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

Shubham Agnihotri (), Sanjay Kumar Singh () and Umesh Singh ()
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Shubham Agnihotri: Banaras Hindu University
Sanjay Kumar Singh: Banaras Hindu University
Umesh Singh: Banaras Hindu University

Computational Statistics, 2025, vol. 40, issue 5, No 13, 2635-2655

Abstract: Abstract 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.

Keywords: Multiple interval censoring plan; Bayesian prediction; Exponentiated exponential distribution; MCMC algorithm (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s00180-024-01565-3

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