Improved Bayes estimators and prediction for the Wilson-Hilferty distribution
Abstract: In this paper, we revisit the Wilson-Hilferty distribution and presented its mathematical properties such as the r-th moments and reliability properties. The parameters estimators are discussed using objective reference Bayesian analysis for both complete and censored data where the resulting marginal posterior intervals have accurate frequentist coverage. A simulation study is presented to compare the performance of the proposed estimators with the frequentist approach where it is observed a clear advantage for the Bayesian method. Finally, the proposed methodology is illustrated on three real datasets.
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| Main Authors: | , , , |
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| Format: | Digital revista |
| Language: | English |
| Published: |
Academia Brasileira de Ciências
2019
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| Online Access: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652019000500202 |
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| Summary: | Abstract: In this paper, we revisit the Wilson-Hilferty distribution and presented its mathematical properties such as the r-th moments and reliability properties. The parameters estimators are discussed using objective reference Bayesian analysis for both complete and censored data where the resulting marginal posterior intervals have accurate frequentist coverage. A simulation study is presented to compare the performance of the proposed estimators with the frequentist approach where it is observed a clear advantage for the Bayesian method. Finally, the proposed methodology is illustrated on three real datasets. |
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