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用于r-最大顺序统计的通用Gumbel模型,并应用到峰值流量流量
Yire Shin1,2, Jeong-Soo Park3,4
1Department of Statistics, Chonnam National University, 61186, Gwangju, Korea.
Scientific reports
|March 4, 2025
概括
本研究引入了一种新的灵活模型,即r-最大顺序统计 (rGGD) 的通用甘贝尔分布,以更好地分析稀缺的极端值数据. rGGD改进了rLOS的标准Gumbel分布,为极端事件提供了增强的建模功能.
科学领域:
- 极端价值分析是一种极端价值分析.
- 统计建模 统计建模
- 可能性分布的概率分布.
背景情况:
- 极端值是罕见的,需要有效的分析方法.
- 对于r-最大顺序统计 (rGD) 的Gumbel分布受到其两个参数结构的限制.
- 区块最大值方法可能比使用r-最大顺序统计 (rLOS) 效率低.
研究的目的:
- 将rLOS的Gumbel分布扩展到一个更灵活的三参数模型.
- 为rLOS (rGGD) 引入通用的冈贝尔分布.
- 为新的rGGD模型提供可靠的统计推断方法.
主要方法:
- 对rGGD.的概率函数的推导.
- 应用最大概率估计和参数估计的三角形方法.
- 使用差测试和交叉验证的概率来进行模型选择和推理.
主要成果:
- 拟议的rGGD模型在捕捉r-最大数据的可变性方面表现出更大的灵活性.
- 蒙特卡洛模拟证实了该模型的有用性和有效性.
- 对峰值流量数据的应用显示了实际适用性.
结论:
- 对于rLOS (rGGD) 的通用贝尔分布,它为极端价值分析提供了一种更具适应性的方法.
- 开发的推理方法为应用rGGD提供了坚实的框架.
- 该模型可以帮助设计工程结构,以减轻极端事件带来的风险.
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