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Estimating the entropy of a Rayleigh model under progressive first-failure censoring

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  • Mohammed S. Kotb

    (Al-Azhar University
    Al-Baha University)

  • Huda M. Alomari

    (Al-Baha University)

Abstract

Based on a progressive first-failure censoring (PFFC) sample, we discuss the statistical inferences of the entropy of a Rayleigh distribution. In particular, the Maximum likelihood and the different Bayes estimates for entropy are derived and compared via a Monte Carlo simulation study. Bayes estimators are developed using both symmetric and asymmetric loss functions. Approximate confidence intervals (CIs) and credible intervals (CrIs) of the entropy of the model are also performed. Numerical examples and a real data set are given to illustrate the proposed estimators.

Suggested Citation

  • Mohammed S. Kotb & Huda M. Alomari, 2024. "Estimating the entropy of a Rayleigh model under progressive first-failure censoring," Statistical Papers, Springer, vol. 65(5), pages 3135-3154, July.
    • Handle: RePEc:spr:stpapr:v:65:y:2024:i:5:d:10.1007_s00362-023-01508-y
    DOI: 10.1007/s00362-023-01508-y
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    References listed on IDEAS

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