Robust inference for parsimonious model-based clustering

ABSTRACT

We introduce a robust clustering procedure for parsimonious model-based clustering. The classical mclust framework is robustified through impartial trimming and eigenvalue-ratio constraints (the tclust framework, which is robust but not affine invariant). An advantage of our resulting mtclust approach is that eigenvalue-ratio constraints are not needed for certain model formulations, leading to affine invariant robust parsimonious clustering. We illustrate the approach via simulations and a benchmark real data example. R code for the proposed method is available at https://github.com/afarcome/mtclust.

KEYWORDS:

• mclust
• tclust
• factor model
• groups
• affine invariance

Acknowledgments

The authors are grateful to one referee for kind suggestions.

Disclosure statement

No potential conflict of interest was reported by the authors.