Weighted approximations of tail copula processes with application to testing the bivariate extreme value condition

dc.creatorEinmahl, John H. J.
dc.creatorde Haan, Laurens
dc.creatorLi, Deyuan
dc.date2006-11-13
dc.date.accessioned2026-07-07T08:08:23Z
dc.date.available2026-07-07T08:08:23Z
dc.descriptionConsider $n$ i.i.d. random vectors on $\mathbb{R}^2$, with unknown, common distribution function $F$. Under a sharpening of the extreme value condition on $F$, we derive a weighted approximation of the corresponding tail copula process. Then we construct a test to check whether the extreme value condition holds by comparing two estimators of the limiting extreme value distribution, one obtained from the tail copula process and the other obtained by first estimating the spectral measure which is then used as a building block for the limiting extreme value distribution. We derive the limiting distribution of the test statistic from the aforementioned weighted approximation. This limiting distribution contains unknown functional parameters. Therefore, we show that a version with estimated parameters converges weakly to the true limiting distribution. Based on this result, the finite sample properties of our testing procedure are investigated through a simulation study. A real data application is also presented.
dc.descriptionPublished at http://dx.doi.org/10.1214/009053606000000434 in the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org)
dc.identifierhttps://arxiv.org/abs/math/0611370
dc.identifierhttp://arxiv.org/abs/math/0611370
dc.identifierAnnals of Statistics 2006, Vol. 34, No. 4, 1987-2014
dc.identifierdoi:10.1214/009053606000000434
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/131247
dc.subjectStatistics Theory
dc.subject62G32, 62G30, 62G10 (Primary) 60G70, 60F17 (Secondary)
dc.titleWeighted approximations of tail copula processes with application to testing the bivariate extreme value condition
dc.typetext

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