Risk Efficiencies of Empirical Bayes and Generalized MaximumLikelihood Estimates for Rayleigh Model under Censored Data

Abstract

The comparison of empirical Bayes and generalized maximum likelihood estimates of reliability performances is made in termsof risk efficiencies when the data are progressively Type II censored from Rayleigh distribution. The empirical Bayes estimatesare obtained using an asymmetric loss function. The risk functions of the estimates and risk efficiencies are obtained under thisloss function. A real data set is presented to illustrate the proposed comparison method, and the performance of the estimates isexamined and compared in terms of risk efficiencies by means of Monte Carlo simulations. The simulation results indicate that theproposed empirical Bayes estimates are more preferable than the generalized maximum likelihood estimates