Bayesian inferences and prediction of exponentiated exponential distribution based on multiple interval censored data

This article carefully defines a multiple interval censoring plan, and its scope of application in the Bayesian setup is demonstrated. The Bayes estimators of shape and scale parameters of the exponentiated exponential distribution are obtained under symmetric and asymmetric loss functions. Additionally, the credible intervals for both parameters are obtained. The performances of Bayes estimators and credible intervals are investigated through the appropriate Monte Carlo method. Furthermore, the authors also considered the prediction of future samples as well as the prediction interval. Lastly, a real-world example is presented in order to illustrate the effectiveness of the proposed methods.