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arXiv 2003.12573math.STmath.PRstat.TH
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基于加权两样本U统计量的变点检测

Change-point detection based on weighted two-sample U-statistics

Herold Dehling, Kata Vuk, Martin Wendler

AI总结:

本文研究了短程相关数据下基于加权两样本U统计量的变点检验的大样本行为,证明了其向极值分布的收敛性,并发现加权检验在变点靠近边界时优于非加权版本,但在中心处功效较弱。

摘要:

我们研究了在短程相关数据情况下,基于加权两样本U统计量的变点检验的大样本行为。在一些温和的混合条件下,我们建立了检验统计量向极值分布的收敛性。一项模拟研究表明,当变点发生在时间区间边界附近时,加权检验优于非加权版本,而在中心处则会损失功效。

英文摘要:

We investigate the large-sample behavior of change-point tests based on weighted two-sample U-statistics, in the case of short-range dependent data. Under some mild mixing conditions, we establish convergence of the test statistic to an extreme value distribution. A simulation study shows that the weighted tests are superior to the non-weighted versions when the change-point occurs near the boundary of the time interval, while they loose power in the center.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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