Weak convergence of the empirical copula process with respect to weighted metrics

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dc.contributor.authorBerghaus, Betina
dc.contributor.authorBücher, Axel
dc.contributor.authorVolgushev, Stanislav
dc.date.accessioned2014-11-25T11:28:37Z
dc.date.available2014-11-25T11:28:37Z
dc.date.issued2014
dc.description.abstractThe empirical copula process plays a central role in the asymptotic analysis of many statistical procedures which are based on copulas or ranks. Among other applications, results regarding its weak convergence can be used to develop asymptotic theory for estimators of dependence measures or copula densities, they allow to derive tests for stochastic independence or specific copula structures, or they may serve as a fundamental tool for the analysis of multivariate rank statistics. In the present paper, we establish weak convergence of the empirical copula process (for observations that are allowed to be serially dependent) with respect to weighted supremum distances. The usefulness of our results is illustrated by applications to general bivariate rank statistics and to estimation procedures for the Pickands dependence function arising in multivariate extreme-value theory.en
dc.identifier.urihttp://hdl.handle.net/2003/33701
dc.identifier.urihttp://dx.doi.org/10.17877/DE290R-6729
dc.language.isoende
dc.relation.ispartofseriesDiscussion Paper / SFB 823;38/2014
dc.subjectempirical copula processen
dc.subjectPickands dependence functionen
dc.subjectbivariate rank statisticsen
dc.subjectstrongly mixingen
dc.subjectweighted weak convergenceen
dc.subject.ddc310
dc.subject.ddc330
dc.subject.ddc620
dc.titleWeak convergence of the empirical copula process with respect to weighted metricsen
dc.typeTextde
dc.type.publicationtypeworkingPaperde
dcterms.accessRightsopen access

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