A Bayes approach in step-stress accelerated life testings
Abstract
A Bayesian analysis for the Weibull proportional hazard (PH) model is presented. A comparison between the Weibull PH model and the Weibull cumulative exposure (CE) model is made graphically and mathematically. The PH model is as flexible as the CE model in fitting step-stress data and the mathematical form of the PH model enables researchers to do Bayesian inference much easier than the CE model. In addition, the PH model has the desirable proportional hazard property. A convex tent prior is used for Bayesian analysis. Markov chain Monte Carlo methods are used for posterior inferences. In this study, we adopt two sampling methods. The first way is to draw samples of the unknown parameters individually from each of the conditional posterior density functions. Another way is to perform joint sampling of the unknown parameters from the joint posterior density function. The performance of the two sampling methods is investigated using both simulated and real data sets.
Subject Area
Statistics
Recommended Citation
Teng, Hao Yang, "A Bayes approach in step-stress accelerated life testings" (2015). ETD Collection for University of Texas, El Paso. AAI1594526.
https://scholarworks.utep.edu/dissertations/AAI1594526