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A Novel Extension of the Inverse Rayleigh Distribution: Theory, Simulation, and Real-World Application |
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PP: 467-488 |
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doi:10.18576/amis/190220
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Author(s) |
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Alaa A. Khalaf,
Mundher A. Khaleel,
Taghreed M. Jawa,
Neveen Sayed-Ahmed,
Ahlam H. Tolba,
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Abstract |
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Generalized distributions benefit applied statisticians, and there are several approaches to expanding common distributions. This article presents a new sub-model, the Odd Burr XII-inverse Rayleigh (OBXII-IR) distribution, as well as a new family of generalized distributions, the Odd Burr-G family. To generate the OBXII-G family, we combine the T-X family with the Burr XII distribution. Examine a few OBXII-IR distribution statistics. These statistics include moments, incomplete moments, quantile function, order statistics, harmonic mean, and Re ́nyi entropy. The methods used for parameter estimation include maximum likelihood, least squares, weighted least squares, Anderson Darling, and right-tailed Anderson Darling. This research evaluates the performance of these different estimators using a Monte Carlo simulation. The distribution’s applicability to two real data sets proves that the OBXII-IR distribution is really useful and practical.
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