Department of Mathematics & Statistics, College of Science, Taif University, Taif, Saudi Arabia.
Department of Mathematics, College of Education, Misan University, Amarah, Iraq.
PLoS One. 2023 Feb 2;18(2):e0275430. doi: 10.1371/journal.pone.0275430. eCollection 2023.
In this work, a new flexible class, called the type-I extended-F family, is proposed. A special sub-model of the proposed class, called type-I extended-Weibull (TIEx-W) distribution, is explored in detail. Basic properties of the TIEx-W distribution are provided. The parameters of the TIEx-W distribution are obtained by eight classical methods of estimation. The performance of these estimators is explored using Monte Carlo simulation results for small and large samples. Besides, the Bayesian estimation of the model parameters under different loss functions for the real data set is also provided. The importance and flexibility of the TIEx-W model are illustrated by analyzing an insurance data. The real-life insurance data illustrates that the TIEx-W distribution provides better fit as compared to competing models such as Lindley-Weibull, exponentiated Weibull, Kumaraswamy-Weibull, α logarithmic transformed Weibull, and beta Weibull distributions, among others.
在这项工作中,提出了一个新的灵活类别,称为 I 型扩展 F 族。详细探讨了所提出类别中的一个特殊子模型,称为 I 型扩展威布尔(TIEx-W)分布。提供了 TIEx-W 分布的基本性质。通过八种经典的估计方法获得 TIEx-W 分布的参数。通过小样本和大样本的蒙特卡罗模拟结果探讨了这些估计器的性能。此外,还提供了在不同损失函数下对真实数据集的模型参数进行贝叶斯估计。通过分析保险数据来说明 TIEx-W 模型的重要性和灵活性。实际的保险数据表明,与其他竞争模型(如林德利-威布尔、指数威布尔、库马拉斯瓦米-威布尔、α对数转换威布尔和β威布尔分布等)相比,TIEx-W 分布提供了更好的拟合。