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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/24109

Title: Nonparametric testing for no covariate effects in conditional copulas
Authors: Gijbels, Irene
Omelka, Marek
Veraverbeke, Noel
Issue Date: 2017
Citation: STATISTICS, 51(3), p. 475-509
Abstract: In 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.
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.
URI: http://hdl.handle.net/1942/24109
DOI: 10.1080/02331888.2016.1258070
ISI #: 000399481400001
ISSN: 0233-1888
Category: A1
Type: Journal Contribution
Appears in Collections: Research publications

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