A Flexible Extension to an Extreme Distribution
The aim of this paper is not only to propose a new extreme distribution, but also to show that the new extreme model can be used as an alternative to well-known distributions in the literature to model various kinds of datasets in different fields. Several of its statistical properties are explored....
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-04-01
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| Series: | Symmetry |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2073-8994/13/5/745 |
| _version_ | 1797536587312005120 |
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| author | Mohamed S. Eliwa Fahad Sameer Alshammari Khadijah M. Abualnaja Mahmoud El-Morshedy |
| author_facet | Mohamed S. Eliwa Fahad Sameer Alshammari Khadijah M. Abualnaja Mahmoud El-Morshedy |
| author_sort | Mohamed S. Eliwa |
| collection | DOAJ |
| description | The aim of this paper is not only to propose a new extreme distribution, but also to show that the new extreme model can be used as an alternative to well-known distributions in the literature to model various kinds of datasets in different fields. Several of its statistical properties are explored. It is found that the new extreme model can be utilized for modeling both asymmetric and symmetric datasets, which suffer from over- and under-dispersed phenomena. Moreover, the hazard rate function can be constant, increasing, increasing–constant, or unimodal shaped. The maximum likelihood method is used to estimate the model parameters based on complete and censored samples. Finally, a significant amount of simulations was conducted along with real data applications to illustrate the use of the new extreme distribution. |
| first_indexed | 2024-03-10T12:01:54Z |
| format | Article |
| id | doaj.art-6f8dc0bf47cf43689e22f1007158924d |
| institution | Directory Open Access Journal |
| issn | 2073-8994 |
| language | English |
| last_indexed | 2024-03-10T12:01:54Z |
| publishDate | 2021-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Symmetry |
| spelling | doaj.art-6f8dc0bf47cf43689e22f1007158924d2023-11-21T16:53:20ZengMDPI AGSymmetry2073-89942021-04-0113574510.3390/sym13050745A Flexible Extension to an Extreme DistributionMohamed S. Eliwa0Fahad Sameer Alshammari1Khadijah M. Abualnaja2Mahmoud El-Morshedy3Department of Mathematics, Faculty of Science, Mansoura University, Mansoura 35516, EgyptDepartment of Mathematics, College of Science and Humanities in Al-Kharj, Prince Sattam bin Abdulaziz University, Al-Kharj 11942, Saudi ArabiaDepartment of Mathematics and Statistics, College of Science, Taif University, P.O. Box 11099, Taif 21944, Saudi ArabiaDepartment of Mathematics, College of Science and Humanities in Al-Kharj, Prince Sattam bin Abdulaziz University, Al-Kharj 11942, Saudi ArabiaThe aim of this paper is not only to propose a new extreme distribution, but also to show that the new extreme model can be used as an alternative to well-known distributions in the literature to model various kinds of datasets in different fields. Several of its statistical properties are explored. It is found that the new extreme model can be utilized for modeling both asymmetric and symmetric datasets, which suffer from over- and under-dispersed phenomena. Moreover, the hazard rate function can be constant, increasing, increasing–constant, or unimodal shaped. The maximum likelihood method is used to estimate the model parameters based on complete and censored samples. Finally, a significant amount of simulations was conducted along with real data applications to illustrate the use of the new extreme distribution.https://www.mdpi.com/2073-8994/13/5/745probability distributionsskewed and symmetric datamaximum likelihood estimationhazard rate functioncensored samples |
| spellingShingle | Mohamed S. Eliwa Fahad Sameer Alshammari Khadijah M. Abualnaja Mahmoud El-Morshedy A Flexible Extension to an Extreme Distribution Symmetry probability distributions skewed and symmetric data maximum likelihood estimation hazard rate function censored samples |
| title | A Flexible Extension to an Extreme Distribution |
| title_full | A Flexible Extension to an Extreme Distribution |
| title_fullStr | A Flexible Extension to an Extreme Distribution |
| title_full_unstemmed | A Flexible Extension to an Extreme Distribution |
| title_short | A Flexible Extension to an Extreme Distribution |
| title_sort | flexible extension to an extreme distribution |
| topic | probability distributions skewed and symmetric data maximum likelihood estimation hazard rate function censored samples |
| url | https://www.mdpi.com/2073-8994/13/5/745 |
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