Bayesian Prediction Intervals Based on Type-I Hybrid Censored Data from the Lomax Distribution under Step-Stress Model

Abdalla Rabie, Abd EL-Baset A. Ahmad, Mohamad A. Fawzy, Tahani A. Aloafi and Ali Sajid

Journal of Mathematics, 2022, vol. 2022, 1-10

Abstract: The Bayesian prediction of future failures from Lomax distribution is the subject of this research. The observed data is censored using a Type-I hybrid censoring scheme under a step-stress partially accelerated life test. There are two types of sampling schemes considered: one-sample and two-sample. We create predictive intervals for failure observations in the future. Bayesian prediction intervals are constructed using MCMC algorithms. After all, two numerical examples, simulation study and a real-life example are provided for both one-sample and two-sample methods for the purpose of illustration.

Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jjmath:2801582

DOI: 10.1155/2022/2801582

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