Investigation of scale parameter for the Weibull-Chen distribution
Within this article, we estimate the scale parameter for the Weibull-Chen distribution and calculate posterior distributions. This analysis involves the application of the Bayesian technique, which utilizes two non-informative priors along with three distinct loss functions. The aim of utilizing the...
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| Format: | Article |
| Language: | English |
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Taylor & Francis
2025-05-01
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| Series: | Research in Statistics |
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| Online Access: | https://www.tandfonline.com/doi/10.1080/27684520.2025.2507619 |
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| author | Mohamed Mubarak Fathy H. Riad |
| author_facet | Mohamed Mubarak Fathy H. Riad |
| author_sort | Mohamed Mubarak |
| collection | DOAJ |
| description | Within this article, we estimate the scale parameter for the Weibull-Chen distribution and calculate posterior distributions. This analysis involves the application of the Bayesian technique, which utilizes two non-informative priors along with three distinct loss functions. The aim of utilizing these loss functions is to produce the Bayes estimators and compare their performance using simulation and real-world applications. The optimal combination of a loss function and a prior can be determined by minimizing Bayes risk and achieving the best results. |
| format | Article |
| id | doaj-art-5aaa2f59a72f4d8c92d22c8fbedb1c27 |
| institution | DOAJ |
| issn | 2768-4520 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | Taylor & Francis |
| record_format | Article |
| series | Research in Statistics |
| spelling | doaj-art-5aaa2f59a72f4d8c92d22c8fbedb1c272025-08-20T03:20:11ZengTaylor & FrancisResearch in Statistics2768-45202025-05-013110.1080/27684520.2025.2507619Investigation of scale parameter for the Weibull-Chen distributionMohamed Mubarak0Fathy H. Riad1Department of Mathematics, Faculty of Science, Minia University, Minia, EgyptDepartment of Mathematics, College of Science, Jouf University, Sakaka, Saudi ArabiaWithin this article, we estimate the scale parameter for the Weibull-Chen distribution and calculate posterior distributions. This analysis involves the application of the Bayesian technique, which utilizes two non-informative priors along with three distinct loss functions. The aim of utilizing these loss functions is to produce the Bayes estimators and compare their performance using simulation and real-world applications. The optimal combination of a loss function and a prior can be determined by minimizing Bayes risk and achieving the best results.https://www.tandfonline.com/doi/10.1080/27684520.2025.2507619Bayesian analysisScale parameterWeibull-Chen (WC) distributionUniform priorJeffrey priorLoss functions |
| spellingShingle | Mohamed Mubarak Fathy H. Riad Investigation of scale parameter for the Weibull-Chen distribution Research in Statistics Bayesian analysis Scale parameter Weibull-Chen (WC) distribution Uniform prior Jeffrey prior Loss functions |
| title | Investigation of scale parameter for the Weibull-Chen distribution |
| title_full | Investigation of scale parameter for the Weibull-Chen distribution |
| title_fullStr | Investigation of scale parameter for the Weibull-Chen distribution |
| title_full_unstemmed | Investigation of scale parameter for the Weibull-Chen distribution |
| title_short | Investigation of scale parameter for the Weibull-Chen distribution |
| title_sort | investigation of scale parameter for the weibull chen distribution |
| topic | Bayesian analysis Scale parameter Weibull-Chen (WC) distribution Uniform prior Jeffrey prior Loss functions |
| url | https://www.tandfonline.com/doi/10.1080/27684520.2025.2507619 |
| work_keys_str_mv | AT mohamedmubarak investigationofscaleparameterfortheweibullchendistribution AT fathyhriad investigationofscaleparameterfortheweibullchendistribution |