指数式的冈贝尔-韦布尔 (Logistic) 分布与尼日利亚的COVID-19感染数据的应用
Patrick Osatohanmwen1, Eferhonore Efe-Eyefia2, Francis O Oyegue3
1School of Science and Technology, Pan-Atlantic University, Lagos, Nigeria.
概括
开发了一个新的灵活的概率分布,即指数化的冈贝尔-韦布尔逻辑分布. 这种分布有效地模拟了现实世界的数据,包括COVID-19感染,展示了它的多功能性.
科学领域:
- 统计 统计 统计 统计
- 可能性理论概率理论.
- 数学建模的数学建模
背景情况:
- 需要灵活的概率分布来建模复杂的真实世界数据是显著的.
- 现有的分布可能无法捕捉到各种现象中观察到的各种形状和尾巴行为.
研究的目的:
- 引入和定义一种新的灵活的单变概率分布.
- 调查拟议分布的统计性质和灵活性.
- 为了证明新分布在现实世界的数据适配中的适用性.
主要方法:
- 使用指数化的冈贝尔分布,通过物流分布的量子函数生成通用的韦布尔分布.
- 研究了新分布的详细统计性质.
- 用最大概率方法进行了参数估计.
主要成果:
- 新的"指数加倍的冈贝尔-韦布尔物流分布"被成功定义.
- 该分布表现出单模和双模特征,以及多功能形状和尾部特性.
- 该分布证明了对尼日利亚的COVID-19日常感染数据和其他五个不同的数据集的有效匹配.
结论:
- 指数化的冈贝尔-韦布尔物流分布为统计建模提供了灵活而有效的工具.
- 它能够捕获各种数据模式的能力使其适用于广泛的应用.
- 该发行版在真实世界数据集上的性能验证了其实用性和灵活性.
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