Finite sampling inequalities: an application to two-sample Kolmogorov-Smirnov statistics
Statistics Theory
2017-02-20 v3 Statistics Theory
Abstract
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.
Cite
@article{arxiv.1502.00342,
title = {Finite sampling inequalities: an application to two-sample Kolmogorov-Smirnov statistics},
author = {Evan Greene and Jon A. Wellner},
journal= {arXiv preprint arXiv:1502.00342},
year = {2017}
}
Comments
16 pages