Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1145174 | Journal of Multivariate Analysis | 2016 | 20 Pages |
Abstract
We derive central limit theorems for the Wasserstein distance between the empirical distributions of Gaussian samples. The cases are distinguished whether the underlying laws are the same or different. Results are based on the (quadratic) Fréchet differentiability of the Wasserstein distance in the gaussian case. Extensions to elliptically symmetric distributions are discussed as well as several applications such as bootstrap and statistical testing.
Keywords
Related Topics
Physical Sciences and Engineering
Mathematics
Numerical Analysis
Authors
Thomas Rippl, Axel Munk, Anja Sturm,