Non-parametric estimation of the limit dependence function

DOI10.1023/A:1009954903111zbMath0957.62044OpenAlexW2153788418MaRDI QIDQ5926463

A. Khoudraji, Belkacem Abdous, Kilani Ghoudi

Publication date: 1 March 2001

Published in: Extremes (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1023/a:1009954903111

zbMATH Keywords

copulasdependence functionGaussian processeskernel estimationmultivariate extremesregular variation

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Nonparametric estimation (62G05) Characterization and structure theory for multivariate probability distributions; copulas (62H05) Statistics of extreme values; tail inference (62G32)

Related Items (12)

An efficient nonparametric estimator for models with nonlinear dependence ⋮ Bivariate distributions with given extreme value attractor ⋮ Semi‐Parametric Models for the Multivariate Tail Dependence Function – the Asymptotically Dependent Case ⋮ Tail asymptotics for the sum of two heavy-tailed dependent risks ⋮ On Pickands coordinates in arbitrary dimensions ⋮ On the distribution of Pickands coordinates in bivariate EV and GP models ⋮ Non-parametric estimators of multivariate extreme dependence functions ⋮ Clustering of time series via non-parametric tail dependence estimation ⋮ Non-parametric Estimation of Tail Dependence ⋮ Estimating the tail-dependence coefficient: properties and pitfalls ⋮ Projection estimators of Pickands dependence functions ⋮ Nonparametric estimation of the spectral measure of an extreme value distribution.

This page was built for publication: Non-parametric estimation of the limit dependence function