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A novel extension of half-logistic distribution with statistical inference, estimation and applications.
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- Author(s): Bhat, A. A.; Ahmad, S. P.; Gemeay, Ahmed M.; Muse, Abdisalam Hassan; Bakr, M. E.; Balogun, Oluwafemi Samson
- Source:
Scientific Reports; 2/21/2024, Vol. 14 Issue 1, p1-17, 17p- Subject Terms:
- Source:
- Additional Information
- Abstract: In the present study, we develop and investigate the odd Frechet Half-Logistic (OFHL) distribution that was developed by incorporating the half-logistic and odd Frechet-G family. The OFHL model has very adaptable probability functions: decreasing, increasing, bathtub and inverted U shapes are shown for the hazard rate functions, illustrating the model's capacity for flexibility. A comprehensive account of the mathematical and statistical properties of the proposed model is presented. In estimation viewpoint, six distinct estimation methodologies are used to estimate the unknown parameters of the OFHL model. Furthermore, an extensive Monte Carlo simulation analysis is used to evaluate the effectiveness of these estimators. Finally, two applications to real data are used to demonstrate the versatility of the suggested method, and the comparison is made with the half-logistic and some of its well-known extensions. The actual implementation shows that the suggested model performs better than competing models. [ABSTRACT FROM AUTHOR]
- Abstract: Copyright of Scientific Reports is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
- Abstract:
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