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Classical and Bayesian Inference under Burr‐X Distribution Based on New Unified Progressive Hybrid Censoring Scheme with Engineering Applications

Author

Listed:
  • Saieed F. Ateya
  • Randa Alharbi
  • Mutua Kilai
  • Ramy Aldallal

Abstract

In this paper, a new unified progressive hybrid censoring scheme (UPHCS) has been constructed. This unified censoring scheme covers eleven famous censoring schemes. The estimation problem of Burr‐X distribution parameters has been studied using the maximum likelihood and Bayes approaches based on the suggested unified progressive hybrid censored samples. Two real data sets have been used as illustrative engineering examples.

Suggested Citation

  • Saieed F. Ateya & Randa Alharbi & Mutua Kilai & Ramy Aldallal, 2022. "Classical and Bayesian Inference under Burr‐X Distribution Based on New Unified Progressive Hybrid Censoring Scheme with Engineering Applications," Journal of Mathematics, John Wiley & Sons, vol. 2022(1).
    • Handle: RePEc:wly:jjmath:v:2022:y:2022:i:1:n:3746821
    DOI: 10.1155/2022/3746821
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    References listed on IDEAS

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    1. B. Chandrasekar & A. Childs & N. Balakrishnan, 2004. "Exact likelihood inference for the exponential distribution under generalized Type‐I and Type‐II hybrid censoring," Naval Research Logistics (NRL), John Wiley & Sons, vol. 51(7), pages 994-1004, October.
    2. Manoj Rastogi & Yogesh Tripathi, 2013. "Inference on unknown parameters of a Burr distribution under hybrid censoring," Statistical Papers, Springer, vol. 54(3), pages 619-643, August.
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