Bayesian prediction of future observations from weighted exponential distribution constant-stress model based on Type-II hybrid censored data. Issue 12 (18th June 2021)

• Record Type: Journal Article
• Authors: Ahmad, Abd EL-Baset A.; Fawzy, Mohamad A.; Ouda, Hosam
• Is Part Of: Communications in statistics. Volume 50:Issue 12(2021)
• Page Start: 2732
• Page End: 2746
• Publication Date: 2021-06-18
• Subjects: Bayesian prediction -- Type-II hybrid censored sample -- constant-stress partially accelerated life test -- Weighted exponential distribution -- Markov Chain Monte Carlo technique; 62Fxx -- 62F15; Mathematical statistics -- Periodicals; Mathematics; Statistics; 519.2
• DOI: 10.1080/03610926.2019.1667394
• Languages: English
• ISSNs: 0361-0926

Abstract

Abstract: In this paper, the problem of Bayesian prediction intervals for a future observations from weighted exponential distribution is concerned. Constant-stress partially accelerated life test under Type-II hybrid censoring scheme of the observed data is used. One- and two-sample Bayesian prediction intervals for a future observations based on Type-II hybrid censored data are derived. Markov Chain Monte Carlo (MCMC) technique is used to find Bayesian predictive intervals because one- and two-sample Bayesian predictive survival function cannot be obtained in closed-form. Finally, some numerical results are presented to illustrate all the inferential results developed in this paper.