1 | \hypertarget{classbdm_1_1BM}{ |
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2 | \section{bdm::BM Class Reference} |
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3 | \label{classbdm_1_1BM}\index{bdm::BM@{bdm::BM}} |
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4 | } |
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5 | {\tt \#include $<$libBM.h$>$} |
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6 | |
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7 | Inheritance diagram for bdm::BM:\nopagebreak |
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8 | \begin{figure}[H] |
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9 | \begin{center} |
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10 | \leavevmode |
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11 | \includegraphics[width=400pt]{classbdm_1_1BM__inherit__graph} |
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12 | \end{center} |
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13 | \end{figure} |
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14 | |
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15 | |
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16 | \subsection{Detailed Description} |
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17 | Bayesian Model of a system, i.e. all uncertainty is modeled by probabilities. |
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18 | |
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19 | \subsection*{Public Member Functions} |
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20 | \begin{Indent}{\bf Constructors}\par |
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21 | \begin{CompactItemize} |
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22 | \item |
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23 | \hypertarget{classbdm_1_1BM_db12aecc3135e7868c664e39e7133756}{ |
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24 | \textbf{BM} ()} |
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25 | \label{classbdm_1_1BM_db12aecc3135e7868c664e39e7133756} |
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26 | |
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27 | \item |
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28 | \hypertarget{classbdm_1_1BM_241b3701190ff1f729fe873a2eef0055}{ |
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29 | \textbf{BM} (const \hyperlink{classbdm_1_1BM}{BM} \&B)} |
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30 | \label{classbdm_1_1BM_241b3701190ff1f729fe873a2eef0055} |
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31 | |
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32 | \item |
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33 | virtual \hyperlink{classbdm_1_1BM}{BM} $\ast$ \hyperlink{classbdm_1_1BM_c0f027ff91d8459937c6f60ff8e553ff}{\_\-copy\_\-} () |
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34 | \end{CompactItemize} |
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35 | \end{Indent} |
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36 | \begin{Indent}{\bf Mathematical operations}\par |
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37 | \begin{CompactItemize} |
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38 | \item |
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39 | virtual void \hyperlink{classbdm_1_1BM_60b1779a577367c369a932cabd3a6188}{bayes} (const vec \&dt)=0 |
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40 | \begin{CompactList}\small\item\em Incremental Bayes rule. \item\end{CompactList}\item |
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41 | \hypertarget{classbdm_1_1BM_1dee3fddaf021e62d925289660a707dc}{ |
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42 | virtual void \hyperlink{classbdm_1_1BM_1dee3fddaf021e62d925289660a707dc}{bayesB} (const mat \&Dt)} |
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43 | \label{classbdm_1_1BM_1dee3fddaf021e62d925289660a707dc} |
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44 | |
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45 | \begin{CompactList}\small\item\em Batch Bayes rule (columns of Dt are observations). \item\end{CompactList}\item |
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46 | virtual double \hyperlink{classbdm_1_1BM_50257e0c1e5b5c73153ea6e716ad8ae0}{logpred} (const vec \&dt) const |
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47 | \item |
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48 | \hypertarget{classbdm_1_1BM_0e8ebe61fb14990abe1254bd3dda5fae}{ |
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49 | vec \hyperlink{classbdm_1_1BM_0e8ebe61fb14990abe1254bd3dda5fae}{logpred\_\-m} (const mat \&dt) const } |
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50 | \label{classbdm_1_1BM_0e8ebe61fb14990abe1254bd3dda5fae} |
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51 | |
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52 | \begin{CompactList}\small\item\em Matrix version of logpred. \item\end{CompactList}\item |
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53 | \hypertarget{classbdm_1_1BM_688d7a2aced1e06aa1c468d73a9e5eba}{ |
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54 | virtual \hyperlink{classbdm_1_1epdf}{epdf} $\ast$ \hyperlink{classbdm_1_1BM_688d7a2aced1e06aa1c468d73a9e5eba}{epredictor} () const } |
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55 | \label{classbdm_1_1BM_688d7a2aced1e06aa1c468d73a9e5eba} |
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56 | |
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57 | \begin{CompactList}\small\item\em Constructs a predictive density $ f(d_{t+1} |d_{t}, \ldots d_{0}) $. \item\end{CompactList}\item |
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58 | \hypertarget{classbdm_1_1BM_598b25e3f3d96a5bc00a5faeb5b3c912}{ |
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59 | virtual \hyperlink{classbdm_1_1mpdf}{mpdf} $\ast$ \hyperlink{classbdm_1_1BM_598b25e3f3d96a5bc00a5faeb5b3c912}{predictor} () const } |
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60 | \label{classbdm_1_1BM_598b25e3f3d96a5bc00a5faeb5b3c912} |
