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Bayesian inference and prediction of the Pareto distribution based on ordered ranked set sampling

Author

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  • Mostafa M. Mohie El-Din
  • Mohamed S. Kotb
  • Ehab F. Abd-Elfattah
  • Haidy A. Newer

Abstract

In this paper, order statistics from independent and non identically distributed random variables is used to obtain ordered ranked set sampling (ORSS). Bayesian inference of unknown parameters under a squared error loss function of the Pareto distribution is determined. We compute the minimum posterior expected loss (the posterior risk) of the derived estimates and compare them with those based on the corresponding simple random sample (SRS) to assess the efficiency of the obtained estimates. Two-sample Bayesian prediction for future observations is introduced by using SRS and ORSS for one- and m-cycle. A simulation study and real data are applied to show the proposed results.

Suggested Citation

  • Mostafa M. Mohie El-Din & Mohamed S. Kotb & Ehab F. Abd-Elfattah & Haidy A. Newer, 2017. "Bayesian inference and prediction of the Pareto distribution based on ordered ranked set sampling," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 46(13), pages 6264-6279, July.
    • Handle: RePEc:taf:lstaxx:v:46:y:2017:i:13:p:6264-6279
    DOI: 10.1080/03610926.2015.1124118
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    Cited by:

    1. H. M. Barakat & Haidy A. Newer, 2022. "Exact prediction intervals for future exponential and Pareto lifetimes based on ordered ranked set sampling of non-random and random size," Statistical Papers, Springer, vol. 63(6), pages 1801-1827, December.
    2. Mohammed S. Kotb & Haidy A. Newer & Marwa M. Mohie El-Din, 2024. "Bayesian Inference for the Entropy of the Rayleigh Model Based on Ordered Ranked Set Sampling," Annals of Data Science, Springer, vol. 11(4), pages 1435-1458, August.

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