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arXiv 1502.00342math.STstat.TH
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有限抽样不等式在两样本Kolmogorov-Smirnov统计中的应用

Finite sampling inequalities: an application to two-sample Kolmogorov-Smirnov statistics

Evan Greene, Jon A. Wellner

摘要:

我们回顾了Serfling提出的有限采样指数界,并讨论了超几何分布的相关指数界。然后,我们讨论了这样的界限如何激发一些新的结果,两个样本的经验过程。我们的发展补充了Wei和Dudley(2011)关于双侧Kolmogorov-Smirnov统计量的指数界的最新结果,给出了单侧统计量的相应结果,重点是Dvoretzky,Kiefer和Wolfowitz(1956)和Massart(1990)最初证明的单样本统计量的“调整”不等式。

英文摘要:

We review a finite-sampling exponential bound due to Serfling and discuss related exponential bounds for the hypergeometric distribution. We then discuss how such bounds motivate some new results for two-sample empirical processes. Our development complements recent results by Wei and Dudley (2011) concerning exponential bounds for two-sided Kolmogorov - Smirnov statistics by giving corresponding results for one-sided statistics with emphasis on "adjusted" inequalities of the type proved originally by Dvoretzky, Kiefer, and Wolfowitz (1956) and by Massart (1990) for one-sample versions of these statistics.

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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