A parametric registration model for warped distributions with Wasserstein’s distance

We consider a parametric deformation model for distributions. More precisely, we assume we observe J samples of random variables which are warped from an unknown distribution template. We tackle in this paper the problem of estimating the individual deformation parameters. For this, we construct a registering criterion based on the Wasserstein distance to quantify the alignment of the distributions. We prove consistency of the empirical estimators.

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Year of publication:	2015
Authors:	Agulló-Antolín, Marina ; Cuesta-Albertos, J.A. ; Lescornel, Hélène ; Loubes, Jean-Michel
Published in:	Journal of Multivariate Analysis. - Elsevier, ISSN 0047-259X. - Vol. 135.2015, C, p. 117-130
Publisher:	Elsevier
Subject:	Wasserstein distance \| Deformation \| Semi-parametric model

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Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10011189565