Finite mixture of skewed sub-Gaussian stable distributions

2022/05/27 by Mahdi Teimouri, Teimouri, Mahdi
Computer Science · Mathematics · #60E07 #Bayesian Methods and Mixture Models #Census and Population Estimation #FOS: Computer and information sciences #MSC 62H30 #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Methodology (stat.ME) #Statistical Methods and Bayesian Inference

paper · pdf · doi:10.48550/arxiv.2205.14067

openalex publication_date 2022/05/27 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

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.

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