bdm::MixEF Class Reference

Mixture of Exponential Family Densities. More...

#include <mixtures.h>

List of all members.

Detailed Description

Mixture of Exponential Family Densities.

An approximate estimation method for models with latent discrete variable, such as mixture models of the following kind:

where is a known function of past outputs, are component weights, and component parameters are assumed to be mutually independent. is an aggregation af all component parameters and weights, i.e. .

The characteristic feature of this model is that if the exact values of the latent variable were known, estimation of the parameters can be handled by a single model. For example, for the case of mixture models, posterior density for each component parameters would be a BayesianModel from Exponential Family.

This class uses EM-style type algorithms for estimation of its parameters. Under this simplification, the posterior density is a product of exponential family members, hence under EM-style approximate estimation this class itself belongs to the exponential family.

Two methods are provided:

• QB where the probability of being from one component is computed using predictors,
• EM where the data is assigned to component with the highest likelihood (winner takes all)

These methods are stored in attribute options:

• method: ["EM","QB"] estimation method as mentioned above, QB is default
• max_niter: maximum of iterations in bayes_batch()

Member Function Documentation

    class = 'MixEF';
    Coms = { list of bdm::BMEF };                    % list of components containing any offsprings of Bayesian models BMEF, bdm::BMEF::from_setting
    weights = [...];                                 % vector containing weights of components
    --- optional fields ---
    options = configuration of bdm::MixEF::Options;  % see MixEF::Options, bdm::MixEF::Options::from_setting
    --- inherited fields ---
    bdm::BMEF::from_setting

• mixtures.h
• mixtures.cpp