# Class List

Here are the classes, structs, unions and interfaces with brief descriptions:

bdm::ARX | Linear Autoregressive model with Gaussian noise
bdm::ArxDS | Generator of ARX data
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
bdm::chmat | Symmetric matrix stored in square root decomposition using upper cholesky
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 with a condition
bdm::datalink_m2m |
bdm::Designer | Base class of designers of control strategy
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::egiwmix | Mixture of egiws
bdm::eigamma | Inverse-Gamma posterior density
bdm::eiWishartCh | Inverse Wishart on Choleski decomposition
bdm::EKF< sq_T > | Extended Kalman Filter
bdm::EKFCh | Extended Kalman Filter in Square root
bdm::EKFCh_chQ | Extended Kalman filter in Choleski form 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`
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`
bdm::fsqmat | Fake sqmat. This class maps sqmat operations to operations on full matrix
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
bdm::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::LQG |
bdm::MemDS | Memory storage of off-line data column-wise
bdm::memlog |
bdm::mepdf | Unconditional mpdf, allows using epdf in the role of mpdf
bdm::merger_base | Base class for general combination of pdfs on discrete support
bdm::merger_mix | Merger using importance sampling with mixture proposal density
bdm::MexDS | Memory storage of off-line data column-wise
bdm::mexlog | Logger storing results into an mxArray
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, TEpdf > | 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 RV and RVC
bdm::mpdf | Conditional probability density, e.g. modeling , where is random variable, `rv`, and is conditioning variable, `rvc`
bdm::mpdf_internal< EPDF > | Mpdf with internal epdf that is modified by function `condition`
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
bdm::MultiModel | (Switching) Multiple Model The model runs several models in parallel and evaluates thier weights (fittness)
bdm::object_ptr< T > | A wrapper of shared_ptr which is never empty
bdm::Participant | Basic Participant
bdm::ParticularUI< T > |
bdm::PF | Trivial particle filter with proposal density equal to parameter evolution model
bdm::root | Root class of BDM objects
bdm::RV | Class representing variables, most often random variables
bdm::rwiWishartCh | Random Walk on inverse Wishart
bdm::SettingResolver | This class serves to expand links used within configuration files
bdm::shared_ptr< T > | A naive implementation of roughly a subset of the std::tr1:shared_ptr spec
bdm::sqmat | Abstract class for representation of double symmetric matrices in square-root form
bdm::str | Structure of RV, i.e. RVs expanded into a flat list of IDs, used for debugging
bdm::UI | UI is an abstract class which collects all the auxiliary functions useful to prepare some concrete user-infos
bdm::UIException |
bdm::UIFile | This class serves to load and/or save user-infos into/from configuration files stored on a hard-disk
UImxArray | Class for writing Settings into Matlab's mxArray
UImxConfig | Reimplementation of libconfig's Config class for Matlab mxArray structures