Bayesian analysis for dependent competing risks model with masked causes of failure in step-stress accelerated life test under progressive hybrid censoring

This article considers the statistical analysis of dependent competing risks model with masked causes of failure in step-stress accelerated life test, where the failure times of the competing risks at each stress level follow Weibull distribution and they are related to the Khamis-Higgins model assumptions. In the usual step-stress experiment, the expected lifetime of the experimental unit is shortened as the stress level increases. We provided Bayesian inference of the unknown parameters under this restriction using the prior assumption. In addition, Bayesian predictive estimates and prediction intervals for the future observations are obtained. Finally, simulations are performed to demonstrate the performances of the estimates, and one data set has been analyzed for illustrative purposes.