A hierarchical Bayes analysis for one-shot device testing experiment under the assumption of exponentiality

The article considers a two-stage hierarchical Bayes technique to analyze a dataset coming from a “one-shot” device testing experiment. The development is based on the assumption of exponential model for the lifetimes with failure rate regressed according to the Cox proportional hazards model. The Bayes implementation is done through a Gibbs–Metropolis hybridization scheme that easily entertains the missing data cases as well. Lastly, numerical illustration is provided based on a real data example on electro-explosive devices. The results show that the Bayesian method performs considerably well for such type of experiments.