smm_fit_em_CWL04: Greedily estimate Student's t Mixture parameters using...

In merkys/MixtureFitting: Fitting of univariate mixture distributions to data using various approaches

Greedily estimate Student's t Mixture parameters using Expectation Maximisation.

Description

Estimates (greedily) parameters for univariate Student's t mixture using Expectation Maximisation algorithm, implemented according to Chen et al. (2004). The algorithm relies upon smm_fit_em_GNL08() to estimate mixture parameters iteratively.

Usage

    smm_fit_em_CWL04( x, p, collect.history = FALSE, debug = FALSE,
                      ... )

Arguments

x	data vector
p	initialisation vector of 4*n parameters, where n is number of mixture components. Structure of p vector is p = c( A1, A2, ..., An, mu1, mu2, ..., mun, k1, k2, ..., kn, ni1, ni2, ..., nin ), where Ai is the proportion of i-th component, mui is the center of i-th component, ki is the concentration of i-th component and nii is the degrees of freedom of i-th component.
collect.history	logical. If set to TRUE, a list of parameter values of all iterations is returned.
debug	flag to turn the debug prints on/off.
...	parameters passed to smm_fit_em_GNL08().

Value

A list.

Author(s)

Andrius Merkys

References

Chen, S.; Wang, H. & Luo, B. Greedy EM Algorithm for Robust T-Mixture Modeling Third International Conference on Image and Graphics (ICIG'04), Institute of Electrical & Electronics Engineers (IEEE), 2004, 548–551

merkys/MixtureFitting documentation built on May 25, 2024, 9:01 a.m.