Distribution's template estimate with Wasserstein metrics
Statistics Theory
2013-12-12 v2 Statistics Theory
Abstract
In this paper we tackle the problem of comparing distributions of random variables and defining a mean pattern between a sample of random events. Using barycenters of measures in the Wasserstein space, we propose an iterative version as an estimation of the mean distribution. Moreover, when the distributions are a common measure warped by a centered random operator, then the barycenter enables to recover this distribution template.
Cite
@article{arxiv.1111.5927,
title = {Distribution's template estimate with Wasserstein metrics},
author = {Emmanuel Boissard and Thibaut Le Gouic and Jean-Michel Loubes},
journal= {arXiv preprint arXiv:1111.5927},
year = {2013}
}