A0162
Title: Central limit theorems in high-dimensions: Recent developments
Authors: Yuta Koike - University of Tokyo (Japan) [presenting]
Abstract: The purpose is to review recent progress in multivariate normal approximation on hyper-rectangles in the high-dimensional setting, where the dimension can be much larger than the sample size. Such an approximation is useful for justifying bootstrap approximations of maximum statistics in high-dimensional settings. It is, therefore, important for uniform inference in high-dimensional models.
