E-Bayesian estimation and associated properties of simple step-stress model for exponential distribution based on type-Ⅱ censoring

摘要

In this paper, expected Bayesian (E-Bayesian) estimation for the simple step-stress model based on type-II censoring scheme is considered. The case of exponential distribution for the underlying lifetimes is considered assuming a cumulative exposure model. The E-Bayesian estimation is discussed by considering three different prior distributions for the hyperparameters. The E-Bayesian estimators as well as the corresponding E-posterior risks are obtained by using squared error and linear-exponential (LINEX) loss functions. Some properties of the E-Bayesian estimators are also derived. We conduct a simulation study to compare the various estimators and a simulated and real data sets are analyzed to show the applicability of the different estimators. The numerical results show that the E-Bayesian estimators perform better than the classical and Bayesian estimators.