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61 | |
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62 | \begin{CompactList}\small\item\em Constructs a conditional density 1-step ahead predictor. \item\end{CompactList}\end{CompactItemize} |
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63 | \end{Indent} |
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64 | \begin{Indent}{\bf Access to attributes}\par |
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65 | \begin{CompactItemize} |
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66 | \item |
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67 | \hypertarget{classbdm_1_1BM_ff2d8755ba0b3def927d31305c03b09c}{ |
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68 | const \hyperlink{classbdm_1_1RV}{RV} \& \textbf{\_\-drv} () const } |
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69 | \label{classbdm_1_1BM_ff2d8755ba0b3def927d31305c03b09c} |
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70 | |
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71 | \item |
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72 | \hypertarget{classbdm_1_1BM_f135ae6dce7e9f30c9f88229c7930b96}{ |
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73 | void \textbf{set\_\-drv} (const \hyperlink{classbdm_1_1RV}{RV} \&rv)} |
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74 | \label{classbdm_1_1BM_f135ae6dce7e9f30c9f88229c7930b96} |
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75 | |
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76 | \item |
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77 | \hypertarget{classbdm_1_1BM_5be65d37dedfe33a3671e7065f523a70}{ |
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78 | double \textbf{\_\-ll} () const } |
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79 | \label{classbdm_1_1BM_5be65d37dedfe33a3671e7065f523a70} |
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80 | |
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81 | \item |
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82 | \hypertarget{classbdm_1_1BM_236b3abbcc93594fc97cd86d82c1a83f}{ |
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83 | void \textbf{set\_\-evalll} (bool evl0)} |
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84 | \label{classbdm_1_1BM_236b3abbcc93594fc97cd86d82c1a83f} |
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85 | |
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86 | \item |
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87 | \hypertarget{classbdm_1_1BM_963258c4c2dd05be001003b19aceefef}{ |
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88 | virtual const \hyperlink{classbdm_1_1epdf}{epdf} \& \textbf{\_\-epdf} () const =0} |
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89 | \label{classbdm_1_1BM_963258c4c2dd05be001003b19aceefef} |
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90 | |
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91 | \item |
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92 | \hypertarget{classbdm_1_1BM_4ed0f8b880e606316ae800f3a011c3a6}{ |
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93 | virtual const \hyperlink{classbdm_1_1epdf}{epdf} $\ast$ \textbf{\_\-e} () const =0} |
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94 | \label{classbdm_1_1BM_4ed0f8b880e606316ae800f3a011c3a6} |
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95 | |
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96 | \end{CompactItemize} |
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97 | \end{Indent} |
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98 | \subsection*{Protected Attributes} |
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99 | \begin{CompactItemize} |
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100 | \item |
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101 | \hypertarget{classbdm_1_1BM_c400357e37d27a4834b2b1d9211009ed}{ |
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102 | \hyperlink{classbdm_1_1RV}{RV} \hyperlink{classbdm_1_1BM_c400357e37d27a4834b2b1d9211009ed}{drv}} |
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103 | \label{classbdm_1_1BM_c400357e37d27a4834b2b1d9211009ed} |
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104 | |
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105 | \begin{CompactList}\small\item\em Random variable of the data (optional). \item\end{CompactList}\item |
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106 | \hypertarget{classbdm_1_1BM_4064b6559d962633e4372b12f4cd204a}{ |
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107 | double \hyperlink{classbdm_1_1BM_4064b6559d962633e4372b12f4cd204a}{ll}} |
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108 | \label{classbdm_1_1BM_4064b6559d962633e4372b12f4cd204a} |
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109 | |
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110 | \begin{CompactList}\small\item\em Logarithm of marginalized data likelihood. \item\end{CompactList}\item |
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111 | \hypertarget{classbdm_1_1BM_faff0ad12556fe7dc0e2807d4fd938ee}{ |
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112 | bool \hyperlink{classbdm_1_1BM_faff0ad12556fe7dc0e2807d4fd938ee}{evalll}} |
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113 | \label{classbdm_1_1BM_faff0ad12556fe7dc0e2807d4fd938ee} |
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114 | |
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115 | \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 computational time. \item\end{CompactList}\end{CompactItemize} |
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116 | |
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117 | |
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118 | \subsection{Member Function Documentation} |
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119 | \hypertarget{classbdm_1_1BM_c0f027ff91d8459937c6f60ff8e553ff}{ |
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120 | \index{bdm::BM@{bdm::BM}!\_\-copy\_\-@{\_\-copy\_\-}} |
