vmm_fit_em: Estimate von Mises Mixture parameters using Expectation...

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

Estimate von Mises Mixture parameters using Expectation Maximisation.

Description

Estimates parameters for univariate von Mises mixture using Expectation Maximisation algorithm.

Usage

    vmm_fit_em( x, p, epsilon = c( 0.000001, 0.000001, 0.000001 ),
                debug = FALSE, implementation = "C" )

Arguments

x	data vector
p	initialisation vector of 3*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 ), where Ai is the proportion of i-th component, mui is the center of i-th component and ki is the concentration of i-th component.
epsilon	tolerance threshold for convergence. Structure of epsilon is epsilon = c( epsilon_A, epsilon_mu, epsilon_k ), where epsilon_A is threshold for component proportions, epsilon_mu is threshold for component centers and epsilon_k is threshold for component concentrations.
debug	flag to turn the debug prints on/off.
implementation	flag to switch between C (default) and R implementations.

Value

Vector of mixture parameters, whose structure is the same as of input parameter's p.

Author(s)

Andrius Merkys

References

Banerjee et al. Expectation Maximization for Clustering on Hyperspheres (2003), manuscript, accesible on: http://www.lans.ece.utexas.edu/~abanerjee/papers/05/banerjee05a.pdf

merkys/MixtureFitting documentation built on Feb. 26, 2023, 5:21 p.m.