[91] | 1 | \section{Class List} |
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[3] | 2 | Here are the classes, structs, unions and interfaces with brief descriptions:\begin{CompactList} |
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[255] | 3 | \item\contentsline{section}{\hyperlink{classbdm_1_1ARX}{bdm::ARX} (Linear Autoregressive model with Gaussian noise )}{\pageref{classbdm_1_1ARX}}{} |
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[261] | 4 | \item\contentsline{section}{\hyperlink{classbdm_1_1ArxDS}{bdm::ArxDS} (Generator of \hyperlink{classbdm_1_1ARX}{ARX} data )}{\pageref{classbdm_1_1ArxDS}}{} |
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| 5 | \item\contentsline{section}{\hyperlink{classbdm_1_1bdmroot}{bdm::bdmroot} (Root class of BDM objects )}{\pageref{classbdm_1_1bdmroot}}{} |
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[255] | 6 | \item\contentsline{section}{\hyperlink{classbdm_1_1bilinfn}{bdm::bilinfn} (Class representing function $f(x,u) = Ax+Bu$ )}{\pageref{classbdm_1_1bilinfn}}{} |
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[269] | 7 | \item\contentsline{section}{\hyperlink{classbdm_1_1BM}{bdm::BM} (Bayesian Model of a system, i.e. all uncertainty is modeled by probabilities )}{\pageref{classbdm_1_1BM}}{} |
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[255] | 8 | \item\contentsline{section}{\hyperlink{classbdm_1_1BMcond}{bdm::BMcond} (Conditional Bayesian Filter )}{\pageref{classbdm_1_1BMcond}}{} |
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| 9 | \item\contentsline{section}{\hyperlink{classbdm_1_1BMEF}{bdm::BMEF} (Estimator for Exponential family )}{\pageref{classbdm_1_1BMEF}}{} |
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[172] | 10 | \item\contentsline{section}{\hyperlink{classchmat}{chmat} (Symmetric matrix stored in square root decomposition using upper cholesky )}{\pageref{classchmat}}{} |
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[261] | 11 | \item\contentsline{section}{\hyperlink{classbdm_1_1compositepdf}{bdm::compositepdf} (Abstract composition of pdfs, will be used for specific classes this abstract class is common to \hyperlink{classbdm_1_1epdf}{epdf} and \hyperlink{classbdm_1_1mpdf}{mpdf} )}{\pageref{classbdm_1_1compositepdf}}{} |
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[255] | 12 | \item\contentsline{section}{\hyperlink{classbdm_1_1constfn}{bdm::constfn} (Class representing function $f(x) = a$, here {\tt rv} is empty )}{\pageref{classbdm_1_1constfn}}{} |
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[270] | 13 | \item\contentsline{section}{\hyperlink{classbdm_1_1datalink}{bdm::datalink} (DataLink is a connection between two data vectors Up and Down )}{\pageref{classbdm_1_1datalink}}{} |
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[255] | 14 | \item\contentsline{section}{\hyperlink{classbdm_1_1datalink__m2e}{bdm::datalink\_\-m2e} (Data link between )}{\pageref{classbdm_1_1datalink__m2e}}{} |
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| 15 | \item\contentsline{section}{\hyperlink{classbdm_1_1datalink__m2m}{bdm::datalink\_\-m2m} }{\pageref{classbdm_1_1datalink__m2m}}{} |
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| 16 | \item\contentsline{section}{\hyperlink{classbdm_1_1diffbifn}{bdm::diffbifn} (Class representing a differentiable function of two variables $f(x,u)$ )}{\pageref{classbdm_1_1diffbifn}}{} |
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| 17 | \item\contentsline{section}{\hyperlink{classbdm_1_1dirfilelog}{bdm::dirfilelog} (Logging into dirfile with buffer in memory )}{\pageref{classbdm_1_1dirfilelog}}{} |
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| 18 | \item\contentsline{section}{\hyperlink{classbdm_1_1DS}{bdm::DS} (Abstract class for discrete-time sources of data )}{\pageref{classbdm_1_1DS}}{} |
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| 19 | \item\contentsline{section}{\hyperlink{classbdm_1_1eDirich}{bdm::eDirich} (Dirichlet posterior density )}{\pageref{classbdm_1_1eDirich}}{} |
