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.
Citation
Emmanuel Boissard. Thibaut Le Gouic. Jean-Michel Loubes. "Distribution’s template estimate with Wasserstein metrics." Bernoulli 21 (2) 740 - 759, May 2015. https://doi.org/10.3150/13-BEJ585
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