When studying the dependence structure of multivariate random vectors, the copula is crucial. A copula is called exchangeable, if it is invariant under any permutation of its arguments. In this thesis, a limit for the absolute distance between a copula and a version of itself with permuted arguments is derived. Furthermore, nonparametric test procedures for testing the hypothesis of exchangeability of a given sample of multivariate data are discussed as well as their asymptotic behavior
Tests of multivariate independence may rely on asymptotically independent Cramér-von Mises statistic...
The family of Clayton copulas is one of the most widely used Archimedean copulas for dependency meas...
The modelling of dependence relations between random variables is one of the most widely studied sub...
Whenever multivariate data has to be modelled, a copula approach naturally comes into play. As a dis...
Multivariate total positivity of order 2 (MTP2) is a dependence property with a number of applicatio...
Multivariate total positivity of order 2 (MTP2) is a dependence property with a number of applicati...
Copulas are a powerful tool to model dependence between the components of a random vector. One well-...
Restricted until 15 Feb. 2009.A construction of multivariate distribution functions that allows for ...
AbstractIn the class of bivariate extreme value copulas, an upper bound is calculated for the measur...
This thesis describes tests for specific dependence structures between two random variables, in part...
This paper suggests Lévy copulas in order to characterize the dependence among components of multidi...
This paper proposes competing procedures to the tests of symmetry for bivariate copulas of Genest, N...
AbstractThis paper suggests Lévy copulas in order to characterize the dependence among components of...
Principles of Copula Theory explores the state of the art on copulas and provides you with the found...
Copulas have now become ubiquitous statistical tools for describing, analysing and modelling depende...
Tests of multivariate independence may rely on asymptotically independent Cramér-von Mises statistic...
The family of Clayton copulas is one of the most widely used Archimedean copulas for dependency meas...
The modelling of dependence relations between random variables is one of the most widely studied sub...
Whenever multivariate data has to be modelled, a copula approach naturally comes into play. As a dis...
Multivariate total positivity of order 2 (MTP2) is a dependence property with a number of applicatio...
Multivariate total positivity of order 2 (MTP2) is a dependence property with a number of applicati...
Copulas are a powerful tool to model dependence between the components of a random vector. One well-...
Restricted until 15 Feb. 2009.A construction of multivariate distribution functions that allows for ...
AbstractIn the class of bivariate extreme value copulas, an upper bound is calculated for the measur...
This thesis describes tests for specific dependence structures between two random variables, in part...
This paper suggests Lévy copulas in order to characterize the dependence among components of multidi...
This paper proposes competing procedures to the tests of symmetry for bivariate copulas of Genest, N...
AbstractThis paper suggests Lévy copulas in order to characterize the dependence among components of...
Principles of Copula Theory explores the state of the art on copulas and provides you with the found...
Copulas have now become ubiquitous statistical tools for describing, analysing and modelling depende...
Tests of multivariate independence may rely on asymptotically independent Cramér-von Mises statistic...
The family of Clayton copulas is one of the most widely used Archimedean copulas for dependency meas...
The modelling of dependence relations between random variables is one of the most widely studied sub...