Add to ORKGAn investigation is presented of how a comprehensive choice of five most important measures of concordance (namely Spearman's rho, Kendall's tau, Gini's gamma, Blomqvist's beta, and their weaker counterpart Spearman's footrule) relate to non-exchangeability, i.e., asymmetry on copulas. Besides these results, the method proposed also seems to be new and may serve as a raw model for exploration of the relationship between a specific property of a copula and some of its measures of dependence structure, or perhaps the relationship between various measures of dependence structure themselves.Comment: 27 pages, 11 figure
Building upon earlier work in which axioms were formulated for multivariate measures of concordance,...
A continuous random vector (X,Y) uniquely determines a copula C: [0,1]2 → [0,1] such that when the d...
When studying the dependence structure of multivariate random vectors, the copula is crucial. A copu...
A new measure of asymmetry in dependence is proposed that is based on taking the difference between ...
Copulas are real functions representing the dependence structure of the distribution of a random vec...
A new measure of asymmetry in dependence is proposed that is based on taking the difference between ...
A new measure of asymmetry in dependence is proposed which is based on taking the difference betwee...
This note contributes to the development of the theory of stochastic dependence by employing the gen...
AbstractThe dependence structure among each risk factors has been an important topic for researches ...
This note contributes to the development of the theory of stochastic dependence by employing the gen...
Building upon earlier work in which axioms were formulated for multivariate measures of concordance,...
summary:The present paper introduces a group of transformations on the collection of all bivariate c...
Multivariate total positivity of order 2 (MTP2) is a dependence property with a number of applicatio...
We call a measure of concordance [kappa] of an ordered pair (X,Y) of two continuous random variables...
Quantifying tail dependence is an important issue in insurance and risk management. The prevalent ta...
Building upon earlier work in which axioms were formulated for multivariate measures of concordance,...
A continuous random vector (X,Y) uniquely determines a copula C: [0,1]2 → [0,1] such that when the d...
When studying the dependence structure of multivariate random vectors, the copula is crucial. A copu...
A new measure of asymmetry in dependence is proposed that is based on taking the difference between ...
Copulas are real functions representing the dependence structure of the distribution of a random vec...
A new measure of asymmetry in dependence is proposed that is based on taking the difference between ...
A new measure of asymmetry in dependence is proposed which is based on taking the difference betwee...
This note contributes to the development of the theory of stochastic dependence by employing the gen...
AbstractThe dependence structure among each risk factors has been an important topic for researches ...
This note contributes to the development of the theory of stochastic dependence by employing the gen...
Building upon earlier work in which axioms were formulated for multivariate measures of concordance,...
summary:The present paper introduces a group of transformations on the collection of all bivariate c...
Multivariate total positivity of order 2 (MTP2) is a dependence property with a number of applicatio...
We call a measure of concordance [kappa] of an ordered pair (X,Y) of two continuous random variables...
Quantifying tail dependence is an important issue in insurance and risk management. The prevalent ta...
Building upon earlier work in which axioms were formulated for multivariate measures of concordance,...
A continuous random vector (X,Y) uniquely determines a copula C: [0,1]2 → [0,1] such that when the d...
When studying the dependence structure of multivariate random vectors, the copula is crucial. A copu...