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121 | \index{\_\-copy\_\-@{\_\-copy\_\-}!bdm::BM@{bdm::BM}} |
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122 | \subsubsection[\_\-copy\_\-]{\setlength{\rightskip}{0pt plus 5cm}virtual {\bf BM}$\ast$ bdm::BM::\_\-copy\_\- ()\hspace{0.3cm}{\tt \mbox{[}inline, virtual\mbox{]}}}} |
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123 | \label{classbdm_1_1BM_c0f027ff91d8459937c6f60ff8e553ff} |
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124 | |
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125 | |
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126 | Copy function required in vectors, Arrays of \hyperlink{classbdm_1_1BM}{BM} etc. Have to be DELETED manually! Prototype: |
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127 | |
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128 | \begin{Code}\begin{verbatim} BM* _copy_(){return new BM(*this);} |
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129 | \end{verbatim} |
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130 | \end{Code} |
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131 | |
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132 | |
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133 | |
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134 | Reimplemented in \hyperlink{classbdm_1_1ARX_60c40b5c6abc4c7e464b4ccae64a5a61}{bdm::ARX}.\hypertarget{classbdm_1_1BM_60b1779a577367c369a932cabd3a6188}{ |
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135 | \index{bdm::BM@{bdm::BM}!bayes@{bayes}} |
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136 | \index{bayes@{bayes}!bdm::BM@{bdm::BM}} |
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137 | \subsubsection[bayes]{\setlength{\rightskip}{0pt plus 5cm}virtual void bdm::BM::bayes (const vec \& {\em dt})\hspace{0.3cm}{\tt \mbox{[}pure virtual\mbox{]}}}} |
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138 | \label{classbdm_1_1BM_60b1779a577367c369a932cabd3a6188} |
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139 | |
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140 | |
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141 | Incremental Bayes rule. |
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142 | |
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143 | \begin{Desc} |
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144 | \item[Parameters:] |
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145 | \begin{description} |
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146 | \item[{\em dt}]vector of input data \end{description} |
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147 | \end{Desc} |
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148 | |
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149 | |
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150 | Implemented in \hyperlink{classbdm_1_1ARX_8bdf2974052e8ce74eb0d4f3791c58a3}{bdm::ARX}, \hyperlink{classbdm_1_1Kalman_4a39330c14eff8d13179e868a1d1aa8c}{bdm::Kalman$<$ sq\_\-T $>$}, \hyperlink{classbdm_1_1KalmanCh_b41fe5540548100b08e1684c3be767b6}{bdm::KalmanCh}, \hyperlink{classbdm_1_1EKFfull_f149ae8e9ce14d9931a7bb2850736699}{bdm::EKFfull}, \hyperlink{classbdm_1_1EKF_3fb182ecc29b10ca1163cecbf3bcccfa}{bdm::EKF$<$ sq\_\-T $>$}, \hyperlink{classbdm_1_1EKFCh_4c8609c37290b158f88a31dae4047225}{bdm::EKFCh}, \hyperlink{classbdm_1_1PF_638946eea22d4964bf9350286bb4efd8}{bdm::PF}, \hyperlink{classbdm_1_1MPF_286d040770d08bd7ff416cea617b1b14}{bdm::MPF$<$ BM\_\-T $>$}, \hyperlink{classbdm_1_1MixEF_5bd7da667da183eed1577f11dff0c1f1}{bdm::MixEF}, \hyperlink{classbdm_1_1BMEF_c287f4c0c1ea31b91572ec45351838f1}{bdm::BMEF}, \hyperlink{classbdm_1_1multiBM_1e4bf41b61937fd80f34049742e23f95}{bdm::multiBM}, \hyperlink{classbdm_1_1Kalman_4a39330c14eff8d13179e868a1d1aa8c}{bdm::Kalman$<$ ldmat $>$}, \hyperlink{classbdm_1_1Kalman_4a39330c14eff8d13179e868a1d1aa8c}{bdm::Kalman$<$ chmat $>$}, and \hyperlink{classbdm_1_1Kalman_4a39330c14eff8d13179e868a1d1aa8c}{bdm::Kalman$<$ fsqmat $>$}. |
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151 | |
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152 | Referenced by bayesB().\hypertarget{classbdm_1_1BM_50257e0c1e5b5c73153ea6e716ad8ae0}{ |
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153 | \index{bdm::BM@{bdm::BM}!logpred@{logpred}} |
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154 | \index{logpred@{logpred}!bdm::BM@{bdm::BM}} |
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155 | \subsubsection[logpred]{\setlength{\rightskip}{0pt plus 5cm}virtual double bdm::BM::logpred (const vec \& {\em dt}) const\hspace{0.3cm}{\tt \mbox{[}inline, virtual\mbox{]}}}} |
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156 | \label{classbdm_1_1BM_50257e0c1e5b5c73153ea6e716ad8ae0} |
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157 | |
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158 | |
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159 | Evaluates predictive log-likelihood of the given data record I.e. marginal likelihood of the data with the posterior integrated out. |
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160 | |
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161 | Reimplemented in \hyperlink{classbdm_1_1ARX_080a7e531e3aa06694112863b15bc6a4}{bdm::ARX}, \hyperlink{classbdm_1_1MixEF_da724da464a75e07521941e430929efa}{bdm::MixEF}, and \hyperlink{classbdm_1_1multiBM_e157b607c1e3fa91d42aeea44458e2bf}{bdm::multiBM}. |
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162 | |
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163 | Referenced by logpred\_\-m(). |
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164 | |
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165 | The documentation for this class was generated from the following files:\begin{CompactItemize} |
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166 | \item |
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167 | \hyperlink{libBM_8h}{libBM.h}\item |
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168 | libBM.cpp\end{CompactItemize} |
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