdf}(rv$|$cond)\$  
     64Returns a sample from the density conditioned on {\tt cond}, \$x  \doxyref{epdf}{p.}{classepdf}(rv$|$cond)\$. \begin{Desc} 
     65\item[Parameters:] 
     66\begin{description} 
     67\item[{\em lik}]is a return value of likelihood of the sample. \end{description} 
     68\end{Desc} 
     69 
    4470 
    4571The documentation for this class was generated from the following file:\begin{CompactItemize} 

  • doc/latex/classsqmat.tex

    r22 r32  
    2121 
    2222\begin{CompactList}\small\item\em Conversion to full matrix. \item\end{CompactList}\item  
    23 virtual void {\bf mult\_\-sym} (const mat \&C, bool trans=true)=0 
     23virtual void {\bf mult\_\-sym} (const mat \&C)=0 
    2424\begin{CompactList}\small\item\em Inplace symmetric multiplication by a SQUARE matrix \$C\$, i.e. \$V = C$\ast$V$\ast$C'\$. \item\end{CompactList}\item  
    25 virtual double {\bf logdet} ()=0\label{classsqmat_5c852819589f74cdaefbd648c0ce8547} 
     25virtual void {\bf mult\_\-sym\_\-t} (const mat \&C)=0 
     26\begin{CompactList}\small\item\em Inplace symmetric multiplication by a SQUARE transpose of matrix \$C\$, i.e. \$V = C'$\ast$V$\ast$C\$. \item\end{CompactList}\item  
     27virtual double {\bf logdet} () const =0\label{classsqmat_0a772b396750eeeed85d69fa72478b45} 
    2628 
    2729\begin{CompactList}\small\item\em Logarithm of a determinant. \item\end{CompactList}\item  
    28 virtual vec {\bf sqrt\_\-mult} (vec \&v)=0 
     30virtual vec {\bf sqrt\_\-mult} (const vec \&v)=0 
    2931\begin{CompactList}\small\item\em Multiplies square root of \$V\$ by vector \$x\$. \item\end{CompactList}\item  
    30 virtual double {\bf qform} (vec \&v)=0\label{classsqmat_44e079468bc8bfccf634dc85b32ba6be} 
     32virtual double {\bf qform} (const vec \&v)=0\label{classsqmat_90f97cdf9de08ead4f0648419b3aa4ce} 
    3133 
    3234\begin{CompactList}\small\item\em Evaluates quadratic form \$x= v'$\ast$V$\ast$v\$;. \item\end{CompactList}\item  
    … …  
    3941int {\bf rows} () const \label{classsqmat_071e80ced9cc3b8cbb360fa7462eb646} 
    4042 
    41 \begin{CompactList}\small\item\em Reimplementing common functions of mat: \doxyref{cols()}{p.}{classsqmat_ecc2e2540f95a04f4449842588170f5b}. \item\end{CompactList}\end{CompactItemize} 
     43\begin{CompactList}\small\item\em Reimplementing common functions of mat: \doxyref{cols()}{p.}{classsqmat_ecc2e2540f95a04f4449842588170f5b}. \item\end{CompactList}\item  
     44virtual {\bf $\sim$sqmat} ()\label{classsqmat_0481f2067bb32aaea7e6d4f27e46b656} 
     45 
     46\begin{CompactList}\small\item\em Destructor for future use;. \item\end{CompactList}\end{CompactItemize} 
    4247\subsection*{Protected Attributes} 
    4348\begin{CompactItemize} 
    … …  
