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http://hdl.handle.net/1942/24438
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DC Field | Value | Language |
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dc.contributor.author | Gijbels, Irène | - |
dc.contributor.author | OMELKA, Marek | - |
dc.contributor.author | Pešta, Michal | - |
dc.contributor.author | VERAVERBEKE, Noel | - |
dc.date.accessioned | 2017-09-08T09:46:56Z | - |
dc.date.available | 2017-09-08T09:46:56Z | - |
dc.date.issued | 2017 | - |
dc.identifier.citation | JOURNAL OF MULTIVARIATE ANALYSIS, 159, p. 111-133 | - |
dc.identifier.issn | 0047-259X | - |
dc.identifier.uri | http://hdl.handle.net/1942/24438 | - |
dc.description.abstract | We consider copula modeling of the dependence between two or more random variables in the presence of a multivariate covariate. The dependence parameter of the conditional copula possibly depends on the value of the covariate vector. In this paper we develop a new testing methodology for some important parametric specifications of this dependence parameter: constant, linear, quadratic, etc. in the covariate values, possibly after transformation with a link function. The margins are left unspecified. Our novel methodology opens plenty of new possibilities for testing how the conditional copula depends on the multivariate covariate and also for variable selection in copula model building. The suggested test is based on a Rao-type score statistic and regularity conditions are given under which the test has a limiting chi-square distribution under the null hypothesis. For small and moderate sample sizes, a permutation procedure is suggested to assess significance. In simulations it is shown that the test performs well (even under misspecification of the copula family and/or the dependence parameter structure) in comparison to available tests designed for testing for constancy of the dependence parameter. The test is illustrated on a real data set on concentrations of chemicals in water samples. (C) 2017 Elsevier Inc. All rights reserved. | - |
dc.description.sponsorship | The authors are grateful to the Editor-in-Chief, Associate Editor and the reviewers for their valuable comments, which led to an improved manuscript. This 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 and the third author gratefully acknowledge support from the grant GACR 15-04774Y. The fourth author is an extraordinary professor at the North-West University, Potchefstroom, South Africa. | - |
dc.language.iso | en | - |
dc.publisher | ELSEVIER INC | - |
dc.rights | © 2017 Elsevier Inc. All rights reserved. | - |
dc.subject.other | conditional copula; covariate effect; parametric dependence structure; rao score test; specification test | - |
dc.subject.other | Conditional copula; Covariate effect; Parametric dependence structure; Rao score test; Specification test | - |
dc.title | Score tests for covariate effects in conditional copulas | - |
dc.type | Journal Contribution | - |
dc.identifier.epage | 133 | - |
dc.identifier.spage | 111 | - |
dc.identifier.volume | 159 | - |
local.format.pages | 23 | - |
local.bibliographicCitation.jcat | A1 | - |
dc.description.notes | [Gijbels, Irene] Katholieke Univ Leuven, Dept Math, Celestijnenlaan 200B,Box 2400, B-3001 Heverlee, Belgium. [Gijbels, Irene] Katholieke Univ Leuven, Leuven Stat Res Ctr LStat, Celestijnenlaan 200B,Box 2400, B-3001 Heverlee, Belgium. [Omelka, Marek; Pesta, Michal] Charles Univ Prague, Dept Probabil & Stat, Fac Math & Phys, Sokolovska 83, Prague 18675 8, Czech Republic. [Veraverbeke, Noel] Hasselt Univ, Ctr Stat, Agoralaan Bldg D, B-3590 Diepenbeek, Belgium. [Veraverbeke, Noel] North West Univ, Unit BMI, Potchefstroom, South Africa. | - |
local.publisher.place | SAN DIEGO | - |
local.type.refereed | Refereed | - |
local.type.specified | Article | - |
dc.identifier.doi | 10.1016/j.jmva.2017.05.001 | - |
dc.identifier.isi | 000405976900007 | - |
item.accessRights | Restricted Access | - |
item.validation | ecoom 2018 | - |
item.fulltext | With Fulltext | - |
item.fullcitation | Gijbels, Irène; OMELKA, Marek; Pešta, Michal & VERAVERBEKE, Noel (2017) Score tests for covariate effects in conditional copulas. In: JOURNAL OF MULTIVARIATE ANALYSIS, 159, p. 111-133. | - |
item.contributor | Gijbels, Irène | - |
item.contributor | OMELKA, Marek | - |
item.contributor | Pešta, Michal | - |
item.contributor | VERAVERBEKE, Noel | - |
crisitem.journal.issn | 0047-259X | - |
Appears in Collections: | Research publications |
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File | Description | Size | Format | |
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gijbels 1.pdf Restricted Access | Published version | 573.42 kB | Adobe PDF | View/Open Request a copy |
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