A Central Limit Theorem for Semidiscrete Wasserstein Distances
Probability
2021-05-26 v1
Abstract
We address the problem of proving a Central Limit Theorem for the empirical optimal transport cost, , in the semi discrete case, i.e when the distribution is finitely supported. We show that the asymptotic distribution is the supremun of a centered Gaussian process which is Gaussian under some additional conditions on the probability and on the cost. Such results imply the central limit theorem for the -Wassertein distance, for . Finally, the semidiscrete framework provides a control on the second derivative of the dual formulation, which yields the first central limit theorem for the optimal transport potentials.
Cite
@article{arxiv.2105.11721,
title = {A Central Limit Theorem for Semidiscrete Wasserstein Distances},
author = {Eustasio del Barrio and Alberto González-Sanz and Jean-Michel Loubes},
journal= {arXiv preprint arXiv:2105.11721},
year = {2021}
}