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DC Field | Value | Language |
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dc.contributor.author | VERAVERBEKE, Noel | - |
dc.contributor.author | OMELKA, Marek | - |
dc.contributor.author | Gijbels, Irene | - |
dc.date.accessioned | 2012-01-18T07:57:36Z | - |
dc.date.available | 2012-01-18T07:57:36Z | - |
dc.date.issued | 2011 | - |
dc.identifier.citation | SCANDINAVIAN JOURNAL OF STATISTICS, 38 (4), p. 766-780 | - |
dc.identifier.issn | 0303-6898 | - |
dc.identifier.uri | http://hdl.handle.net/1942/13000 | - |
dc.description.abstract | This paper is concerned with studying the dependence structure between two random variables Y(1) and Y(2) conditionally upon a covariate X. The dependence structure is modelled via a copula function, which depends on the given value of the covariate in a general way. Gijbels et. al. (Comput. Statist. Data Anal., 55, 2011, 1919) suggested two non-parametric estimators of the conditional copula and investigated their numerical performances. In this paper we establish the asymptotic properties of the proposed estimators as well as conditional association measures derived from them. Practical recommendations for their use are then discussed. | - |
dc.description.sponsorship | The authors are grateful to the Editor, the Associate Editor and two referees for their very valuable comments which led to a considerable improvement of the manuscript. This work was supported by the IAP Research Network P6/03 of the Belgian State (Belgian Science Policy). This work was started while Marek Omelka was a postdoctoral researcher at the Katholieke Universiteit Leuven and the Universiteit Hasselt within the IAP Research Network. The support of Project MSM 0021620839 of Ministry of Education, Youth and Sport of the Czech Republic is also highly appreciated. The first author acknowledges support from research grant MTM 2008-03129 of the Spanish Ministerio de Ciencia e Innovacion. The third author gratefully acknowledges support from the GOA/07/04-project of the Research Fund KULeuven. | - |
dc.language.iso | en | - |
dc.publisher | WILEY-BLACKWELL | - |
dc.subject.other | asymptotic representation; conditional Kendall's tau; empirical copula process; fixed design; random design; smoothing; weak convergence | - |
dc.subject.other | Statistics & Probability; asymptotic representation; conditional Kendrall's tau; empirical copula process; fixed design; random design; smoothing; weak convergence | - |
dc.title | Estimation of a Conditional Copula and Association Measures | - |
dc.type | Journal Contribution | - |
dc.identifier.epage | 780 | - |
dc.identifier.issue | 4 | - |
dc.identifier.spage | 766 | - |
dc.identifier.volume | 38 | - |
local.format.pages | 15 | - |
local.bibliographicCitation.jcat | A1 | - |
dc.description.notes | [Gijbels, Irene] Katholieke Univ Leuven, Dept Math, B-3001 Heverlee, Belgium. [Gijbels, Irene] Katholieke Univ Leuven, Leuven Stat Res Ctr LStat, B-3001 Heverlee, Belgium. [Veraverbeke, Noel] Hasselt Univ, Ctr Stat, Diepenbeek, Belgium. [Omelka, Marek] Charles Univ Prague, Dept Probabil & Stat, Fac Math & Phys, Prague, Czech Republic. irene.gijbels@wis.kuleuven.be | - |
local.publisher.place | MALDEN | - |
local.type.refereed | Refereed | - |
local.type.specified | Article | - |
dc.bibliographicCitation.oldjcat | A1 | - |
dc.identifier.doi | 10.1111/j.1467-9469.2011.00744.x | - |
dc.identifier.isi | 000297841000009 | - |
item.fullcitation | VERAVERBEKE, Noel; OMELKA, Marek & Gijbels, Irene (2011) Estimation of a Conditional Copula and Association Measures. In: SCANDINAVIAN JOURNAL OF STATISTICS, 38 (4), p. 766-780. | - |
item.validation | ecoom 2013 | - |
item.fulltext | With Fulltext | - |
item.accessRights | Restricted Access | - |
item.contributor | VERAVERBEKE, Noel | - |
item.contributor | OMELKA, Marek | - |
item.contributor | Gijbels, Irene | - |
crisitem.journal.issn | 0303-6898 | - |
crisitem.journal.eissn | 1467-9469 | - |
Appears in Collections: | Research publications |
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Estimation of a conditional copula and association measures.pdf Restricted Access | Published version | 247.04 kB | Adobe PDF | View/Open Request a copy |
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