在一般的整数值时间序列中检测流行病变化点.
Mamadou Lamine Diop1, William Kengne1
1THEMA, CY Cergy Paris Université, Cergy-Pontoise Cedex, France.
Journal of applied statistics
|April 17, 2024
概括
本研究引入了一种新方法,用于检测离散时间序列数据中的结构变化,即使数据分布未知. 拟议的方法有效地使用Poisson准最大概率估计器识别流行病变化点.
科学领域:
- 统计 统计 统计 统计
- 计量经济学 计量经济学
- 时间序列分析时间序列分析
背景情况:
- 时间序列数据的结构变化会对模型准确性产生重大影响.
- 检测这些变化,特别是在分布未知的离散值序列中,会带来分析挑战.
- 现有的方法可能无法在如此复杂的数据中充分解决流行病转变点场景.
研究的目的:
- 开发一种可靠的方法来检测离散值时间序列中的结构变化.
- 提出一种基于准最大概率估计的流行病变化点检测测试.
- 为拟议的估计器和测试统计数据建立理论保证.
主要方法:
- 使用Poisson准最大概率估计器 (QMLE) 对未知条件分布的模型.
- 从QMLE中开发一个测试统计数据,以检测参数变化.
- 分析QMLE的异面性质 (一致性和正常性).
- 在零 (没有变化) 和替代 (流行病变化) 假设下调查测试统计数据的行为.
主要成果:
- 建立了足够的条件,以确保Poisson QMLE的一致性和异常正常性.
- 提出了一种用于流行病变化点检测的新型测试统计.
- 在零假设下,测试统计数据汇聚到已知的分布 (布罗恩桥增量).
- 在流行病替代方案下,测试统计数据有所不同,证实了该程序的功率一致性.
结论:
- 拟议的Poisson QMLE为具有变化参数的离散时间序列提供了一个一致的和异常正常的估计器.
- 开发的变化点检测测试是有效的,并且在统计学上是有效的,用于识别流行性结构断裂.
- 该方法通过模拟和现实世界数据分析进行验证,证明其实际适用性.
关键词:
62F03 这是什么意思?62F12 这是一个很好的例子.62M1010 它们是什么?离散估值时间序列.鱼QMLE是什么意思变化点检测 变化点检测流行病替代品 流行病替代品这是一个半参数统计数据.更多相关视频
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