Statistical Inference for Progressive Stress Accelerated Life Testing with Birnbaum-Saunders Distribution

Naijun Sha
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Naijun Sha: Department of Mathematical Sciences, University of Texas at El Paso, El Paso, TX 79968, USA

Stats, 2018, vol. 1, issue 1, 1-15

Abstract: As a result of the two-parameter Birnbaum–Saunders (BS) distribution being successful in modelling fatigue failure times, several extensions of this model have been explored from different aspects. In this article, we consider a progressive stress accelerated life testing for the BS model to introduce a generalized Birnbaum–Saunders (we call it Type-II GBS) distribution on the lifetime of products in the test. We outline some interesting properties of this highly flexible distribution, present the Fisher’s information in the maximum likelihood estimation method, and propose a new Bayesian approach for inference. Simulation studies are carried out to assess the performance of the methods under various settings of parameter values and sample sizes. Real data are analyzed for illustrative purposes to demonstrate the efficiency and accuracy of the proposed Bayesian method over the likelihood-based procedure.

Keywords: progressive accelerated life testing; generalized Birnbaum–Saunders distribution; Bayesian inference; Fisher’s information; MCMC sampling (search for similar items in EconPapers)
JEL-codes: C1 C10 C11 C14 C15 C16 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:gam:jstats:v:1:y:2018:i:1:p:14-203:d:190124

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