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::eigammaInverse-Gamma posterior density
bdm::EKF< sq_T >Extended Kalman Filter
EKF_unQExtended Kalman filter with unknown Q
bdm::EKFChExtended Kalman Filter in Square root
bdm::EKFCh_chQExtended Kalman filter in Choleski form with unknown Q
EKFCh_condExtended Kalman filter 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
EKFCh_du_kQExtended Kalman filter with unknown Q and delta u
EKFfixedExtended Kalman Filter with full matrices in fixed point arithmetic
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
IMk1Model stredni hodnoty vyvoje stavu pro k1
IMpmsmState evolution model for a PMSM drive and its derivative with respect to $x$
IMpmsm2oState evolution model for a PMSM drive and its derivative with respect to $x$
IMpmsmStatState evolution model for a PMSM drive and its derivative with respect to $x$, equation for $\omega$ is omitted.$
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
OMk1Model stredni hodnoty pozorovani pro k1
OMpmsmObservation model for PMSM drive and its derivative with respect to $x$
bdm::PFTrivial particle filter with proposal density equal to parameter evolution model
pmsmCRBThis class behaves like BM but it is evaluating EKF
pmsmDSSimulator of PMSM machine with predefined profile on omega
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
UIARX
UIArxDS
bdm::UIbuilderBuilds computational object from a UserInfo structure
UIdirfilelogUI for dirfilelog (Kst file format)
bdm::UIexternal
bdm::UIinternal
UImexDSCreate memory data source from mxArray
UImgnorm
UImigamma_ref
UImlognorm
UIMPF
UIpmsmDSUI for pmsmDS,
UIpmsmOMUI for pmsm observation model
UIrvUI for class RV (description of data vectors)
UIstateDS

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