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

Author

Listed:
  • Abdalla Rabie
  • Abd EL-Baset A. Ahmad
  • Mohamad A. Fawzy
  • Tahani A. Aloafi

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.

Suggested Citation

  • Abdalla Rabie & Abd EL-Baset A. Ahmad & Mohamad A. Fawzy & Tahani A. Aloafi, 2022. "Bayesian Prediction Intervals Based on Type‐I Hybrid Censored Data from the Lomax Distribution under Step‐Stress Model," Journal of Mathematics, John Wiley & Sons, vol. 2022(1).
    • Handle: RePEc:wly:jjmath:v:2022:y:2022:i:1:n:2801582
    DOI: 10.1155/2022/2801582
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    References listed on IDEAS

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