El-Alosey Alaa R, Alotaibi Mohammed S, Gemeay Ahmed M
Department of Mathematics, Faculty of Science, Tanta University, Tanta 31527, Egypt.
Heliyon. 2024 Sep 24;10(19):e38198. doi: 10.1016/j.heliyon.2024.e38198. eCollection 2024 Oct 15.
This paper introduces a novel two-parameter G-family of distributions derived through a mixing approach, where a mixture of the exponentiated G-family with parameter follows gamma distribution. Within this new family, we focus on the mixture of gamma-exponentiated exponential distribution (MGExED) as a key sub-model. The study thoroughly investigates by determining some of the MGExED statistical properties, such as quantile function, moments, and order statistics. The MGExED's parameters are estimated using different estimation methods. Due to the complexity of obtaining explicit forms for MGExED's estimators, the accuracy of these estimates is assessed through Monte Carlo simulations. To illustrate the practical utility of the MGExED, we apply it to two distinct real datasets, demonstrating its superior flexibility and fit compared to several established distributions in the literature. This comprehensive evaluation underscores the MGExED's potential for broader statistical modeling and analysis application.
本文介绍了一种通过混合方法推导出来的新型双参数G族分布，其中参数为 的指数化G族的混合服从伽马分布。在这个新族中，我们将重点关注伽马-指数化指数分布的混合（MGExED）作为关键子模型。该研究通过确定MGExED的一些统计性质，如分位数函数、矩和顺序统计量，进行了深入研究。MGExED的参数使用不同的估计方法进行估计。由于获得MGExED估计量的显式形式较为复杂，这些估计的准确性通过蒙特卡罗模拟进行评估。为了说明MGExED的实际效用，我们将其应用于两个不同的真实数据集，表明它与文献中几个既定分布相比具有更高的灵活性和拟合度。这种全面评估强调了MGExED在更广泛的统计建模和分析应用中的潜力。
