bdm::ARX | Linear Autoregressive model with Gaussian noise |
bdm::ArxDS | Generator of ARX data |
bdm::bdmroot | Root class of BDM objects |
bdm::bilinfn | Class representing function |
bdm::BM | Bayesian Model of a system, i.e. all uncertainty is modeled by probabilities |
bdm::BMEF | Estimator for Exponential family |
chmat | Symmetric matrix stored in square root decomposition using upper cholesky |
bdm::compositepdf | Abstract composition of pdfs, will be used for specific classes this abstract class is common to epdf and mpdf |
bdm::constfn | Class representing function , here rv is empty |
bdm::CsvFileDS | CSV 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 , 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. , one row for each discrete time instant |
bdm::datalink | DataLink is a connection between two data vectors Up and Down |
bdm::datalink_m2e | Data link between |
bdm::datalink_m2m | |
bdm::diffbifn | Class representing a differentiable function of two variables |
bdm::dirfilelog | Logging into dirfile with buffer in memory |
bdm::DS | Abstract class for discrete-time sources of data |
bdm::eDirich | Dirichlet posterior density |
bdm::eEF | General conjugate exponential family posterior density |
bdm::eEmp | Weighted empirical density |
bdm::egamma | Gamma posterior density |
bdm::egiw | Gauss-inverse-Wishart density stored in LD form |
bdm::eigamma | Inverse-Gamma posterior density |
bdm::EKF< sq_T > | Extended Kalman Filter |
EKF_unQ | Extended Kalman filter with unknown Q |
bdm::EKFCh | Extended Kalman Filter in Square root |
bdm::EKFCh_chQ | Extended Kalman filter in Choleski form with unknown Q |
EKFCh_cond | Extended Kalman filter with unknown Q |
bdm::EKFCh_cond | Extended Kalman filter with unknown parameters in IM |
bdm::EKFCh_dQ | Extended Kalman filter in Choleski form with unknown diagonal Q |
EKFCh_du_kQ | Extended Kalman filter with unknown Q and delta u |
EKFfixed | Extended Kalman Filter with full matrices in fixed point arithmetic |
bdm::EKFful_unQR | Extended Kalman filter with unknown Q and R |
bdm::EKFfull | Extended Kalman Filter in full matrices |
bdm::elognorm | |
bdm::emix | Mixture of epdfs |
bdm::enorm< sq_T > | Gaussian density with positive definite (decomposed) covariance matrix |
bdm::epdf | Probability density function with numerical statistics, e.g. posterior density |
bdm::eprod | Product of independent epdfs. For dependent pdfs, use mprod |
bdm::euni | Uniform distributed density on a rectangular support |
bdm::eWishartCh | |
bdm::FileDS | |
bdm::fnc | Class representing function of variable represented by rv |
fsqmat | Fake sqmat. This class maps sqmat operations to operations on full matrix |
itpp::Gamma_RNG | Gamma distribution |
IMk1 | Model stredni hodnoty vyvoje stavu pro k1 |
IMpmsm | State evolution model for a PMSM drive and its derivative with respect to |
IMpmsm2o | State evolution model for a PMSM drive and its derivative with respect to |
IMpmsmStat | State evolution model for a PMSM drive and its derivative with respect to , equation for is omitted.$ |
bdm::ItppFileDS | Read Data Matrix from an IT file |
bdm::Kalman< sq_T > | Kalman filter with covariance matrices in square root form |
bdm::KalmanCh | Kalman filter in square root form |
bdm::KalmanFull | Basic Kalman filter with full matrices (education purpose only)! Will be deleted soon! |
bdm::KFcondQR | Kalman Filter with conditional diagonal matrices R and Q |
bdm::KFcondR | Kalman Filter with conditional diagonal matrices R and Q |
ldmat | Matrix stored in LD form, (commonly known as UD) |
bdm::linfn | Class representing function |
bdm::logger | Class for storing results (and semi-results) of an experiment |
bdm::mEF | Exponential family model |
bdm::MemDS | Memory storage of off-line data column-wise |
bdm::memlog | Logging into matrices in data format in memory |
bdm::mepdf | Unconditional mpdf, allows using epdf in the role of mpdf |
bdm::merger | Function for general combination of pdfs |
bdm::mgamma | Gamma random walk |
bdm::mgamma_fix | Gamma random walk around a fixed point |
bdm::mgnorm< sq_T > | Mpdf with general function for mean value |
bdm::migamma | Inverse-Gamma random walk |
bdm::migamma_ref | Inverse-Gamma random walk around a fixed point |
bdm::MixEF | Mixture of Exponential Family Densities |
bdm::mlnorm< sq_T > | Normal distributed linear function with linear function of mean value; |
bdm::mlognorm | Log-Normal random walk |
bdm::mlstudent | |
bdm::mmix | Mixture of mpdfs with constant weights, all mpdfs are of equal type |
bdm::mpdf | Conditional probability density, e.g. modeling some dependencies |
bdm::MPF< BM_T > | Marginalized Particle filter |
bdm::mprod | Chain rule decomposition of epdf |
bdm::mratio | Class representing ratio of two densities which arise e.g. by applying the Bayes rule. It represents density in the form:
where |
bdm::multiBM | Estimator for Multinomial density |
OMk1 | Model stredni hodnoty pozorovani pro k1 |
OMpmsm | Observation model for PMSM drive and its derivative with respect to |
bdm::PF | Trivial particle filter with proposal density equal to parameter evolution model |
pmsmCRB | This class behaves like BM but it is evaluating EKF |
pmsmDS | Simulator of PMSM machine with predefined profile on omega |
bdm::RV | Class representing variables, most often random variables |
sqmat | Virtual class for representation of double symmetric matrices in square-root form |
bdm::str | Structure of RV (used internally), i.e. expanded RVs |
UIARX | |
UIArxDS | |
bdm::UIbuilder | Builds computational object from a UserInfo structure |
UIdirfilelog | UI for dirfilelog (Kst file format) |
bdm::UIexternal | |
bdm::UIinternal | |
UImexDS | Create memory data source from mxArray |
UImgnorm | |
UImigamma_ref | |
UImlognorm | |
UIMPF | |
UIpmsmDS | UI for pmsmDS, |
UIpmsmOM | UI for pmsm observation model |
UIrv | UI for class RV (description of data vectors) |
UIstateDS |