Estimating the entropy of a Rayleigh model under progressive first-failure censoring
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 estima...
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| Veröffentlicht in: | Statistical papers (Berlin, Germany) Germany), 2024-07, Vol.65 (5), p.3135-3154 |
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| container_title | Statistical papers (Berlin, Germany) |
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| creator | Kotb, Mohammed S. Alomari, Huda M. |
| description | 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. |
| doi_str_mv | 10.1007/s00362-023-01508-y |
| format | Article |
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| subjects | Confidence intervals Economic Theory/Quantitative Economics/Mathematical Methods Economics Entropy Estimators Experiments Finance Insurance Management Mathematics and Statistics Monte Carlo simulation Operations Research/Decision Theory Probability Theory and Stochastic Processes Random variables Rayleigh distribution Regular Article Statistical analysis Statistics Statistics for Business |
| title | Estimating the entropy of a Rayleigh model under progressive first-failure censoring |
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