Bayesian Inference of Mixture of two Rayleigh Distributions: A New Look

Abstract

There are several papers which discuss the Bayesian analysis of the mixture models under type I singly censored samples. This paper considers a new methodology for Bayesian analysis of mixture models under doubly censored samples. We have discussed the Bayesian estimation of parameters of the two-component mixture of Rayleigh distribution under square root gamma, Maxwell and half normal priors using two loss functions. Further, we analyzed some simulated and real data sets in order to investigate the performance of the estimators for the parameters of the proposed mixture model.