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On the asymptotic covariance of the multivariate empirical copula process

On the asymptotic covariance of the multivariate empirical copula process AbstractGenest and Segers (2010) gave conditions under which the empirical copula process associated with a random sample from a bivariate continuous distribution has a smaller asymptotic covariance than the standard empirical process based on a random sample from the underlying copula. An extension of this result to the multivariate case is provided. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Dependence Modeling de Gruyter

On the asymptotic covariance of the multivariate empirical copula process

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Publisher
de Gruyter
Copyright
© 2019 Christian Genest et al., published by De Gruyter
ISSN
2300-2298
eISSN
2300-2298
DOI
10.1515/demo-2019-0015
Publisher site
See Article on Publisher Site

Abstract

AbstractGenest and Segers (2010) gave conditions under which the empirical copula process associated with a random sample from a bivariate continuous distribution has a smaller asymptotic covariance than the standard empirical process based on a random sample from the underlying copula. An extension of this result to the multivariate case is provided.

Journal

Dependence Modelingde Gruyter

Published: Jan 1, 2019

References