Advertisement
Published in:
2010 | OriginalPaper | Chapter
Copula-Based Measures of Multivariate Association
Authors : Friedrich Schmid, Rafael Schmidt, Thomas Blumentritt, Sandra Gaißer, Martin Ruppert
Published in: Copula Theory and Its Applications
Publisher: Springer Berlin Heidelberg
Activate our intelligent search to find suitable subject content or patents.
Select sections of text to find matching patents with Artificial Intelligence. powered by
Select sections of text to find additional relevant content using AI-assisted search. powered by
This chapter constitutes a survey on copula-based measures of multivariate association - i.e. association in a
d
-dimensional random vector
$$X = (X_1 , \ldots ,X_d )$$
where
$$d \ge 2$$
. Some of the measures discussed are multivariate extensions of wellknown bivariate measures such as Spearman’s rho, Kendall’s tau, Blomqvist’s beta or Gini’s gamma. Others rely on information theory or are based on
L p
-distances of copulas. Various measures of multivariate tail dependence are derived by extending the coefficient of bivariate tail dependence. Nonparametric estimation of these measures based on the empirical copula is further addressed.