    6873Implemented in {\bf fsqmat} \doxyref{}{p.}{classfsqmat_b36530e155667fe9f1bd58394e50c65a}.\index{sqmat@{sqmat}!mult_sym@{mult\_\-sym}} 
    6974\index{mult_sym@{mult\_\-sym}!sqmat@{sqmat}} 
    70 \subsubsection{\setlength{\rightskip}{0pt plus 5cm}virtual void sqmat::mult\_\-sym (const mat \& {\em C}, bool {\em trans} = {\tt true})\hspace{0.3cm}{\tt  [pure virtual]}}\label{classsqmat_faa3bc90be142adde9cf74f573c70157} 
     75\subsubsection{\setlength{\rightskip}{0pt plus 5cm}virtual void sqmat::mult\_\-sym (const mat \& {\em C})\hspace{0.3cm}{\tt  [pure virtual]}}\label{classsqmat_60fbbfa9e483b8187c135f787ee53afa} 
    7176 
    7277 
    … …  
    7681\item[Parameters:] 
    7782\begin{description} 
    78 \item[{\em C}]multiplying matrix, \item[{\em trans}]if true, product \$V = C'$\ast$V$\ast$C\$ will be computed instead; \end{description} 
     83\item[{\em C}]multiplying matrix, \end{description} 
    7984\end{Desc} 
    8085 
    8186 
    82 Implemented in {\bf fsqmat} \doxyref{}{p.}{classfsqmat_acc5d2d0a243f1de6d0106065f01f518}.\index{sqmat@{sqmat}!sqrt_mult@{sqrt\_\-mult}} 
     87Implemented in {\bf fsqmat} \doxyref{}{p.}{classfsqmat_5530d2756b5d991de755e6121c9a452e}.\index{sqmat@{sqmat}!mult_sym_t@{mult\_\-sym\_\-t}} 
     88\index{mult_sym_t@{mult\_\-sym\_\-t}!sqmat@{sqmat}} 
     89\subsubsection{\setlength{\rightskip}{0pt plus 5cm}virtual void sqmat::mult\_\-sym\_\-t (const mat \& {\em C})\hspace{0.3cm}{\tt  [pure virtual]}}\label{classsqmat_6909e906da17725b1b80f3cae7cf3325} 
     90 
     91 
     92Inplace symmetric multiplication by a SQUARE transpose of matrix \$C\$, i.e. \$V = C'$\ast$V$\ast$C\$.  
     93 
     94\begin{Desc} 
     95\item[Parameters:] 
     96\begin{description} 
     97\item[{\em C}]multiplying matrix, \end{description} 
     98\end{Desc} 
     99 
     100 
     101Implemented in {\bf fsqmat} \doxyref{}{p.}{classfsqmat_92052a8adc2054b63e42d1373d145c89}.\index{sqmat@{sqmat}!sqrt_mult@{sqrt\_\-mult}} 
    83102\index{sqrt_mult@{sqrt\_\-mult}!sqmat@{sqmat}} 
    84 \subsubsection{\setlength{\rightskip}{0pt plus 5cm}virtual vec sqmat::sqrt\_\-mult (vec \& {\em v})\hspace{0.3cm}{\tt  [pure virtual]}}\label{classsqmat_b5236c8a050199e1a9d338b0da1a08d2} 
     103\subsubsection{\setlength{\rightskip}{0pt plus 5cm}virtual vec sqmat::sqrt\_\-mult (const vec \& {\em v})\hspace{0.3cm}{\tt  [pure virtual]}}\label{classsqmat_975ddc7e8035d8d4e6cbd52dd99c248c} 
    85104 
    86105 
    … …  
    89108Used e.g. in generating normal samples.  
    90109 
    91 Implemented in {\bf fsqmat} \doxyref{}{p.}{classfsqmat_6648dd4291b809cce14e8497d0433ad3}. 
     110Implemented in {\bf fsqmat} \doxyref{}{p.}{classfsqmat_2288389e2d47bd9df112815ef570c5c9}. 
    92111 
    93112The documentation for this class was generated from the following file:\begin{CompactItemize} 

