A robust model-based clustering based on the geometric median and the Median Covariation Matrix
Methodology
2022-11-16 v1 Statistics Theory
Statistics Theory
Abstract
Grouping observations into homogeneous groups is a recurrent task in statistical data analysis. We consider Gaussian Mixture Models, which are the most famous parametric model-based clustering method. We propose a new robust approach for model-based clustering, which consists in a modification of the EM algorithm (more specifically, the M-step) by replacing the estimates of the mean and the variance by robust versions based on the median and the median covariation matrix. All the proposed methods are available in the R package RGMM accessible on CRAN.
Keywords
Cite
@article{arxiv.2211.08131,
title = {A robust model-based clustering based on the geometric median and the Median Covariation Matrix},
author = {Antoine Godichon-Baggioni and Stéphane Robin},
journal= {arXiv preprint arXiv:2211.08131},
year = {2022}
}