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| 20 | \item\contentsline{section}{\hyperlink{classbdm_1_1eEF}{bdm::eEF} (General conjugate exponential family posterior density )}{\pageref{classbdm_1_1eEF}}{} |
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| 21 | \item\contentsline{section}{\hyperlink{classbdm_1_1eEmp}{bdm::eEmp} (Weighted empirical density )}{\pageref{classbdm_1_1eEmp}}{} |
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| 22 | \item\contentsline{section}{\hyperlink{classbdm_1_1egamma}{bdm::egamma} (Gamma posterior density )}{\pageref{classbdm_1_1egamma}}{} |
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| 23 | \item\contentsline{section}{\hyperlink{classbdm_1_1egiw}{bdm::egiw} (Gauss-inverse-Wishart density stored in LD form )}{\pageref{classbdm_1_1egiw}}{} |
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| 24 | \item\contentsline{section}{\hyperlink{classbdm_1_1eigamma}{bdm::eigamma} (Inverse-Gamma posterior density )}{\pageref{classbdm_1_1eigamma}}{} |
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| 25 | \item\contentsline{section}{\hyperlink{classbdm_1_1EKF}{bdm::EKF$<$ sq\_\-T $>$} (Extended \hyperlink{classbdm_1_1Kalman}{Kalman} Filter )}{\pageref{classbdm_1_1EKF}}{} |
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| 26 | \item\contentsline{section}{\hyperlink{classbdm_1_1EKFCh}{bdm::EKFCh} (Extended \hyperlink{classbdm_1_1Kalman}{Kalman} Filter in Square root )}{\pageref{classbdm_1_1EKFCh}}{} |
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| 27 | \item\contentsline{section}{\hyperlink{classbdm_1_1EKFCh__cond}{bdm::EKFCh\_\-cond} (Extended \hyperlink{classbdm_1_1Kalman}{Kalman} filter with unknown parameters in {\tt IM} )}{\pageref{classbdm_1_1EKFCh__cond}}{} |
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| 28 | \item\contentsline{section}{\hyperlink{classbdm_1_1EKFCh__unQ}{bdm::EKFCh\_\-unQ} (Extended \hyperlink{classbdm_1_1Kalman}{Kalman} filter in Choleski form with unknown {\tt Q} )}{\pageref{classbdm_1_1EKFCh__unQ}}{} |
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| 29 | \item\contentsline{section}{\hyperlink{classbdm_1_1EKFful__unQR}{bdm::EKFful\_\-unQR} (Extended \hyperlink{classbdm_1_1Kalman}{Kalman} filter with unknown {\tt Q} and {\tt R} )}{\pageref{classbdm_1_1EKFful__unQR}}{} |
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| 30 | \item\contentsline{section}{\hyperlink{classbdm_1_1EKFfull}{bdm::EKFfull} (Extended \hyperlink{classbdm_1_1Kalman}{Kalman} Filter in full matrices )}{\pageref{classbdm_1_1EKFfull}}{} |
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| 31 | \item\contentsline{section}{\hyperlink{classbdm_1_1emix}{bdm::emix} (Mixture of epdfs )}{\pageref{classbdm_1_1emix}}{} |
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| 32 | \item\contentsline{section}{\hyperlink{classbdm_1_1enorm}{bdm::enorm$<$ sq\_\-T $>$} (Gaussian density with positive definite (decomposed) covariance matrix )}{\pageref{classbdm_1_1enorm}}{} |
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| 33 | \item\contentsline{section}{\hyperlink{classbdm_1_1epdf}{bdm::epdf} (Probability density function with numerical statistics, e.g. posterior density )}{\pageref{classbdm_1_1epdf}}{} |
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| 34 | \item\contentsline{section}{\hyperlink{classbdm_1_1eprod}{bdm::eprod} (Product of independent epdfs. For dependent pdfs, use \hyperlink{classbdm_1_1mprod}{mprod} )}{\pageref{classbdm_1_1eprod}}{} |
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| 35 | \item\contentsline{section}{\hyperlink{classbdm_1_1euni}{bdm::euni} (Uniform distributed density on a rectangular support )}{\pageref{classbdm_1_1euni}}{} |
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| 36 | \item\contentsline{section}{\hyperlink{classbdm_1_1fnc}{bdm::fnc} (Class representing function $f(x)$ of variable $x$ represented by {\tt rv} )}{\pageref{classbdm_1_1fnc}}{} |
