Bayesian Analysis Of Gumbel Type II Distribution Under Doubly Censored Samples Using Different Loss Functions

Gumbel type II distribution is very usfull in life testing. In this paper, the Bayesian analysis of this distribution under the doubly censored data has been considered. The posterior distributions have been derived under the assumption of informative and non-informative priors. The Bayes estimates and associated risks have been obtained under the assumption of each prior using different loss functions. The Bayesian credible intervals have also been constructed and evaluated. The posterior predictive distributions have been derived to predict the future values of the variable. The performance of the estimates have been compared under a simulation study along with a real life data.