A combinatorial approach to small ball inequalities for sums and differences

Abstract

Small ball inequalities have been extensively studied in the setting of Gaussian processes and associated Banach or Hilbert spaces. In this paper, we focus on studying small ball probabilities for sums or differences of independent, identically distributed random elements taking values in very general sets. Depending on the setting--abelian or nonabelian groups, or vector spaces, or Banach spaces--we provide a collection of inequalities relating different small ball probabilities that are sharp in many cases of interest. We prove these distribution-free probabilistic inequalities by showing that underlying them are inequalities of extremal combinatorial nature, related among other things to classical packing problems such as the kissing number problem. Applications are given to moment inequalities.

Typos and grammatical errors are corrected, Section 7.2 (Holder-type inequalities) and Section 7.3 (reverse Holder-type inequalities) in the old draft are combined into one Section 7.2 (Moment inequalities), since a simple proof of the main result of Section 7.3 (Theorem 7.7, old draft, i.e., Corollary 7.8, new draft) is found, Combin. Probab. Comput. 2018

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Cited by in corpus (3)

• Forward and Reverse Entropy Power Inequalities in Convex Geometry
• Sumset estimates in convex geometry
• Tail bounds for sums of independent two-sided exponential random variables