A New Generalized Gamma-Weibull Distribution and its Applications

Nihimat Iyebuhola Aleshinloye, Samuel Adewale Aderoju, Alfred Adewole Abiodun, Bako Lukmon Taiwo
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Abstract

In this paper, a New Generalized Gamma-Weibull (NGGW) distribution is developed by compounding Weibull and generalized gamma distribution. Some mathematical properties such as moments, Rényi entropy and order statistics are derived and discussed. The maximum likelihood estimation (MLE) method is used to estimate the model parameters. The proposed model is applied to two real-life datasets to illustrate its performance and flexibility as compared to some other competing distributions. The results obtained show that the new distribution fits each of the data better than the other competing distributions.
一种新的广义γ -威布尔分布及其应用
本文将广义伽玛分布与威布尔分布复合,得到了一种新的广义伽玛-威布尔分布。推导并讨论了矩、rsamnyi熵和序统计量等数学性质。采用极大似然估计(MLE)方法估计模型参数。将该模型应用于两个实际数据集,以说明与其他竞争分布相比,该模型的性能和灵活性。结果表明,新分布比其他竞争分布更适合每个数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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