Bayesian analysis for 3-component mixture of exponentiated Weibull distribution assuming non-informative priors

Abstract

ABSTRACTBayesian analysis of 3-component mixture model, of exponentiated Weibull distribution under type-I right censoring scheme, is explored in this study. With the help of non-informative (uniform and Jeffreys) priors and loss functions (e.g. squared error loss function, quadratic loss function, precautionary loss function and DeGroot loss function), Bayes estimators and posterior risks are derived. The Bayes estimators and posterior risks are observed as a function of the test termination time. Simulation study as well as a practical example is given in this study.