Kilai Mutua, Waititu Gichuhi A, Kibira Wanjoya A, Alshanbari Huda M, El-Morshedy M
Department of Mathematics, Pan African Insitute of Basic Science, Technology and Innovation, Nairobi, Kenya.
Department of Statistics and Actuarial Sciences, Jomo Kenyatta University of Agriculture and Technology, Nairobi, Kenya.
Results Phys. 2022 May;36:105339. doi: 10.1016/j.rinp.2022.105339. Epub 2022 Mar 21.
This paper proposes a new generalization of the Gull Alpha Power Family of distribution, namely the exponentiated generalized gull alpha power family of distribution abbreviated as (EGGAPF) with two additional parameters. This proposed family of distributions has some well known sub-models. Some of the basic properties of the distribution like the hazard function, survival function, order statistics, quantile function, moment generating function are investigated. In order to estimate the parameters of the model the method of maximum likelihood estimation is used. To assess the performance of the MLE estimates a simulation study was performed. It is observed that with increase in sample size, the average bias, and the RMSE decrease. A distribution from this family is fitted to two real data sets and compared to its sub-models. It can be concluded that the proposed distribution outperforms its sub-models.
本文提出了广义鸥α幂分布族的一种新的推广形式，即带两个附加参数的指数广义鸥α幂分布族，简称为（EGGAPF）。该分布族有一些著名的子模型。研究了该分布的一些基本性质，如风险函数、生存函数、顺序统计量、分位数函数、矩生成函数。为了估计模型参数，采用了极大似然估计法。为评估极大似然估计的性能进行了模拟研究。观察到随着样本量的增加，平均偏差和均方根误差减小。将该分布族中的一种分布拟合到两个实际数据集，并与其子模型进行比较。可以得出结论，所提出的分布优于其子模型。
