Bivariate Tail Dependence and the Generation of Multivariate Extreme Value Distributions

DOI10.1080/03610926.2012.744052zbMath1310.60063arXiv1203.1875OpenAlexW2191951433MaRDI QIDQ5177623

No author found.

Publication date: 13 March 2015

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1203.1875

zbMATH Keywords

tail dependencemultivariate extreme value theoryextremal coefficients

Mathematics Subject Classification ID

Extreme value theory; extremal stochastic processes (60G70) Distribution theory (60E99)

Cites Work

• Goodness-of-fit tests for copulas: A review and a power study
• Fragility index of block tailed vectors
• Bivariate extreme statistics. I
• An introduction to copulas.
• Construction of asymmetric multivariate copulas
• Orthant tail dependence of multivariate extreme value distributions
• Inequalities for the extremal coefficients of multivariate extreme value distributions
• Weak convergence of empirical copula processes
• Domains of attraction of multivariate extreme value distributions
• On the generation of a multivariate extreme value distribution with prescribed tail dependence parameter matrix
• Non-parametric Estimation of Tail Dependence
• Copula–Based Models for Financial Time Series

This page was built for publication: Bivariate Tail Dependence and the Generation of Multivariate Extreme Value Distributions