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High-dimensional Berry-Esseen Bound for $m$-Dependent Random Samples (2212.05355v1)
Published 10 Dec 2022 in math.PR, math.ST, and stat.TH
Abstract: In this work, we provide a $(n/m){-1/2}$-rate finite sample Berry-Esseen bound for $m$-dependent high-dimensional random vectors over the class of hyper-rectangles. This bound imposes minimal assumptions on the random vectors such as nondegenerate covariances and finite third moments. The proof uses inductive relationships between anti-concentration inequalities and Berry--Esseen bounds, which are inspired by the telescoping method of Chen and Shao (2004) and the recursion method of Kuchibhotla and Rinaldo (2020). Performing a dual induction based on the relationships, we obtain tight Berry-Esseen bounds for dependent samples.
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