  • doc/latex/doxygen.sty

    r28 r32  
    1111\rhead[\fancyplain{}{\bfseries\leftmark}] 
    1212        {\fancyplain{}{\bfseries\thepage}} 
    13 \rfoot[\fancyplain{}{\bfseries\scriptsize Generated on Mon Feb 18 21:48:39 2008 for mixpp by Doxygen }]{} 
    14 \lfoot[]{\fancyplain{}{\bfseries\scriptsize Generated on Mon Feb 18 21:48:39 2008 for mixpp by Doxygen }} 
     13\rfoot[\fancyplain{}{\bfseries\scriptsize Generated on Thu Feb 28 16:54:39 2008 for mixpp by Doxygen }]{} 
     14\lfoot[]{\fancyplain{}{\bfseries\scriptsize Generated on Thu Feb 28 16:54:39 2008 for mixpp by Doxygen }} 
    1515\cfoot{} 
    1616\newenvironment{Code} 

  • doc/latex/hierarchy.tex

    r22 r32  
    44\begin{CompactList} 
    55\item \contentsline{section}{Kalman$<$ sq\_\-T $>$}{\pageref{classKalman}}{} 
    6 \item \contentsline{section}{Kalman$<$ fsqmat $>$}{\pageref{classKalman}}{} 
     6\item \contentsline{section}{Kalman$<$ ldmat $>$}{\pageref{classKalman}}{} 
    77\begin{CompactList} 
    88\item \contentsline{section}{EKF$<$ sq\_\-T $>$}{\pageref{classEKF}}{} 
     9\item \contentsline{section}{KFcondQR}{\pageref{classKFcondQR}}{} 
    910\end{CompactList} 
    10 \item \contentsline{section}{KalmanFull}{\pageref{classKalmanFull}}{} 
    1111\item \contentsline{section}{PF}{\pageref{classPF}}{} 
    1212\begin{CompactList} 
    13 \item \contentsline{section}{TrivialPF}{\pageref{classTrivialPF}}{} 
     13\item \contentsline{section}{MPF$<$ BM\_\-T $>$}{\pageref{classMPF}}{} 
    1414\end{CompactList} 
     15\end{CompactList} 
     16\item \contentsline{section}{BMcond}{\pageref{classBMcond}}{} 
     17\begin{CompactList} 
     18\item \contentsline{section}{KFcondQR}{\pageref{classKFcondQR}}{} 
    1519\end{CompactList} 
    1620\item \contentsline{section}{DS}{\pageref{classDS}}{} 
    … …  
    2226\item \contentsline{section}{eEF}{\pageref{classeEF}}{} 
    2327\begin{CompactList} 
     28\item \contentsline{section}{egamma}{\pageref{classegamma}}{} 
    2429\item \contentsline{section}{enorm$<$ sq\_\-T $>$}{\pageref{classenorm}}{} 
     30\item \contentsline{section}{enorm$<$ ldmat $>$}{\pageref{classenorm}}{} 
    2531\end{CompactList} 
     32\item \contentsline{section}{eEmp}{\pageref{classeEmp}}{} 
     33\item \contentsline{section}{emix}{\pageref{classemix}}{} 
     34\item \contentsline{section}{euni}{\pageref{classeuni}}{} 
    2635\end{CompactList} 
    2736\item \contentsline{section}{fnc}{\pageref{classfnc}}{} 
    … …  
    3443\item \contentsline{section}{linfn}{\pageref{classlinfn}}{} 
    3544\end{CompactList} 
     45\item \contentsline{section}{itpp::Gamma\_\-RNG}{\pageref{classitpp_1_1Gamma__RNG}}{} 
     46\item \contentsline{section}{KalmanFull}{\pageref{classKalmanFull}}{} 
     47\item \contentsline{section}{mgamma}{\pageref{classmgamma}}{} 
     48\item \contentsline{section}{mlnorm$<$ sq\_\-T $>$}{\pageref{classmlnorm}}{} 
    3649\item \contentsline{section}{mpdf}{\pageref{classmpdf}}{} 
    3750\item \contentsline{section}{RV}{\pageref{classRV}}{} 

  • doc/latex/libBM_8h.tex

    r22 r32  
    1919\begin{center} 
    2020\leavevmode 
    21 \includegraphics[width=361pt]{libBM_8h__dep__incl} 
     21\includegraphics[width=272pt]{libBM_8h__dep__incl} 
    2222\end{center} 
    2323\end{figure} 
    … …  
    2929class {\bf fnc} 
    3030\begin{CompactList}\small\item\em Class representing function \$f(x)\$ of variable \$x\$ represented by {\tt rv}. \item\end{CompactList}\item  
    31 class {\bf BM} 
    32 \begin{CompactList}\small\item\em Bayesian Model of the world, i.e. all uncertainty is modeled by probabilities. \item\end{CompactList}\item  
    3331class {\bf epdf} 
    3432\begin{CompactList}\small\item\em Probability density function with numerical statistics, e.g. posterior density. \item\end{CompactList}\item  
    … …  
    3634\begin{CompactList}\small\item\em Conditional probability density, e.g. modeling some dependencies. \item\end{CompactList}\item  
    3735class {\bf DS} 
    38 \begin{CompactList}\small\item\em Abstract class for discrete-time sources of data. \item\end{CompactList}\end{CompactItemize} 
     36\begin{CompactList}\small\item\em Abstract class for discrete-time sources of data. \item\end{CompactList}\item  
     37class {\bf BM} 
     38\begin{CompactList}\small\item\em Bayesian Model of the world, i.e. all uncertainty is modeled by probabilities. \item\end{CompactList}\item  
     39class {\bf BMcond} 
     40\begin{CompactList}\small\item\em Conditional Bayesian Filter. \item\end{CompactList}\end{CompactItemize} 
    3941 
    4042 

