Estimation of Two Parameter Birnbaum-Saunders Distribution Based on Type-II Right Censored Reliability Data Using Genetic Algorithm

Authors

  • Ali Assoumani Rassoul Department of Statistics, Çukurova University, Turkey
  • Güzin Yüksel Department of Statistics, Çukurova University, Turkey

Keywords:

Birnbaum-Saunders Distribution, Genetic Algorithm, Maximum Likelihood, Type-II Right Censored Data.

Abstract

The Birnbaum-Saunders (BS) distribution is a common reliability distribution used in
scientific studies. There have been studies in the literature on parameter estimates for this
distribution. Furthermore, in many studies, it is recommended to use genetic algorithm (GA)
optimization methods for parameter estimation in modeling. This article focuses on estimating
the model parameters of a two-parameter Birnbaum-Saunders distribution for type II right
censored reliability data. For parameter estimation of the Birnbaum-Saunders distribution, we
propose the Genetic Algorithm (GA) method as an alternative to the Maximum Likelihood
(ML) estimation method. Psi31 data is often used as an example to show the limitations of
prediction methods when using inaccurate data. In addition, the performances of ML and GA
methods were investigated through Monte Carlo simulation with different sample sizes and
censorship rates.

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Published

13-08-2025

How to Cite

Rassoul, A. A., & Yüksel, G. (2025). Estimation of Two Parameter Birnbaum-Saunders Distribution Based on Type-II Right Censored Reliability Data Using Genetic Algorithm. Communications in Mathematics and Applications, 16(1), 353–366. Retrieved from https://www.journals.rgnpublications.com/index.php/cma/article/view/2259

Issue

Vol. 16 No. 1 (2025)

Section

Research Article

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