In this paper, we present a Bayesian analysis for the Weibull proportional hazard (PH) model used in step-stress accelerated life testings. The key mathematical and graphical difference between the Weibull cumulative exposure (CE) model and the PH model is illustrated. Compared with the CE model, the PH model provides more flexibility in fitting step-stress testing data and has the attractive mathematical properties of being desirable in the Bayesian framework. A Markov chain Monte Carlo algorithm with adaptive rejection sampling technique is used for posterior inference. We demonstrate the performance of this method on both simulated and real datasets.
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- Bayesian Analysis for Step-Stress Accelerated Life Testing Using Weibull Proportional Hazard Model
- Sha, Naijun (Author)
- Pan, Rong (Author)
- Ira A. Fulton Schools of Engineering (Contributor)
- Digital object identifier: 10.1007/s00362-013-0521-2
- Identifier TypeInternational standard serial numberIdentifier Value0932-5026
- This is the authors' final accepted manuscript. The final publication is available at http://dx.doi.org/10.1007/s00362-013-0521-2, opens in a new window
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Sha, Naijun, & Pan, Rong (2014). Bayesian analysis for step-stress accelerated life testing using weibull proportional hazard model. STATISTICAL PAPERS, 55(3), 715-726. http://dx.doi.org/10.1007/s00362-013-0521-2