一个经过修订的双方向通用极端值分布:理论和气候数据应用
Cira E G Otiniano1, Mathews N S Lisboa1, Terezinha K A Ribeiro1
1Statistics Department, University of Brasília, Brasília 70910-900, DF, Brazil.
Entropy (Basel, Switzerland)
|July 29, 2025
概括
带有位置参数的新双式通用极端值 (BGEV) 分布增强了极端事件建模的灵活性. 这种2024年重新定义的模型为气候数据分析提供了改进的实际应用和统计属性.
科学领域:
- 统计 统计 统计 统计
- 极端价值理论 极端价值理论
- 气候科学 气候科学
背景情况:
- 最初的双模通用极端值 (BGEV) 分布 (2023) 为双模极端事件提供了灵活性,但缺乏位置参数,使应用复杂化.
- 一般化极端值 (GEV) 分布是极端事件的标准但不那么灵活的模型.
研究的目的:
- 调查重新定义的BGEV分布的属性,其中包含一个位置参数 (2024).
- 为极端和异质数据增强 BGEV 模型的灵活性和实际应用性.
- 为分析复杂极端事件提供更强大的统计框架.
主要方法:
- 对概率密度函数 (PDF) 和危险率函数的明确表达式的导数.
- 为重新定义的BGEV分布计算量子函数 (QF).
- 确定可识别性质和导出时刻,时刻生成函数 (MGF) 和.
主要成果:
- 重新定义的BGEV分布与位置参数显示了增强的灵活性.
- 成功地获得了关键分布性质的明确数学公式.
- 证实了新的分销类别的可识别性.
- 计算了时刻,MGF和,提供了一个全面的统计概况.
结论:
- 2024年重新定义的BGEV分布为现有的极端价值分析模型提供了更实用和灵活的替代方案.
- 由此产生的属性使得这种新分布在包括气候科学在内的各个领域的应用更加容易.
- 包含位置参数显著提高了模型对现实世界的数据与异质极端事件的实用性.
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