连续概率分布的新型概括的韦布尔·波松G类,其中有一些配方,属性和对现实数据集的应用
Atef F Hashem1,2, M A Abdelkawy1,2, Abdisalam Hassan Muse3
1Department of Mathematics and Statistics, College of Science, Imam Mohammad Ibn Saud Islamic University (IMSIU), 11432, Riyadh, Saudi Arabia.
Scientific reports
|January 19, 2024
概括
这项研究引入了新的偶数合概率分布,包括广义的韦布尔Poisson-G家族,用于建模复杂数据. 这些多功能分布有助于研究人员和统计学家在现实应用中做出明智的决策.
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:
- 复杂的多变量数据交互需要先进的建模技术.
- 传统的概率分布可能无法充分捕捉各种现实世界的事件.
- 偶联分布为建模相互依赖提供了更大的灵活性.
研究的目的:
- 介绍和分析新的偶联概率分布.
- 开发通用的韦布尔鱼类-G家族和新的双变型G家族.
- 用真实数据集证明这些分布的实际实用性.
主要方法:
- 数学分析统计属性的数学分析.
- 通过结合现有的分布来构建复合的G家族.
- 应用各种各样的 (克莱顿,冈贝尔,莫根斯特恩等) 和度的措施.
- 使用洛马克斯分布作为基本模型.
主要成果:
- 成功构建和数学分析了广义的韦布尔Poisson-G家族.
- 使用多样化的体结构开发新的双变型G型家族.
- 证明分布能够模拟复杂的依赖关系的能力.
- 通过两个实例来证明家庭的重要性.
结论:
- 拟议的偶分布是多功能和数学上健全的.
- 这些模型有效地捕捉了多变量数据中的复杂的相互依赖关系.
- 这些发现为研究人员,统计学家和数据分析和决策从业人员提供了宝贵的工具.
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