The copula-based modeling of multivariate distributions with continuous margins is presented as a succession of rank-based tests: a multivariate test of randomness followed by a test of mutual independence and a series of goodness-of-fit tests. All the tests under consideration are based on the empirical copula, which is a nonparametric rank-based estimator of the true unknown copula. The principles of the tests are recalled and their implementation in the copula R package is briefly described. Their use in the construction of a copula model from data is thoroughly illustrated on real insurance and financial data
Diploma thesis abstract Thesis title: Statistical inference in multivariate distributions based on c...
Copulas provide a potential useful modeling tool to represent the dependence structure among variabl...
Concepts of association or dependence play a central role when considering multiple random sources i...
The copula-based modeling of multivariate distributions with continuous margins is presented as a su...
The copula-based modeling of multivariate distributions with continuous margins is presented as a su...
This book introduces the main theoretical findings related to copulas and shows how statistical mode...
Copulas have become a popular tool in multivariate modeling successfully applied in many fields. A g...
In this research we introduce a new class of multivariate probability models to the marketing litera...
Copulas have become a popular tool in multivariate modeling successfully applied in many fields. A g...
Copulas have become a popular tool in multivariate modeling successfully applied in many fields. A g...
This article describes the R package gcmr for fitting Gaussian copula marginal regression models. Th...
Flexible multivariate distributions are needed in many areas. The popular multivariate Gaussian dist...
Copulas provide a potential useful modeling tool to represent the dependence structure among variab...
Copulas provide a potential useful modeling tool to represent the dependence structure among variab...
AbstractThis survey reviews the large and growing literature on copula-based models for economic and...
Diploma thesis abstract Thesis title: Statistical inference in multivariate distributions based on c...
Copulas provide a potential useful modeling tool to represent the dependence structure among variabl...
Concepts of association or dependence play a central role when considering multiple random sources i...
The copula-based modeling of multivariate distributions with continuous margins is presented as a su...
The copula-based modeling of multivariate distributions with continuous margins is presented as a su...
This book introduces the main theoretical findings related to copulas and shows how statistical mode...
Copulas have become a popular tool in multivariate modeling successfully applied in many fields. A g...
In this research we introduce a new class of multivariate probability models to the marketing litera...
Copulas have become a popular tool in multivariate modeling successfully applied in many fields. A g...
Copulas have become a popular tool in multivariate modeling successfully applied in many fields. A g...
This article describes the R package gcmr for fitting Gaussian copula marginal regression models. Th...
Flexible multivariate distributions are needed in many areas. The popular multivariate Gaussian dist...
Copulas provide a potential useful modeling tool to represent the dependence structure among variab...
Copulas provide a potential useful modeling tool to represent the dependence structure among variab...
AbstractThis survey reviews the large and growing literature on copula-based models for economic and...
Diploma thesis abstract Thesis title: Statistical inference in multivariate distributions based on c...
Copulas provide a potential useful modeling tool to represent the dependence structure among variabl...
Concepts of association or dependence play a central role when considering multiple random sources i...