Inference on Step-Stress Life Testing Model Using Type-II Censoring

Partially accelerated life test(s) (PALT(s)) of highly reliable products or materials is a good testing method to collect failure data rapidly without putting all test units under severe conditions. This article considers both likelihood and Bayesian estimation of the step-stress PALT model under Type-II censoring when the lifetimes of products follow the generalized exponential distribution. The maximum likelihood and Bayesian estimates of the model parameters are obtained. The posterior means and posterior variances are computed under the squared error (SE) loss function using Lindley’s procedure. The performance of the estimators is evaluated numerically for different parameter values and different sample sizes via their mean squared error. In addition, the average confidence intervals lengths of the model parameters are also obtained. For illustration, a simulation study is provided.