Mixture of extended Birnbaum-Saunders distributions: an approach via the mean-mixture of normal models

Authors

  • Shahrbanoo Mahbudi Department of Statistics‎, ‎Science and Research Branch‎, ‎Islamic Azad University‎, ‎Tehran‎, ‎Iran
  • Ahad Jamalizadeh Department of Statistics‎, ‎Faculty of Mathematics and Computer‎, ‎Shahid Bahonar University of Kerman‎, ‎Kerman‎, ‎Iran
  • Rahman Farnoosh Department of Applied Mathematics, Iran University of Science and Technology, Tehran, Iran

DOI:

https://doi.org/10.30495/jme.v15i0.1293

Keywords:

Birnbaum-Saunders distribution, Mean-mixtures of normal distributions, Finite mixture model, ECM algorithm.

Abstract

The Birnbaum-Saunders (BS) distribution is one of the most con-sidered right-skewed distributions to model failure times for materials subjectto lifetime data. In this paper, a new extension of the BS model is initiallyproposed based on the family of mean-mixtures of normal distributions. Then,we present a new probabilistic mixture model based on the new extended BSdistribution for modeling and clustering right-skewed and heavy-tailed data.The maximum likelihood (ML) parameter estimates of the model in questionare estimated by employing an expectation-maximization (EM) type algorithm.Moreover, the empirical information matrix is derived by using an information-based approach. Simulations and real data analysis illustrate the performanceof the proposed methodology.

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Published

2020-01-28

Issue

Vol. 15

Section

Vol. 15, No. 2, (2021)

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