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

Mohammed S. Kotb () and Huda M. Alomari ()
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Mohammed S. Kotb: Al-Azhar University
Huda M. Alomari: Al-Baha University

Statistical Papers, 2024, vol. 65, issue 5, No 19, 3135-3154

Abstract: 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.

Keywords: Maximum likelihood estimator; Bayes estimator; Entropy; Progressive First-Failure censored sampling; Confidence interval; MCMC simulation; 62F10; 62F15; 62F25; 62N01 (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s00362-023-01508-y

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