Concentration inequalities, large and moderate deviations for self-normalized empirical processes

11Citations
Citations of this article
10Readers
Mendeley users who have this article in their library.

Abstract

We consider the supremum Wn of self-normalized empirical processes indexed by unbounded classes of functions F. Such variables are of interest in various statistical applications, for example, the likelihood ratio tests of contamination. Using the Herbst method, we prove an exponential concentration inequality for ann under a second moment assumption on the envelope function of F. This inequality is applied to obtain moderate deviations for Wn. We also provide large deviations results for some unbounded parametric classes F.

Cite

CITATION STYLE

APA

Bercu, B., Gassiat, E., & Rio, E. (2002). Concentration inequalities, large and moderate deviations for self-normalized empirical processes. Annals of Probability, 30(4), 1576–1604. https://doi.org/10.1214/aop/1039548367

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free