Exponential progressive step-stress life-testing with link function based on Box-Cox transformation

Tsai Hung Fan, Wan Lun Wang, N. Balakrishnan

研究成果: Article同行評審

29 引文 斯高帕斯(Scopus)


In order to quickly extract information on the life of a product, accelerated life-tests are usually employed. In this article, we discuss a k-stage step-stress accelerated life-test with M-stress variables when the underlying data are progressively Type-I group censored. The life-testing model assumed is an exponential distribution with a link function that relates the failure rate and the stress variables in a linear way under the Box-Cox transformation, and a cumulative exposure model for modelling the effect of stress changes. The classical maximum likelihood method as well as a fully Bayesian method based on the Markov chain Monte Carlo (MCMC) technique is developed for inference on all the parameters of this model. Numerical examples are presented to illustrate all the methods of inference developed here, and a comparison of the ML and Bayesian methods is also carried out.

頁(從 - 到)2340-2354
期刊Journal of Statistical Planning and Inference
出版狀態Published - 2008 8月 1

All Science Journal Classification (ASJC) codes

  • 統計與概率
  • 統計、概率和不確定性
  • 應用數學


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