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[172] | 37 | \item\contentsline{section}{\hyperlink{classfsqmat}{fsqmat} (Fake \hyperlink{classsqmat}{sqmat}. This class maps \hyperlink{classsqmat}{sqmat} operations to operations on full matrix )}{\pageref{classfsqmat}}{} |
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[255] | 38 | \item\contentsline{section}{\hyperlink{classbdm_1_1Kalman}{bdm::Kalman$<$ sq\_\-T $>$} (\hyperlink{classbdm_1_1Kalman}{Kalman} filter with covariance matrices in square root form )}{\pageref{classbdm_1_1Kalman}}{} |
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| 39 | \item\contentsline{section}{\hyperlink{classbdm_1_1KalmanCh}{bdm::KalmanCh} (\hyperlink{classbdm_1_1Kalman}{Kalman} filter in square root form )}{\pageref{classbdm_1_1KalmanCh}}{} |
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| 40 | \item\contentsline{section}{\hyperlink{classbdm_1_1KalmanFull}{bdm::KalmanFull} (Basic \hyperlink{classbdm_1_1Kalman}{Kalman} filter with full matrices (education purpose only)! Will be deleted soon! )}{\pageref{classbdm_1_1KalmanFull}}{} |
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| 41 | \item\contentsline{section}{\hyperlink{classbdm_1_1KFcondQR}{bdm::KFcondQR} (\hyperlink{classbdm_1_1Kalman}{Kalman} Filter with conditional diagonal matrices R and Q )}{\pageref{classbdm_1_1KFcondQR}}{} |
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| 42 | \item\contentsline{section}{\hyperlink{classbdm_1_1KFcondR}{bdm::KFcondR} (\hyperlink{classbdm_1_1Kalman}{Kalman} Filter with conditional diagonal matrices R and Q )}{\pageref{classbdm_1_1KFcondR}}{} |
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[181] | 43 | \item\contentsline{section}{\hyperlink{classldmat}{ldmat} (Matrix stored in LD form, (commonly known as UD) )}{\pageref{classldmat}}{} |
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[255] | 44 | \item\contentsline{section}{\hyperlink{classbdm_1_1linfn}{bdm::linfn} (Class representing function $f(x) = Ax+B$ )}{\pageref{classbdm_1_1linfn}}{} |
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[269] | 45 | \item\contentsline{section}{\hyperlink{classbdm_1_1logger}{bdm::logger} (Class for storing results (and semi-results) of an experiment )}{\pageref{classbdm_1_1logger}}{} |
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[255] | 46 | \item\contentsline{section}{\hyperlink{classbdm_1_1mEF}{bdm::mEF} (Exponential family model )}{\pageref{classbdm_1_1mEF}}{} |
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[261] | 47 | \item\contentsline{section}{\hyperlink{classbdm_1_1MemDS}{bdm::MemDS} (Memory storage of off-line data column-wise )}{\pageref{classbdm_1_1MemDS}}{} |
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[255] | 48 | \item\contentsline{section}{\hyperlink{classbdm_1_1memlog}{bdm::memlog} (Logging into matrices in data format in memory )}{\pageref{classbdm_1_1memlog}}{} |
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| 49 | \item\contentsline{section}{\hyperlink{classbdm_1_1mepdf}{bdm::mepdf} (Unconditional \hyperlink{classbdm_1_1mpdf}{mpdf}, allows using \hyperlink{classbdm_1_1epdf}{epdf} in the role of \hyperlink{classbdm_1_1mpdf}{mpdf} )}{\pageref{classbdm_1_1mepdf}}{} |
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| 50 | \item\contentsline{section}{\hyperlink{classbdm_1_1merger}{bdm::merger} (Function for general combination of pdfs )}{\pageref{classbdm_1_1merger}}{} |
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| 51 | \item\contentsline{section}{\hyperlink{classbdm_1_1mgamma}{bdm::mgamma} (Gamma random walk )}{\pageref{classbdm_1_1mgamma}}{} |
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| 52 | \item\contentsline{section}{\hyperlink{classbdm_1_1mgamma__fix}{bdm::mgamma\_\-fix} (Gamma random walk around a fixed point )}{\pageref{classbdm_1_1mgamma__fix}}{} |
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| 53 | \item\contentsline{section}{\hyperlink{classbdm_1_1migamma}{bdm::migamma} (Inverse-Gamma random walk )}{\pageref{classbdm_1_1migamma}}{} |
