Consider n i.i.d. random vectors on R, with unknown, common distribution function F . Under a sharpening of the extreme value condition on F , we derive a weighted approximation of the correspondingâ€¦ (More)

JOHN H.J. EINMAHL, AMÃ‰LIE FILS-VILLETARD and ARMELLE GUILLOU Dept. of Econometrics & OR and CentER, Tilburg University, P.O. Box 90153, 5000 LE Tilburg, The Netherlands. E-mail: j.h.j.einmahl@uvt.nlâ€¦ (More)

Consider a random sample from a bivariate distribution function F in the max-domain of attraction of an extreme-value distribution function G. This G is characterized by two extreme-value indices andâ€¦ (More)

Let (X1;Y1); :::; (Xn;Yn) be a random sample from a bivariate distribution function F in the domain of max-attraction of a distribution function G. This G is characterised by the two extreme valueâ€¦ (More)

Consider the nonparametric regression model Y = m(X) + Îµ, where the function m is smooth, but unknown. We construct tests for the independence of Îµ and X, based on n independent copies of (X, Y ).â€¦ (More)

â€¢ A submitted manuscript is the author's version of the article upon submission and before peer-review. There can be important differences between the submitted version and the official publishedâ€¦ (More)

Users may download and print one copy of any publication from the public portal for the purpose of private study or research You may not further distribute the material or use it for anyâ€¦ (More)

Consider n i.i.d. random elements on C[0, 1]. We show that, under an appropriate strengthening of the domain of attraction condition , natural estimators of the extreme-value index, which is now aâ€¦ (More)

Journal of computational and graphical statisticsâ€¦

2013

Multiple-quantile plots provide a powerful graphical method for comparing the distributions of two or more populations. This article develops a method of visualizing triple-quantile plots and theirâ€¦ (More)