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dc.contributor.authorGijbels, Irène
dc.contributor.authorVeraverbeke, Noël
dc.contributor.authorOmelka, Marek
dc.date.accessioned2017-06-08T13:49:05Z
dc.date.available2017-06-08T13:49:05Z
dc.date.issued2017
dc.identifier.citationGijbels, I. et al. 2017. Nonparametric testing for no covariate effects in conditional copulas. Statistics, 51(3):475-509. [http://dx.doi.org/10.1080/02331888.2016.1258070]en_US
dc.identifier.issn0233-1888
dc.identifier.issn1029-4910 (Online)
dc.identifier.urihttp://hdl.handle.net/10394/24898
dc.identifier.urihttp://dx.doi.org/10.1080/02331888.2016.1258070
dc.identifier.urihttp://www.tandfonline.com/doi/full/10.1080/02331888.2016.1258070
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 testsen_US
dc.language.isoenen_US
dc.publisherTaylor & Francisen_US
dc.subjectConditional copulaen_US
dc.subjectCovariate effecten_US
dc.subjectKendall's tauen_US
dc.subjectNonparametric testingen_US
dc.subjectPairwise simplifying assumptionen_US
dc.subjectPartial copulaen_US
dc.titleNonparametric testing for no covariate effects in conditional copulasen_US
dc.typeArticleen_US
dc.contributor.researchID22051880 - Veraverbeke, Noël Daniel


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