High-Dimensional Data Bootstrap

doi:10.1146/annurev-statistics-040120-022239

High-Dimensional Data Bootstrap

2023-03-10

8

OA

AI

V

Victor Chernozhukov *

DOI：10.1146/annurev-statistics-040120-022239

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This article reviews recent progress in high-dimensional bootstrap. We first review high-dimensional central limit theorems for distributions of sample mean vectors over the rectangles, bootstrap consistency results in high dimensions, and key techniques used to establish those results. We then review selected applications of high-dimensional bootstrap: construction of simultaneous confidence sets for high-dimensional vector parameters, multiple hypothesis testing via step-down, postselection inference, intersection bounds for partially identified parameters, and inference on best policies in policy evaluation. Finally, we also comment on a couple of future research directions.

Keyword:

empirical bootstrap

high-dimensional central limit theorem

multiple testing

multiplier bootstrap

simultaneous inference

High-Dimensional Data Bootstrap

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