E-Bayesian Estimation Based On Generalized Half Logistic Progressive Type-II Censored Data

Abstract

In this paper, given a progressively type II censored sample from a generalized half logistic distribution, the Bayesian and E-Bayesian (expectation of the Bayesian estimate) estimators are obtained under LINEX and squared-error loss functions, for the parameter and reliability function. Monte Carlo simulation method is used to generate a progressive Type-II censored data from generalized half logistic distribution, then these data is used to compute the estimations of the parameter and compare both the methods used when different random schemes.