[30] | 1 | \section{KFcondQR Class Reference} |
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| 2 | \label{classKFcondQR}\index{KFcondQR@{KFcondQR}} |
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| 3 | \doxyref{Kalman}{p.}{classKalman} Filter with conditional diagonal matrices R and Q. |
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| 4 | |
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| 5 | |
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| 6 | {\tt \#include $<$libKF.h$>$} |
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| 7 | |
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| 8 | Inheritance diagram for KFcondQR:\nopagebreak |
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| 9 | \begin{figure}[H] |
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| 10 | \begin{center} |
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| 11 | \leavevmode |
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[91] | 12 | \includegraphics[width=102pt]{classKFcondQR__inherit__graph} |
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[30] | 13 | \end{center} |
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| 14 | \end{figure} |
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| 15 | Collaboration diagram for KFcondQR:\nopagebreak |
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| 16 | \begin{figure}[H] |
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| 17 | \begin{center} |
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| 18 | \leavevmode |
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[33] | 19 | \includegraphics[width=400pt]{classKFcondQR__coll__graph} |
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[30] | 20 | \end{center} |
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| 21 | \end{figure} |
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| 22 | \subsection*{Public Member Functions} |
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| 23 | \begin{CompactItemize} |
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| 24 | \item |
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[33] | 25 | {\bf KFcondQR} ({\bf RV} rvx, {\bf RV} {\bf rvy}, {\bf RV} {\bf rvu}, {\bf RV} rvRQ)\label{classKFcondQR_3f3968f92c7bbe4b0902d5e14ecc1cb4} |
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[30] | 26 | |
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[33] | 27 | \begin{CompactList}\small\item\em Default constructor. \item\end{CompactList}\item |
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[30] | 28 | void {\bf condition} (const vec \&RQ)\label{classKFcondQR_c9ecf292a85327aa6309c9fd70ceb606} |
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| 29 | |
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| 30 | \begin{CompactList}\small\item\em Substitute {\tt val} for {\tt rvc}. \item\end{CompactList}\item |
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[33] | 31 | void {\bf set\_\-parameters} (const mat \&A0, const mat \&B0, const mat \&C0, const mat \&D0, const {\bf ldmat} \&R0, const {\bf ldmat} \&Q0)\label{classKalman_239b28a0380946f5749b2f8d2807f93a} |
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[30] | 32 | |
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| 33 | \begin{CompactList}\small\item\em Set parameters with check of relevance. \item\end{CompactList}\item |
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[33] | 34 | void {\bf set\_\-est} (const vec \&mu0, const {\bf ldmat} \&P0)\label{classKalman_80bcf29466d9a9dd2b8f74699807d0c0} |
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[30] | 35 | |
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| 36 | \begin{CompactList}\small\item\em Set estimate values, used e.g. in initialization. \item\end{CompactList}\item |
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| 37 | void {\bf bayes} (const vec \&dt)\label{classKalman_7750ffd73f261828a32c18aaeb65c75c} |
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| 38 | |
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| 39 | \begin{CompactList}\small\item\em Here dt = [yt;ut] of appropriate dimensions. \item\end{CompactList}\item |
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| 40 | void {\bf bayes} (mat Dt)\label{classBM_87b07867fd4c133aa89a18543f68d9f9} |
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| 41 | |
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| 42 | \begin{CompactList}\small\item\em Batch Bayes rule (columns of Dt are observations). \item\end{CompactList}\item |
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| 43 | {\bf epdf} \& {\bf \_\-epdf} ()\label{classKalman_a213c57aef55b2645e550bed81cfc0d4} |
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| 44 | |
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[33] | 45 | \begin{CompactList}\small\item\em access function \item\end{CompactList}\item |
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[79] | 46 | mat \& {\bf \_\-\_\-K} ()\label{classKalman_980fcd41c6c548c5da7b8b67c8e6da79} |
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| 47 | |
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| 48 | \begin{CompactList}\small\item\em access function \item\end{CompactList}\item |
