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Bibliographic Details
Main Author: Bonis, Thomas
Format: Preprint
Published: 2023
Subjects:
Online Access:https://arxiv.org/abs/2305.14248
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author Bonis, Thomas
author_facet Bonis, Thomas
contents We provide new bounds for the rate of convergence of the multivariate Central Limit Theorem in Wasserstein distances of order $p \geq 2$. 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.
format Preprint
id arxiv_https___arxiv_org_abs_2305_14248
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Improved rates of convergence for the multivariate Central Limit Theorem in Wasserstein distance
Bonis, Thomas
Probability
We provide new bounds for the rate of convergence of the multivariate Central Limit Theorem in Wasserstein distances of order $p \geq 2$. 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.
title Improved rates of convergence for the multivariate Central Limit Theorem in Wasserstein distance
topic Probability
url https://arxiv.org/abs/2305.14248