Abstract
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.
Original language | English (US) |
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Pages (from-to) | 715-726 |
Number of pages | 12 |
Journal | Statistical Papers |
Volume | 55 |
Issue number | 3 |
DOIs | |
State | Published - Jul 2014 |
Keywords
- Bayesian inference
- Cumulative exposure model
- Proportional hazard model
- Step-stress accelerated life test
- Weibull distribution
ASJC Scopus subject areas
- Statistics and Probability
- Statistics, Probability and Uncertainty