Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/11827
Title: Conditional copulas, association measures and their applications
Authors: Gijbels, Irene
VERAVERBEKE, Noel 
OMELKA, Marek 
Issue Date: 2011
Publisher: ELSEVIER SCIENCE BV
Source: COMPUTATIONAL STATISTICS & DATA ANALYSIS, 55 (5). p. 1919-1932
Abstract: One way to model a dependence structure is through the copula function which is a mean to capture the dependence structure in the joint distribution of variables. Association measures such as Kendall's tau or Spearman's rho can be expressed as functionals of the copula. The dependence structure between two variables can be highly influenced by a covariate, and it is of real interest to know how this dependence structure changes with the value taken by the covariate. This motivates the need for introducing conditional copulas, and the associated conditional Kendall's tau and Spearman's rho association measures. After the introduction and motivation of these concepts, two nonparametric estimators for a conditional copula are proposed and discussed. Then nonparametric estimates for the conditional association measures are derived. A key issue is that these measures are now looked at as functions in the covariate. The performances of all estimators are investigated via a simulation study which also includes a data-driven algorithm for choosing the smoothing parameters. The usefulness of the methods is illustrated on two real data examples. (C) 2010 Elsevier B.V. All rights reserved.
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, B-3590 Diepenbeek, Belgium. [Omelka, Marel] Charles Univ Prague, Jaroslav Hajek Ctr Theoret & Appl Stat, Prague 18675 8, Czech Republic. Irene.Gijbels@wis.kuleuven.be; noel.veraverbeke@uhasselt.be; omelka@karlin.mff.cuni.cz
Keywords: Asymptotic bias; Asymptotic variance; Conditional copula; Conditional Kendall's tau; Conditional Spearman's rho; Empirical estimation; Global and local bandwidths; Local dependencies; Smoothing;Asymptotic bias; Asymptotic variance; Conditional copula; Conditional Kendall's tau; Conditional Spearman's rho; Empirical estimation; Global and local bandwidths; Local dependencies; Smoothing
Document URI: http://hdl.handle.net/1942/11827
ISSN: 0167-9473
e-ISSN: 1872-7352
DOI: 10.1016/j.csda.2010.11.010
ISI #: 000287952900003
Category: A1
Type: Journal Contribution
Validations: ecoom 2012
Appears in Collections:Research publications

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