enforce_identifiability: Control parameters output

In bastienchassagnol/RGMMBench: A benchmark on Gaussian mixtures in R

Control parameters output

Description

This step ensures that the estimates returned are uniquely ordered by partial ordering on the means, and that the sum-o-one constraint, that may be violated by numerical artefacts, is enforced

Usage

enforce_identifiability(theta)

Arguments

theta

estimation of the parameters returned either by an initialisation algorithm or by an EM algorithm on an univariate or multivariate GMM MLE estimation The proportions p: p of each component (must be included between 0 and 1, and sum to one overall) The mean matrix mu: \mathrm{\mu}=(\mu_{i,j}) \in \mathbb{R}^{n \times k}, with each column giving the mean values of the variables within a given component The 3-dimensional covariance matrix array Sigma: \mathrm{\Sigma}=(\Sigma_{i,j,l}) \in \mathbb{R}^{n \times n \times k}, with each matrix \Sigma_{..l}, l \in \{ 1, \ldots, k\} storing the covariance matrix of a given component, whose diagonal terms correspond to the variance of each variable, and off-terms diagonal elements return the covariance matrix

Value

a list of the estimates, uniquely identified, by ranking each component based on the ordering of their means

bastienchassagnol/RGMMBench documentation built on Oct. 26, 2023, 5:58 p.m.