Finite mixture of skewed sub-Gaussian stable distributions
Methodology
2022-05-30 v1 Machine Learning
Machine Learning
Abstract
We propose the finite mixture of skewed sub-Gaussian stable distributions. The maximum likelihood estimator for the parameters of proposed finite mixture model is computed through the expectation-maximization algorithm. The proposed model contains the finite mixture of normal and skewed normal distributions. Since the tails of proposed model is heavier than even the Student's t distribution, it can be used as a powerful model for robust model-based clustering. Performance of the proposed model is demonstrated by clustering simulation data and two sets of real data.
Keywords
Cite
@article{arxiv.2205.14067,
title = {Finite mixture of skewed sub-Gaussian stable distributions},
author = {Mahdi Teimouri},
journal= {arXiv preprint arXiv:2205.14067},
year = {2022}
}