Stochastic comparisons of finite mixture models derived from distorted distributions: results based on vector and multivariate chain majorization approaches

In this paper, we focus on classical finite mixture models, which are widely used in modeling lifetime distributions for random samples arising from heterogeneous populations. We then develop results in two directions. First, we carry out stochastic comparisons of finite mixture models derived from distorted distributions based on vector majorization. Next, we use the concept of multivariate chain majorization to establish further comparison results for finite mixture models from distorted distributions. These comparisons are made in terms of various stochastic orders, including the usual stochastic, hazard rate, reversed hazard rate and dispersive orders.

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Publication Details

Journal
Journal of Inequalities and Applications
Published
2026-02-23
DOI
https://doi.org/10.1186/s13660-026-03450-7
Primary Topic
Statistical Distribution Estimation and Applications
Type
article
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article

Stochastic comparisons of finite mixture models derived from distorted distributions: results based on vector and multivariate chain majorization approaches

Zohreh Pakdaman, Marzieh Shekari, N. Balakrishnan, G. Saadat Kia Barmalzan
Journal of Inequalities and Applications
Statistical Distribution Estimation and Applications
article

Stochastic comparisons of finite mixture models derived from distorted distributions: results based on vector and multivariate chain majorization approaches

Zohreh Pakdaman, Marzieh Shekari, N. Balakrishnan, G. Saadat Kia Barmalzan
article en

Abstract

In this paper, we focus on classical finite mixture models, which are widely used in modeling lifetime distributions for random samples arising from heterogeneous populations. We then develop results in two directions. First, we carry out stochastic comparisons of finite mixture models derived from distorted distributions based on vector majorization. Next, we use the concept of multivariate chain majorization to establish further comparison results for finite mixture models from distorted distributions. These comparisons are made in terms of various stochastic orders, including the usual stochastic, hazard rate, reversed hazard rate and dispersive orders.

Journal of Inequalities and ApplicationsVol. 2026(1)
University of Hormozgan (IR), Kermanshah University of Technology (IR), McMaster University (CA)
Openalex Percentile: Top 50%
Statistical Distribution Estimation and Applications
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