gmm_init_vector: Estimate Gaussian Mixture parameters using Expectation...

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

Estimate Gaussian Mixture parameters using Expectation Maximisation.

Description

Estimate an initialisation vector for Gaussian mixture fitting via Expectation Maximisation. Proportions and scales are set to equal, centers are equispaced through the whole domain of input sample.

Usage

    gmm_init_vector( x, n, implementation = "C" )

Arguments

x	data vector
n	number of mixture components
implementation	flag to switch between C (default) and R implementations.

Value

Parameter 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, sigma1, sigma2, ..., sigman ), where Ai is the proportion of i-th component, mui is the location of i-th component, sigmai is the scale of i-th component.

Author(s)

Andrius Merkys

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