Bayesian Prediction Intervals Based on Progressive Type-II Censored Sample from a General Class of Distributions
Abdou, S., Mohie El-Din, M., Sadek, A. (2025). Bayesian Prediction Intervals Based on Progressive Type-II Censored Sample from a General Class of Distributions. EKB Journal Management System, (), -. doi: 10.21608/absb.2025.441164
Salwa Reda Abdou; Mostafa Mohamed Mohie El-Din; Amr Fouad Sadek. "Bayesian Prediction Intervals Based on Progressive Type-II Censored Sample from a General Class of Distributions". EKB Journal Management System, , , 2025, -. doi: 10.21608/absb.2025.441164
Abdou, S., Mohie El-Din, M., Sadek, A. (2025). 'Bayesian Prediction Intervals Based on Progressive Type-II Censored Sample from a General Class of Distributions', EKB Journal Management System, (), pp. -. doi: 10.21608/absb.2025.441164
Abdou, S., Mohie El-Din, M., Sadek, A. Bayesian Prediction Intervals Based on Progressive Type-II Censored Sample from a General Class of Distributions. EKB Journal Management System, 2025; (): -. doi: 10.21608/absb.2025.441164

Bayesian Prediction Intervals Based on Progressive Type-II Censored Sample from a General Class of Distributions

Al-Azhar Bulletin of Science
Articles in Press, Accepted Manuscript, Available Online from 12 July 2025  XML
Document Type: Original Article
DOI: 10.21608/absb.2025.441164
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Authors
Salwa Reda Abdou email 1; Mostafa Mohamed Mohie El-Din2; Amr Fouad Sadek2
1Dept. of Math., Faculty of Science, Fayoum University, Fayoum, Egypt.
2Dept. of Math., Faculty of Science, Al-Azhar University, Nasr City, Cairo, Egypt.
Abstract
In this paper, we consider a general class of distributions for constructing one and two-sample Bayesian prediction intervals assuming a progressive Type-II censored sample. Approximate predictive survival functions are obtained using importance sampling and Markov Chain Monte Carlo (MCMC) techniques. The resulting outcomes are illustrated using examples from the inverse Weibull, inverted exponential, and Gompertz distributions. Finally, several real-life data sets are presented to demonstrate the conclusions reached here.
Keywords
Bayesian prediction; Gompertz distribution; Importance sampling technique; Inverse Weibull distribution; Markov Chain Monte Carlo technique; Progressive Type-II censored
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