  • doc/latex/libDC_8h.tex

    r19 r32  
    1919\begin{center} 
    2020\leavevmode 
    21 \includegraphics[width=276pt]{libDC_8h__dep__incl} 
     21\includegraphics[width=191pt]{libDC_8h__dep__incl} 
    2222\end{center} 
    2323\end{figure} 

  • doc/latex/libEF_8h.tex

    r22 r32  
    66{\tt \#include \char`\"{}../math/libDC.h\char`\"{}}\par 
    77{\tt \#include \char`\"{}libBM.h\char`\"{}}\par 
     8{\tt \#include \char`\"{}../itpp\_\-ext.h\char`\"{}}\par 
    89 
    910 
    … …  
    1213\begin{center} 
    1314\leavevmode 
    14 \includegraphics[width=116pt]{libEF_8h__incl} 
     15\includegraphics[width=157pt]{libEF_8h__incl} 
     16\end{center} 
     17\end{figure} 
     18 
     19 
     20This graph shows which files directly or indirectly include this file:\nopagebreak 
     21\begin{figure}[H] 
     22\begin{center} 
     23\leavevmode 
     24\includegraphics[width=191pt]{libEF_8h__dep__incl} 
    1525\end{center} 
    1626\end{figure} 
    … …  
    2434class {\bf enorm$<$ sq\_\-T $>$} 
    2535\begin{CompactList}\small\item\em Gaussian density with positive definite (decomposed) covariance matrix. \item\end{CompactList}\item  
    26 class \textbf{mlnorm$<$ sq\_\-T $>$} 
     36class {\bf egamma} 
     37\begin{CompactList}\small\item\em Gamma posterior density. \item\end{CompactList}\item  
     38class {\bf emix} 
     39\begin{CompactList}\small\item\em Weighted mixture of epdfs with external owned components. \item\end{CompactList}\item  
     40class {\bf euni} 
     41\begin{CompactList}\small\item\em Uniform distributed density on a rectangular support. \item\end{CompactList}\item  
     42class {\bf mlnorm$<$ sq\_\-T $>$} 
     43\begin{CompactList}\small\item\em Normal distributed linear function with linear function of mean value;. \item\end{CompactList}\item  
     44class {\bf mgamma} 
     45\begin{CompactList}\small\item\em Gamma random walk. \item\end{CompactList}\item  
     46class {\bf eEmp} 
     47\begin{CompactList}\small\item\em Weighted empirical density. \item\end{CompactList}\end{CompactItemize} 
     48\subsection*{Enumerations} 
     49\begin{CompactItemize} 
     50\item  
     51enum {\bf RESAMPLING\_\-METHOD} \{ \textbf{MULTINOMIAL} =  0,  
     52\textbf{STRATIFIED} =  1,  
     53\textbf{SYSTEMATIC} =  3 
     54 \} 
     55\begin{CompactList}\small\item\em Switch between various resampling methods. \item\end{CompactList}\end{CompactItemize} 
     56\subsection*{Variables} 
     57\begin{CompactItemize} 
     58\item  
     59Uniform\_\-RNG {\bf UniRNG}\label{libEF_8h_2ae7dcdfebede774dd1b1f16cad10dd9} 
     60 
     61\begin{CompactList}\small\item\em Global Uniform\_\-RNG. \item\end{CompactList}\item  
     62Normal\_\-RNG \textbf{NorRNG}\label{libEF_8h_395c5925c8792aef3be4c360e91526c0} 
     63 
     64\item  
     65{\bf Gamma\_\-RNG} \textbf{GamRNG}\label{libEF_8h_884a8348c92a49725b78e2b6ab0bb802} 
     66 
    2767\end{CompactItemize} 
    2868 

