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

Department of Mathematical Sciences, University of Texas at El Paso, El Paso, TX 79968, USA
Current address: 500W University Ave., El Paso, TX 79968, USA.
Stats 2018, 1(1), 189-203; https://doi.org/10.3390/stats1010014
Received: 11 November 2018 / Revised: 7 December 2018 / Accepted: 10 December 2018 / Published: 12 December 2018
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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. View Full-Text
Keywords: progressive accelerated life testing; generalized Birnbaum–Saunders distribution; Bayesian inference; Fisher’s information; MCMC sampling progressive accelerated life testing; generalized Birnbaum–Saunders distribution; Bayesian inference; Fisher’s information; MCMC sampling
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Sha, N. Statistical Inference for Progressive Stress Accelerated Life Testing with Birnbaum-Saunders Distribution. Stats 2018, 1, 189-203.

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