Bayesian estimation of Marshall–Olkin extended exponential parameters under various approximation techniques

Abstract

In this paper, we propse Bayes estimators of the parameters of Marshall Olkin extended exponential distribution (MOEED) introduced by Marshall-Olkin [2] for complete sample under squared error loss function (SELF). We have used different approximation techniques to obtain the Bayes estimate of the parameters. A Monte Carlo simulation study is carried out to compare the performance of proposed estimators with the corresponding maximum likelihood estimator (MLE’s) on the basis of their simulated risk. A real data set has been considered for illustrative purpose of the study.