Improved central limit theorem and bootstrap approximations in high dimensions

DOI10.1214/22-AOS2193WikidataQ115021747 ScholiaQ115021747MaRDI QIDQ2105184

Denis Chetverikov, Victor Chernozhuokov, Yuta Koike, Kengo Kato

Publication date: 8 December 2022

Published in: The Annals of Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1912.10529

zbMATH Keywords

bootstrapcentral limit theoremStein kerneliterative randomized Lindeberg method

Mathematics Subject Classification ID

Central limit and other weak theorems (60F05) Approximations to statistical distributions (nonasymptotic) (62E17)

Related Items (9)

A penalized two-pass regression to predict stock returns with time-varying risk premia ⋮ Nearly optimal central limit theorem and bootstrap approximations in high dimensions ⋮ Testing the martingale difference hypothesis in high dimension ⋮ Central limit theorems for high dimensional dependent data ⋮ Bridging factor and sparse models ⋮ Robust high-dimensional tuning free multiple testing ⋮ StarTrek: combinatorial variable selection with false discovery rate control ⋮ Estimation of smooth functionals in high-dimensional models: bootstrap chains and Gaussian approximation ⋮ Improved central limit theorem and bootstrap approximations in high dimensions

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