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<p>This paper provides sufficient conditions for stochastic comparisons between two finite mixture models (FMMs) in the sense of the usual stochastic order under the assumption that the mixing observations have exponentiated location-scale (ELS) family of distributions. The sufficient conditions are based on majorization orders between the vectors of mixing proportions and/or model parameters of the finite mixtures (FMs). Specifically, the stochastic comparisons are carried out while heterogeneity occurs in one model parameter or occurs in both mixing proportion and a model parameter. To justify the theoretical findings, some relevant numerical examples and counterexamples are provided.</p>

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Ordering Results for Two Finite Mixture Models with Exponentiated Location-Scale Distributed Components

  • 期刊论文

  • 发表日期：

    2025年9月10日

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  • Raju Bhakta,
  • Pradip Kundu,
  • Suchandan Kayal

摘要

This paper provides sufficient conditions for stochastic comparisons between two finite mixture models (FMMs) in the sense of the usual stochastic order under the assumption that the mixing observations have exponentiated location-scale (ELS) family of distributions. The sufficient conditions are based on majorization orders between the vectors of mixing proportions and/or model parameters of the finite mixtures (FMs). Specifically, the stochastic comparisons are carried out while heterogeneity occurs in one model parameter or occurs in both mixing proportion and a model parameter. To justify the theoretical findings, some relevant numerical examples and counterexamples are provided.