On Posterior Analysis of Mixture of Two Components of Gumbel Type II Distribution

This paper describes the Bayesian analysis of the parameters of mixture of two components of Gumbel type II distribution. A heterogeneous population has been modeled by means of two components mixture of the Gumbel type II distribution under type I censored data. The Bayes estimators of the said parameters have been derived under the assumption of non-informative priors on the basis of different loss functions. A censored mixture data is simulated by probabilistic mixing for the computational purpose. The comparisons among the estimators have been made in terms of corresponding posterior risks. The posterior predictive distributions and intervals have been derived and evaluated under each prior.