Class List

Here are the classes, structs, unions and interfaces with brief descriptions:
bdm::ARXLinear Autoregressive model with Gaussian noise
bdm::ArxDSGenerator of ARX data
bdm::bdmrootRoot class of BDM objects
bdm::bilinfnClass representing function $f(x,u) = Ax+Bu$
bdm::BMBayesian Model of a system, i.e. all uncertainty is modeled by probabilities
bdm::BMEFEstimator for Exponential family
chmatSymmetric matrix stored in square root decomposition using upper cholesky
bdm::compositepdfAbstract composition of pdfs, will be used for specific classes this abstract class is common to epdf and mpdf
bdm::constfnClass representing function $f(x) = a$, here rv is empty
bdm::CsvFileDSCSV file data storage The constructor creates Data matrix from the records in a CSV file fname. The orientation can be of two types: 1. BY_COL which is default - the data are stored in columns; one column per time $t$, one row per data item. 2. BY_ROW if the data are stored the classical CSV style. Then each column stores the values for data item, for ex. $[y_{t} y_{t-1} ...]$, one row for each discrete time instant
bdm::datalinkDataLink is a connection between two data vectors Up and Down
bdm::datalink_m2eData link between
bdm::datalink_m2m
bdm::diffbifnClass representing a differentiable function of two variables $f(x,u)$
bdm::dirfilelogLogging into dirfile with buffer in memory
bdm::DSAbstract class for discrete-time sources of data
bdm::eDirichDirichlet posterior density
bdm::eEFGeneral conjugate exponential family posterior density
bdm::eEmpWeighted empirical density
bdm::egammaGamma posterior density
bdm::egiwGauss-inverse-Wishart density stored in LD form
bdm::egiwmixMixture of egiws
bdm::eigammaInverse-Gamma posterior density
bdm::EKF< sq_T >Extended Kalman Filter
EKF_unQExtended Kalman filter with unknown Q
EKF_unQRExtended Kalman filter with unknown Q
bdm::EKFChExtended Kalman Filter in Square root
bdm::EKFCh_chQExtended Kalman filter in Choleski form with unknown Q
bdm::EKFCh_condExtended Kalman filter with unknown parameters in IM
bdm::EKFCh_dQExtended Kalman filter in Choleski form with unknown diagonal Q
bdm::EKFful_unQRExtended Kalman filter with unknown Q and R
bdm::EKFfullExtended Kalman Filter in full matrices
bdm::elognorm
bdm::emixMixture of epdfs
bdm::enorm< sq_T >Gaussian density with positive definite (decomposed) covariance matrix
bdm::epdfProbability density function with numerical statistics, e.g. posterior density
bdm::eprodProduct of independent epdfs. For dependent pdfs, use mprod
bdm::euniUniform distributed density on a rectangular support
bdm::eWishartCh
bdm::FileDS
bdm::fncClass representing function $f(x)$ of variable $x$ represented by rv
fsqmatFake sqmat. This class maps sqmat operations to operations on full matrix
itpp::Gamma_RNGGamma distribution
bdm::ITppFileDSRead Data Matrix from an IT file
bdm::Kalman< sq_T >Kalman filter with covariance matrices in square root form
bdm::KalmanChKalman filter in square root form
bdm::KalmanFullBasic Kalman filter with full matrices (education purpose only)! Will be deleted soon!
bdm::KFcondQRKalman Filter with conditional diagonal matrices R and Q
bdm::KFcondRKalman Filter with conditional diagonal matrices R and Q
ldmatMatrix stored in LD form, (commonly known as UD)
bdm::linfnClass representing function $f(x) = Ax+B$
bdm::loggerClass for storing results (and semi-results) of an experiment
bdm::mEFExponential family model
bdm::MemDSMemory storage of off-line data column-wise
bdm::memlogLogging into matrices in data format in memory
bdm::mepdfUnconditional mpdf, allows using epdf in the role of mpdf
bdm::mergerFunction for general combination of pdfs
bdm::mgammaGamma random walk
bdm::mgamma_fixGamma random walk around a fixed point
bdm::mgnorm< sq_T >Mpdf with general function for mean value
bdm::migammaInverse-Gamma random walk
bdm::migamma_refInverse-Gamma random walk around a fixed point
bdm::MixEFMixture of Exponential Family Densities
bdm::mlnorm< sq_T >Normal distributed linear function with linear function of mean value;
bdm::mlognormLog-Normal random walk
bdm::mlstudent
bdm::mmixMixture of mpdfs with constant weights, all mpdfs are of equal type
bdm::mpdfConditional probability density, e.g. modeling some dependencies
bdm::MPF< BM_T >Marginalized Particle filter
bdm::mprodChain rule decomposition of epdf
bdm::mratioClass 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 $

bdm::multiBMEstimator for Multinomial density
bdm::MultiModel(Switching) Multiple Model The model runs several models in parallel and evaluates thier weights (fittness)
bdm::Particular_UI< T >The main userinfo template class. You should derive this class whenever you need a new userinfo of a class which is compound from smaller elements (all having its own userinfo class prepared)
bdm::PFTrivial particle filter with proposal density equal to parameter evolution model
bdm::RVClass representing variables, most often random variables
sqmatVirtual class for representation of double symmetric matrices in square-root form
bdm::strStructure of RV (used internally), i.e. expanded RVs - TODO tak proc je ve verejnem prostoru jmen? upravit
bdm::UIThis class serves to load and/or save DOMElements into/from files stored on a hard-disk
bdm::UI::UI::SettingsResolver
bdm::UIbuilderBuilds computational object from a UserInfo structure
bdm::UIexternal
bdm::UIinternal
UImexDSCreate memory data source from mxArray

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