• Corpus ID: 248693653

# Existence and Consistency of the Maximum Pseudo \b{eta}-Likelihood Estimators for Multivariate Normal Mixture Models

@inproceedings{Chakraborty2022ExistenceAC,
title={Existence and Consistency of the Maximum Pseudo \b\{eta\}-Likelihood Estimators for Multivariate Normal Mixture Models},
author={Soumya Chakraborty and Ayanendranath Basu and Abhik Ghosh},
year={2022}
}
• Published 11 May 2022
• Mathematics
Robust estimation under multivariate normal (MVN) mixture model is always a computational challenge. A recently proposed maximum pseudo β -likelihood estimator aims to estimate the unknown parameters of a MVN mixture model in the spirit of minimum density power divergence (DPD) methodology but with a relatively simpler and tractable computational algorithm even for larger dimensions. In this letter, we will rigorously derive the existence and weak consistency of the maximum pseudo β -likelihood…

## References

SHOWING 1-10 OF 10 REFERENCES

• Computer Science
• 2020
A robust alternative to the ordinary likelihood approach for this estimation problem which performs simultaneous estimation and data clustering and leads to subsequent anomaly detection and is seen to perform competitively or better compared to the popular existing methods.
• Mathematics
• 1998
A minimum divergence estimation method is developed for robust parameter estimation. The proposed approach uses new density-based divergences which, unlike existing methods of this type such as
Overview.- An Overview of Empirical Processes.- Overview of Semiparametric Inference.- Case Studies I.- Empirical Processes.- to Empirical Processes.- Preliminaries for Empirical Processes.-
• P. Deb
• Mathematics
Encyclopedia of Autism Spectrum Disorders
• 2021
Finite mixture models provide a natural way of modeling continuous or discrete outcomes that are observed from populations consisting of a finite number of homogeneous subpopulations. Applications of
• Computer Science
• 2011
Introduction General Notation Illustrative Examples Some Background and Relevant Definitions Parametric Inference based on the Maximum Likelihood Method Hypothesis Testing by Likelihood Methods
• Computer Science
• 1997
A class of procedures based on impartial trimming (self-determined by the data) is introduced with the aim of robustifying k-means, hence the associated clustering analysis. We include a detailed
• Mathematics
• 1996
This chapter discusses Convergence: Weak, Almost Uniform, and in Probability, which focuses on the part of Convergence of the Donsker Property which is concerned with Uniformity and Metrization.
• Computer Science, Mathematics
• 2008
We introduce a new method for performing clustering with the aim of fitting clusters with different scatters and weights. It is designed by allowing to handle a proportion $\alpha$ of contaminating

• 2012