文章基本信息

标题：Statistical Inference for Progressive Stress Accelerated Life Testing with Birnbaum-Saunders Distribution
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作者：Naijun Sha
期刊名称：Stats
电子版ISSN：2571-905X
出版年度：2018
卷号：1
期号：1
页码：189-203
DOI：10.3390/stats1010014
出版社：MDPI AG
摘要：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.
关键词：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