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| 54 | \item\contentsline{section}{\hyperlink{classbdm_1_1migamma__fix}{bdm::migamma\_\-fix} (Inverse-Gamma random walk around a fixed point )}{\pageref{classbdm_1_1migamma__fix}}{} |
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| 55 | \item\contentsline{section}{\hyperlink{classbdm_1_1MixEF}{bdm::MixEF} (Mixture of Exponential Family Densities )}{\pageref{classbdm_1_1MixEF}}{} |
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| 56 | \item\contentsline{section}{\hyperlink{classbdm_1_1mlnorm}{bdm::mlnorm$<$ sq\_\-T $>$} (Normal distributed linear function with linear function of mean value; )}{\pageref{classbdm_1_1mlnorm}}{} |
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| 57 | \item\contentsline{section}{\hyperlink{classbdm_1_1mlstudent}{bdm::mlstudent} }{\pageref{classbdm_1_1mlstudent}}{} |
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| 58 | \item\contentsline{section}{\hyperlink{classbdm_1_1mmix}{bdm::mmix} (Mixture of mpdfs with constant weights, all mpdfs are of equal type )}{\pageref{classbdm_1_1mmix}}{} |
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| 59 | \item\contentsline{section}{\hyperlink{classbdm_1_1mpdf}{bdm::mpdf} (Conditional probability density, e.g. modeling some dependencies )}{\pageref{classbdm_1_1mpdf}}{} |
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| 60 | \item\contentsline{section}{\hyperlink{classbdm_1_1MPF}{bdm::MPF$<$ BM\_\-T $>$} (Marginalized Particle filter )}{\pageref{classbdm_1_1MPF}}{} |
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| 61 | \item\contentsline{section}{\hyperlink{classbdm_1_1mprod}{bdm::mprod} (Chain rule decomposition of \hyperlink{classbdm_1_1epdf}{epdf} )}{\pageref{classbdm_1_1mprod}}{} |
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| 62 | \item\contentsline{section}{\hyperlink{classbdm_1_1mratio}{bdm::mratio} (Class representing ratio of two densities which arise e.g. by applying the Bayes rule. It represents density in the form: \[ f(rv|rvc) = \frac{f(rv,rvc)}{f(rvc)} \] where $ f(rvc) = \int f(rv,rvc) d\ rv $ )}{\pageref{classbdm_1_1mratio}}{} |
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| 63 | \item\contentsline{section}{\hyperlink{classbdm_1_1multiBM}{bdm::multiBM} (Estimator for Multinomial density )}{\pageref{classbdm_1_1multiBM}}{} |
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| 64 | \item\contentsline{section}{\hyperlink{classbdm_1_1PF}{bdm::PF} (Trivial particle filter with proposal density equal to parameter evolution model )}{\pageref{classbdm_1_1PF}}{} |
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| 65 | \item\contentsline{section}{\hyperlink{classbdm_1_1RV}{bdm::RV} (Class representing variables, most often random variables )}{\pageref{classbdm_1_1RV}}{} |
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[172] | 66 | \item\contentsline{section}{\hyperlink{classsqmat}{sqmat} (Virtual class for representation of double symmetric matrices in square-root form )}{\pageref{classsqmat}}{} |
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[255] | 67 | \item\contentsline{section}{\hyperlink{classbdm_1_1str}{bdm::str} (Structure of \hyperlink{classbdm_1_1RV}{RV} (used internally), i.e. expanded RVs )}{\pageref{classbdm_1_1str}}{} |
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[269] | 68 | \item\contentsline{section}{\hyperlink{classUIARX}{UIARX} }{\pageref{classUIARX}}{} |
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[264] | 69 | \item\contentsline{section}{\hyperlink{classUIArxDS}{UIArxDS} }{\pageref{classUIArxDS}}{} |
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| 70 | \item\contentsline{section}{\hyperlink{classbdm_1_1UIbuilder}{bdm::UIbuilder} (Builds computational object from a UserInfo structure )}{\pageref{classbdm_1_1UIbuilder}}{} |
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[3] | 71 | \end{CompactList} |
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