On the asymptotic distribution of the scan statistic for empirical distributions

被引:0
|
作者
Andrew Ying
Wen-Xin Zhou
机构
[1] University of Pennsylvania,Department of Statistics and Data Science, The Wharton School
[2] University of California San Diego,Department of Mathematics
来源
Extremes | 2022年 / 25卷
关键词
Extremes Theory; Order Statistics; Moderate Deviations; Large Deviations;
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学科分类号
摘要
This paper investigates the asymptotic behavior of several variants of the scan statistic for empirical distributions, which can be applied to detect the presence of an anomalous interval of any given length. In particular, we are interested in a Studentized scan statistic that is often preferable in practice. The main ingredients of our proof include Kolmogorov’s theorem, Poisson approximation, and the technical devices developed by Kabluchko and Wang (Stoch. Process. Their Appl.124 (2014) 2824–2867).
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页码:487 / 528
页数:41
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