English

High-dimensional central limit theorems for homogeneous sums

Probability 2021-09-20 v3 Statistics Theory Statistics Theory

Abstract

This paper develops a quantitative version of de Jong's central limit theorem for homogeneous sums in a high-dimensional setting. More precisely, under appropriate moment assumptions, we establish an upper bound for the Kolmogorov distance between a multi-dimensional vector of homogeneous sums and a Gaussian vector so that the bound depends polynomially on the logarithm of the dimension and is governed by the fourth cumulants and the maximal influences of the components. As a corollary, we obtain high-dimensional versions of fourth moment theorems, universality results and Peccati-Tudor type theorems for homogeneous sums. We also sharpen some existing (quantitative) central limit theorems by applications of our result.

Keywords

Cite

@article{arxiv.1902.03809,
  title  = {High-dimensional central limit theorems for homogeneous sums},
  author = {Yuta Koike},
  journal= {arXiv preprint arXiv:1902.03809},
  year   = {2021}
}

Comments

49 pages. Some errors have been corrected. Application to a statistical problem has been added

R2 v1 2026-06-23T07:37:26.915Z