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Heavy-Tailed Extended Exponential Log-Logistic Distribution: Properties and Applications
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Seyed Jamal, Khorashadizadeh    , Fatemeh Yousefzadeh * , Sara Jomhoori |
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Abstract: (1144 Views) |
| Researchers develop generalized families of distributions to better model data in fields like risk management, economics, and insurance. In this paper, a new distribution, the Extended Exponential Log-Logistic Distribution, is introduced, which belongs to the class of heavy-tailed distributions. Some statistical properties of the model, including moments, moment-generating function, entropy, and economic inequality curves, are derived. Six estimation methods are proposed for estimating the model parameters, and the performance of these methods is evaluated using randomly generated datasets. Additionally, several insurance-related measures, including Value at Risk, Tail Value at Risk, Tail Variance, and Tail Variance Premium, are calculated. Finally, two real insurance datasets are employed, showing that the proposed model fits the data better than many existing related models. |
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| Keywords: Risk measures, Extended Exponential Log-Logistic Distribution, Parameter estimation, Tail Variance Premium, Value at Risk, Tail Value at Risk |
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Full-Text [PDF 557 kb]
(490 Downloads)
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Type of Study: Applied |
Subject:
Applied Statistics
Received: 2025/05/29 | Accepted: 2025/04/30 | Published: 2025/11/26
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