Bayesian Predictive Intervals Based on Type-II Hybrid Censored Data

Document Type

Article

Publication Date

2020

Abstract

Prediction of future events on the basis of the past and present knowledge is a fundamental problem of statistics; in this paper we discuss the one- and two- sample Bayesian prediction problem from generalized linear exponential distribution based on Type- II hybrid censored data. Fort his problem, the Gibbs sampling procedure and Lindley approximation are used to approximate the Bayesian predictive survival function, and several hyper parameters are used to show the sensitivity of Bayesian Predictive Intervals with respect to these hyper parameters. Finally, some numerical results are presented.

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