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Statistical Inference for Mixed Burr Type II Distribution using a Bayesian Framework
Abstract
Burr distribution is a useful model for the life-testing of the products that age with time. This paper develops a Bayesian analysis in the context of new improved informative priors for the parameters of the mixture of Burr Type-II distribution using the censored data. The Bayes estimators of the said parameters have been derived under the assumption of informative
priors using Precautionary loss function. The motivation has been to explore the most appropriate prior for the Burr mixture. We model the heterogeneous population using two components mixture of the Burr Type-II distribution. A comprehensive simulation scheme including a number of parameter points has been conducted to highlight the properties and behavior of the estimates in terms of sample size, parameter size, corresponding risks and the mixing weights. A censored mixture data has been simulated by probabilistic mixing for the computational purpose.
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