On the asymptotic covariance of the multivariate empirical copula process

Genest Christian, Mesfioui Mhamed and Nešlehová Johanna G.
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Genest Christian: Department of Mathematics and Statistics, McGill University, 805, rue Sherbrooke ouest, Montréal (Québec) CanadaH3A 0B9
Mesfioui Mhamed: Département de mathématiques et d’informatique, Université du Québec à Trois-Rivières, C.P. 500, Trois-Rivières (Québec) CanadaG9A 5H7
Nešlehová Johanna G.: Department of Mathematics and Statistics, McGill University, 805, rue Sherbrooke ouest, Montréal (Québec) CanadaH3A 0B9

Dependence Modeling, 2019, vol. 7, issue 1, 279-291

Abstract: Genest 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.

Keywords: Empirical copula process; left-tail decreasing variable-by-variable; limiting covariance; rank-based inference (search for similar items in EconPapers)
Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:vrs:demode:v:7:y:2019:i:1:p:279-291:n:15

DOI: 10.1515/demo-2019-0015

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