Two-sample Dvoretzky-Kiefer-Wolfowitz inequalities
Publication
, Journal Article
Wei, F; Dudley, RM
Published in: Statistics and Probability Letters
The Dvoretzky-Kiefer-Wolfowitz (DKW) inequality says that if F n is an empirical distribution function for variables i.i.d. with a distribution function F, and K n is the Kolmogorov statistic nsupx{pipe}(Fn-F)(x){pipe}, then there is a constant C such that for any M>0, Pr(K n>M)≤Cexp(-2M 2). Massart proved that one can take C=2 (DKWM inequality), which is sharp for F continuous. We consider the analogous Kolmogorov-Smirnov statistic for the two-sample case and show that for m=n, the DKW inequality holds for n≥n 0 for some C depending on n 0, with C=2 if and only if n 0≥458.The DKWM inequality fails for the three pairs (m, n) with 1 ≤ m< n≤ 3. We found by computer search that the inequality always holds for n≥ 4 if 1 ≤ m< n≤ 200, and further for n= 2 m if 101 ≤ m≤ 300. We conjecture that the DKWM inequality holds for all pairs m≤ n with the 457 + 3 = 460 exceptions mentioned. © 2011 Elsevier B.V.