Improved rates of convergence for the multivariate Central Limit Theorem in Wasserstein distance
Probability
2024-04-30 v4
Abstract
We provide new bounds for the rate of convergence of the multivariate Central Limit Theorem in Wasserstein distances of order . In particular, we obtain what we conjecture to be the asymptotically optimal rate whenever the density of the summands admits a non-zero continuous component and has a non-zero third moment.
Keywords
Cite
@article{arxiv.2305.14248,
title = {Improved rates of convergence for the multivariate Central Limit Theorem in Wasserstein distance},
author = {Thomas Bonis},
journal= {arXiv preprint arXiv:2305.14248},
year = {2024}
}