Normal approximation for nonlinear statistics using a concentration inequality approach

Abstract

Let $T$ be a general sampling statistic that can be written as a linear statistic plus an error term. Uniform and non-uniform Berry--Esseen type bounds for $T$ are obtained. The bounds are the best possible for many known statistics. Applications to U-statistics, multisample U-statistics, L-statistics, random sums and functions of nonlinear statistics are discussed.

Published at http://dx.doi.org/10.3150/07-BEJ5164 in the Bernoulli (http://isi.cbs.nl/bernoulli/) by the International Statistical Institute/Bernoulli Society (http://isi.cbs.nl/BS/bshome.htm)

References in corpus (1)

• Normal approximation for nonlinear statistics using a concentration inequality approach

Cited by in corpus (2)

• Normal approximation for nonlinear statistics using a concentration inequality approach
• Monotonicity properties of the asymptotic relative efficiency between common correlation statistics in the bivariate normal model