Bayesian Estimation of Parameter For Different Loss Functions Using Progressive Type-II Censored Data

In this present work, we are going to show the various useful propertiesof the existing distribution known as MG_Exp(ε)-distribution which have notquoted by the host authors like moments, mean deviation about mean, meandeviation about median, order statistics, count of uncertainty. Estimation procedures have been adopted under Bayesian estimation for progressive Type-II censored case. Simulation study has also been carried out to judge the behaviour of the Bayes estimator at the long-run. Performance of the Bayes estimators and their posterior risks of the considered loss functions have been obtained, reported and compared for the considered values of sample size, effective sample size, parameter and removals. The comparison of Bayes estimators of all 6 chosen loss functions have been done on the groundof lowest posterior risks.