Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/24109
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dc.contributor.authorGijbels, Irene-
dc.contributor.authorOMELKA, Marek-
dc.contributor.authorVERAVERBEKE, Noel-
dc.date.accessioned2017-08-07T09:57:01Z-
dc.date.available2017-08-07T09:57:01Z-
dc.date.issued2017-
dc.identifier.citationSTATISTICS, 51(3), p. 475-509-
dc.identifier.issn0233-1888-
dc.identifier.urihttp://hdl.handle.net/1942/24109-
dc.description.abstractIn dependence modelling using conditional copulas, one often imposes the working assumption that the covariate influences the conditional copula solely through the marginal distributions. This so-called (pairwise) simplifying assumption is almost standardly made in vine copula constructions. However, in recent literature evidence was provided that such an assumption might not be justified. Among the first issues is thus to test for its appropriateness. In this paper nonparametric tests for the null hypothesis of the simplifying assumption are proposed, and their asymptotic behaviours, under the null hypothesis and under some local alternatives, are established. The tests are fully nonparametric in nature: not requiring choices of copula families nor knowledge of the marginals. In a simulation study, the finite-sample size and power performances of the tests are investigated, and compared with these of the few available tests. A real data application illustrates the use of the tests.-
dc.description.sponsorshipThis research was supported by the IAP Research Network P7/06 of the Belgian State (Belgian Science Policy). The first author gratefully acknowledges support from the GOA/12/014 project of the Research Fund KU Leuven. The second author gratefully acknowledges support from the grant GACR 15-04774Y. The third author is an extraordinary professor at the North-West University, Potchefstroom, South Africa.-
dc.language.isoen-
dc.publisherTAYLOR & FRANCIS LTD-
dc.rights© 2016 Informa UK Limited, trading as Taylor & Francis Group-
dc.subject.otherConditional copula; covariate effect; Kendall's tau; nonparametric testing; pairwise simplifying assumption; partial copula-
dc.subject.otherconditional copula; covariate effect; Kendall's tau; nonparametric testing; pairwise simplifying assumption; partial copula-
dc.titleNonparametric testing for no covariate effects in conditional copulas-
dc.typeJournal Contribution-
dc.identifier.epage509-
dc.identifier.issue3-
dc.identifier.spage475-
dc.identifier.volume51-
local.format.pages35-
local.bibliographicCitation.jcatA1-
dc.description.notes[Gijbels, Irene] Katholieke Univ Leuven, Dept Math, Heverlee, Belgium. [Gijbels, Irene] Katholieke Univ Leuven, Leuven Stat Res Ctr LStat, Heverlee, Belgium. [Omelka, Marek] Charles Univ Prague, Fac Math & Phys, Dept Probabil & Stat, Sokolovska 83, Prague 18675 8, Czech Republic. [Veraverbeke, Noel] Hasselt Univ, Ctr Stat, Diepenbeek, Belgium. [Veraverbeke, Noel] North West Univ, Unit BMI, Potchefstroom, South Africa.-
local.publisher.placeABINGDON-
local.type.refereedRefereed-
local.type.specifiedArticle-
local.classdsPublValOverrule/author_version_not_expected-
dc.identifier.doi10.1080/02331888.2016.1258070-
dc.identifier.isi000399481400001-
item.contributorGijbels, Irene-
item.contributorOMELKA, Marek-
item.contributorVERAVERBEKE, Noel-
item.validationecoom 2018-
item.fullcitationGijbels, Irene; OMELKA, Marek & VERAVERBEKE, Noel (2017) Nonparametric testing for no covariate effects in conditional copulas. In: STATISTICS, 51(3), p. 475-509.-
item.accessRightsRestricted Access-
item.fulltextWith Fulltext-
crisitem.journal.issn0233-1888-
crisitem.journal.eissn1029-4910-
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