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| 49 | vec {\bf \_\-dP} ()\label{classKalman_ac9540f3850b74d89a5fe4db6fc358ce} |
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| 50 | |
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| 51 | \begin{CompactList}\small\item\em access function \item\end{CompactList}\item |
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[33] | 52 | const {\bf RV} \& {\bf \_\-rv} () const \label{classBM_126bd2595c48e311fc2a7ab72876092a} |
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| 53 | |
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| 54 | \begin{CompactList}\small\item\em access function \item\end{CompactList}\item |
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| 55 | double {\bf \_\-ll} () const \label{classBM_87f4a547d2c29180be88175e5eab9c88} |
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| 56 | |
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| 57 | \begin{CompactList}\small\item\em access function \item\end{CompactList}\item |
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| 58 | const {\bf RV} \& {\bf \_\-rvc} () const \label{classBMcond_3fa60348b2da6b4208bb95b8d146900a} |
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| 59 | |
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| 60 | \begin{CompactList}\small\item\em access function \item\end{CompactList}\end{CompactItemize} |
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[30] | 61 | \subsection*{Protected Attributes} |
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| 62 | \begin{CompactItemize} |
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| 63 | \item |
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[33] | 64 | {\bf RV} {\bf rvy}\label{classKalman_7501230c2fafa3655887d2da23b3184c} |
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[30] | 65 | |
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[33] | 66 | \begin{CompactList}\small\item\em Indetifier of output rv. \item\end{CompactList}\item |
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| 67 | {\bf RV} {\bf rvu}\label{classKalman_44a16ffd5ac1e6e39bae34fea9e1e498} |
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[30] | 68 | |
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[33] | 69 | \begin{CompactList}\small\item\em Indetifier of exogeneous rv. \item\end{CompactList}\item |
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| 70 | int {\bf dimx}\label{classKalman_39c8c403b46fa3b8c7da77cb2e3729eb} |
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[30] | 71 | |
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[33] | 72 | \begin{CompactList}\small\item\em cache of rv.count() \item\end{CompactList}\item |
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| 73 | int {\bf dimy}\label{classKalman_ba17b956df1e38b31fbbc299c8213b6a} |
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[30] | 74 | |
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[33] | 75 | \begin{CompactList}\small\item\em cache of rvy.count() \item\end{CompactList}\item |
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| 76 | int {\bf dimu}\label{classKalman_b0153795a1444b6968a86409c778d9ce} |
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[30] | 77 | |
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[33] | 78 | \begin{CompactList}\small\item\em cache of rvu.count() \item\end{CompactList}\item |
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| 79 | mat {\bf A}\label{classKalman_5e02efe86ee91e9c74b93b425fe060b9} |
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[30] | 80 | |
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[33] | 81 | \begin{CompactList}\small\item\em Matrix A. \item\end{CompactList}\item |
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| 82 | mat {\bf B}\label{classKalman_dc87704284a6c0bca13bf51f4345a50a} |
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[30] | 83 | |
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[33] | 84 | \begin{CompactList}\small\item\em Matrix B. \item\end{CompactList}\item |
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| 85 | mat {\bf C}\label{classKalman_86a805cd6515872d1132ad0d6eb5dc13} |
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[30] | 86 | |
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[33] | 87 | \begin{CompactList}\small\item\em Matrix C. \item\end{CompactList}\item |
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| 88 | mat {\bf D}\label{classKalman_d69f774ba3335c970c1c5b1d182f4dd1} |
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[30] | 89 | |
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[33] | 90 | \begin{CompactList}\small\item\em Matrix D. \item\end{CompactList}\item |
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| 91 | {\bf ldmat} {\bf Q}\label{classKalman_9b69015c800eb93f3ee49da23a6f55d9} |
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[30] | 92 | |
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[33] | 93 | \begin{CompactList}\small\item\em Matrix Q in square-root form. \item\end{CompactList}\item |
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| 94 | {\bf ldmat} {\bf R}\label{classKalman_11d171dc0e0ab111c56a70f98b97b3ec} |
