On the extremal dependence coefficient of multivariate distributions

A measure called ‘extremal dependence coefficient’ (EDC) is introduced for studying the asymptotic dependence structure of the minimum and the maximum of a random vector. Some general properties of the EDC are derived and its relation to the tail dependence coefficient is examined. The extremal depe...

Full description

Saved in:
Bibliographic Details
Published in:Statistics & probability letters 2006-08, Vol.76 (14), p.1470-1481
Main Author: Frahm, Gabriel
Format: Article
Language:English
Subjects:
Asymptotic dependence
Asymptotic dependence Copula Elliptical distribution Extremal dependence Tail dependence coefficient Tail index
Copula
Elliptical distribution
Exact sciences and technology
Extremal dependence
Mathematics
Multivariate analysis
Probability and statistics
Sciences and techniques of general use
Statistics
Tail dependence coefficient
Tail index
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:A measure called ‘extremal dependence coefficient’ (EDC) is introduced for studying the asymptotic dependence structure of the minimum and the maximum of a random vector. Some general properties of the EDC are derived and its relation to the tail dependence coefficient is examined. The extremal dependence structure of regularly varying elliptical random vectors is investigated and it is shown that the EDC is only determined by the tail index and by the pseudo-correlation coefficients of the elliptical distribution.
ISSN:0167-7152
1879-2103
DOI:10.1016/j.spl.2006.03.006