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dc.contributor.authorGijbels, Irène
dc.contributor.authorVeraverbeke, Noël
dc.contributor.authorOmelka, Marek
dc.date.accessioned2016-09-02T07:43:08Z
dc.date.available2016-09-02T07:43:08Z
dc.date.issued2015
dc.identifier.citationGijbels, I. et al. 2015. Estimation of a copula when a covariate affects only marginal distributions. Scandinavian journal of statistics, 42(4):1109-1126. [http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1467-9469]en_US
dc.identifier.issn0303-6898
dc.identifier.issn1467-9469 (Online)
dc.identifier.urihttp://hdl.handle.net/10394/18509
dc.identifier.urihttp://dx.doi.org/10.1111/sjos.12154
dc.identifier.urihttp://onlinelibrary.wiley.com/doi/10.1111/sjos.12154/full
dc.description.abstractThis paper is concerned with studying the dependence structure between two random variables Y1 and Y2 in the presence of a covariate X, which affects both marginal distributions but not the dependence structure. This is reflected in the property that the conditional copula of Y1 and Y2 given X, does not depend on the value of X. This latter independence often appears as a simplifying assumption in pair-copula constructions. We introduce a general estimator for the copula in this specific setting and establish its consistency. Moreover, we consider some special cases, such as parametric or nonparametric location-scale models for the effect of the covariate X on the marginals of Y1 and Y2 and show that in these cases, weak convergence of the estimator, at p n-rate, holds. The theoretical results are illustrated by simulations and a real data example.en_US
dc.language.isoenen_US
dc.publisherWileyen_US
dc.subjectAsymptotic representationen_US
dc.subjectconsistencyen_US
dc.subjectempirical copula processen_US
dc.subjectrandom designen_US
dc.subjectsimplifying assumptionen_US
dc.subjectsmoothingen_US
dc.subjectweak convergenceen_US
dc.titleEstimation of a copula when a covariate affects only marginal distributionsen_US
dc.typeArticleen_US
dc.contributor.researchID22051880 - Veraverbeke, Noël Daniël


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