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[30] | 95 | |
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[33] | 96 | \begin{CompactList}\small\item\em Matrix R in square-root form. \item\end{CompactList}\item |
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| 97 | {\bf enorm}$<$ {\bf ldmat} $>$ {\bf est}\label{classKalman_5568c74bac67ae6d3b1061dba60c9424} |
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[30] | 98 | |
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| 99 | \begin{CompactList}\small\item\em posterior density on \$x\_\-t\$ \item\end{CompactList}\item |
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[33] | 100 | {\bf enorm}$<$ {\bf ldmat} $>$ {\bf fy}\label{classKalman_e580ab06483952bd03f2e651763e184f} |
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[30] | 101 | |
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| 102 | \begin{CompactList}\small\item\em preditive density on \$y\_\-t\$ \item\end{CompactList}\item |
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[33] | 103 | mat {\bf \_\-K}\label{classKalman_d422f51467c7a06174af2476d2826132} |
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[30] | 104 | |
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[33] | 105 | \begin{CompactList}\small\item\em placeholder for \doxyref{Kalman}{p.}{classKalman} gain \item\end{CompactList}\item |
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[79] | 106 | vec \& {\bf \_\-yp}\label{classKalman_764bbc95238eda11fc81c5ebd0b1dcfd} |
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[30] | 107 | |
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[33] | 108 | \begin{CompactList}\small\item\em cache of fy.mu \item\end{CompactList}\item |
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[79] | 109 | {\bf ldmat} \& {\bf \_\-Ry}\label{classKalman_45c9f928d2d62e0c884900fb3380f904} |
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[30] | 110 | |
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[33] | 111 | \begin{CompactList}\small\item\em cache of fy.R \item\end{CompactList}\item |
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[79] | 112 | vec \& {\bf \_\-mu}\label{classKalman_fe803a81d2d847b0b1db3c6b29c18061} |
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[30] | 113 | |
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[33] | 114 | \begin{CompactList}\small\item\em cache of est.mu \item\end{CompactList}\item |
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[79] | 115 | {\bf ldmat} \& {\bf \_\-P}\label{classKalman_9fb808cc94a4c2652e1fb93be9bb7dcf} |
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[30] | 116 | |
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[33] | 117 | \begin{CompactList}\small\item\em cache of est.R \item\end{CompactList}\item |
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[30] | 118 | {\bf RV} {\bf rv}\label{classBM_af00f0612fabe66241dd507188cdbf88} |
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| 119 | |
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| 120 | \begin{CompactList}\small\item\em Random variable of the posterior. \item\end{CompactList}\item |
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| 121 | double {\bf ll}\label{classBM_5623fef6572a08c2b53b8c87b82dc979} |
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| 122 | |
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| 123 | \begin{CompactList}\small\item\em Logarithm of marginalized data likelihood. \item\end{CompactList}\item |
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| 124 | bool {\bf evalll}\label{classBM_bf6fb59b30141074f8ee1e2f43d03129} |
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| 125 | |
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| 126 | \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}\item |
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[33] | 127 | {\bf RV} {\bf rvc}\label{classBMcond_9ba793c8ec453f04d372d17195ed8dec} |
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[30] | 128 | |
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[33] | 129 | \begin{CompactList}\small\item\em Identificator of the conditioning variable. \item\end{CompactList}\end{CompactItemize} |
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[30] | 130 | |
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| 131 | |
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| 132 | \subsection{Detailed Description} |
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| 133 | \doxyref{Kalman}{p.}{classKalman} Filter with conditional diagonal matrices R and Q. |
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| 134 | |
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| 135 | The documentation for this class was generated from the following files:\begin{CompactItemize} |
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| 136 | \item |
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[145] | 137 | work/git/mixpp/bdm/estim/{\bf libKF.h}\item |
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| 138 | work/git/mixpp/bdm/estim/libKF.cpp\end{CompactItemize} |
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