Bayesian Estimation and Application of Shifted Exponential Mixture Distribution
In this study, Bayesian parameter estimation for the shifted exponential mixture model is conducted by using informative priors under squared error loss function (SELF), weighted loss function (WLF) and quadratic loss function (QLF). Properties of the proposed Bayes estimators (BEs) are highlighted through simulation study. One and two sample prediction bounds are obtained. Proposed mixture model is applied to a real life example.