  • doc/latex/libKF_8h.tex

    r22 r32  
    55{\tt \#include $<$itpp/itbase.h$>$}\par 
    66{\tt \#include \char`\"{}../stat/libFN.h\char`\"{}}\par 
    7 {\tt \#include \char`\"{}../math/libDC.h\char`\"{}}\par 
     7{\tt \#include \char`\"{}../stat/libEF.h\char`\"{}}\par 
    88 
    99 
    … …  
    1212\begin{center} 
    1313\leavevmode 
    14 \includegraphics[width=134pt]{libKF_8h__incl} 
     14\includegraphics[width=203pt]{libKF_8h__incl} 
    1515\end{center} 
    1616\end{figure} 
    … …  
    2323\begin{CompactList}\small\item\em \doxyref{Kalman}{p.}{classKalman} filter with covariance matrices in square root form. \item\end{CompactList}\item  
    2424class {\bf EKF$<$ sq\_\-T $>$} 
    25 \begin{CompactList}\small\item\em Extended \doxyref{Kalman}{p.}{classKalman} Filter. \item\end{CompactList}\end{CompactItemize} 
     25\begin{CompactList}\small\item\em Extended \doxyref{Kalman}{p.}{classKalman} Filter. \item\end{CompactList}\item  
     26class {\bf KFcondQR} 
     27\begin{CompactList}\small\item\em \doxyref{Kalman}{p.}{classKalman} Filter with conditional diagonal matrices R and Q. \item\end{CompactList}\end{CompactItemize} 
    2628 
    2729 

  • doc/latex/libPF_8h.tex

    r19 r32  
    44 
    55{\tt \#include $<$itpp/itbase.h$>$}\par 
    6 {\tt \#include \char`\"{}../stat/libBM.h\char`\"{}}\par 
     6{\tt \#include \char`\"{}../stat/libEF.h\char`\"{}}\par 
    77{\tt \#include \char`\"{}../math/libDC.h\char`\"{}}\par 
    88 
    … …  
    1212\begin{center} 
    1313\leavevmode 
    14 \includegraphics[width=135pt]{libPF_8h__incl} 
     14\includegraphics[width=182pt]{libPF_8h__incl} 
    1515\end{center} 
    1616\end{figure} 
    … …  
    1919\item  
    2020class {\bf PF} 
    21 \begin{CompactList}\small\item\em A Particle Filter prototype. \item\end{CompactList}\item  
    22 class {\bf TrivialPF} 
    23 \begin{CompactList}\small\item\em Trivial particle filter with proposal density that is not conditioned on the data. \item\end{CompactList}\item  
    24 class \textbf{MPF} 
    25 \end{CompactItemize} 
    26 \subsection*{Enumerations} 
    27 \begin{CompactItemize} 
    28 \item  
    29 enum \textbf{RESAMPLING\_\-METHOD} \{ \textbf{MULTINOMIAL} =  0,  
    30 \textbf{STRATIFIED} =  1,  
    31 \textbf{SYSTEMATIC} =  3 
    32  \} 
    33 \end{CompactItemize} 
     21\begin{CompactList}\small\item\em Trivial particle filter with proposal density equal to parameter evolution model. \item\end{CompactList}\item  
     22class {\bf MPF$<$ BM\_\-T $>$} 
     23\begin{CompactList}\small\item\em Marginalized Particle filter. \item\end{CompactList}\end{CompactItemize} 
    3424 
    3525 

  • doc/latex/refman.tex

    r28 r32  
    2121{\large Generated by Doxygen 1.5.3}\\ 
    2222\vspace*{0.5cm} 
    23 {\small Mon Feb 18 21:48:39 2008}\\ 
     23{\small Thu Feb 28 16:54:39 2008}\\ 
    2424\end{center} 
    2525\end{titlepage} 
    … …  
    4040\input{classbilinfn} 
    4141\include{classBM} 
     42\include{classBMcond} 
    4243\include{classconstfn} 
    4344\include{classdiffbifn} 
    4445\include{classDS} 
    4546\include{classeEF} 
     47\include{classeEmp} 
     48\include{classegamma} 
    4649\include{classEKF} 
     50\include{classemix} 
    4751\include{classenorm} 
    4852\include{classepdf} 
     53\include{classeuni} 
    4954\include{classfnc} 
    5055\include{classfsqmat} 
     56\include{classitpp_1_1Gamma__RNG} 
    5157\include{classKalman} 
    5258\include{classKalmanFull} 
     59\include{classKFcondQR} 
    5360\include{classlinfn} 
    5461\include{classMemDS} 
     62\include{classmgamma} 
     63\include{classmlnorm} 
    5564\include{classmpdf} 
     65\include{classMPF} 
    5666\include{classPF} 
    5767\include{classRV} 
    5868\include{classsqmat} 
    59 \include{classTrivialPF} 
    6069\chapter{mixpp File Documentation} 
    6170\input{libKF_8h}