Copulas are widely used for modeling the dependence structure of multivariate data. Many methods for estimating the copula density functions are investigated. In this paper, we study the asymptotic properties of the Bernstein estimator for unbounded copula density functions. We show that the estimator converges to infinity at the corner and we establish its relative convergence when the copula density is unbounded. Also, we provide the uniform strong consistency of the estimator on every compact in the interior region. We investigate the finite sample performance of the estimator via an extensive simulation study and we compare the Bernstein copula density estimator with other nonparametric methods. Finally, we consider an empirical applica...
Exposé aux Gemeinsame Jahrestagung der Deutschen Mathematiker-Vereinigung und der Gesellschaft für D...
42 pages, 6 figures, 9 tablesIn this paper we study nonparametric estimators of copulas and copula d...
In this study, a new nonparametric approach using Bernstein copula approximation is proposed to esti...
We study the asymptotic properties of the Bernstein estimator for unbounded density copula functions...
Copulas are widely used for modeling the dependence structure of multivariate data. Many methods for...
We study the asymptotic properties of the Bernstein estimator for unbounded density copula function...
Copulas are extensively used for dependence modeling. In many cases the data does not reveal how the...
Copulas are extensively used for dependence modeling. In many cases the data does not reveal how the...
AbstractCopulas are extensively used for dependence modeling. In many cases the data does not reveal...
Copulas are extensively used for dependence modeling. In many cases the data does not reveal how the...
AbstractThe copula density is estimated using Bernstein–Kantorovich polynomials. The estimator is th...
Nonparametric estimation of the copula function using Bernstein polynomials is studied. Convergence ...
The copula function is considered within the context of financial multivariate data sets that are n...
Abstract: In this paper we estimate density functions for positive multivariate data. We propose a s...
Exposé aux Gemeinsame Jahrestagung der Deutschen Mathematiker-Vereinigung und der Gesellschaft für D...
42 pages, 6 figures, 9 tablesIn this paper we study nonparametric estimators of copulas and copula d...
In this study, a new nonparametric approach using Bernstein copula approximation is proposed to esti...
We study the asymptotic properties of the Bernstein estimator for unbounded density copula functions...
Copulas are widely used for modeling the dependence structure of multivariate data. Many methods for...
We study the asymptotic properties of the Bernstein estimator for unbounded density copula function...
Copulas are extensively used for dependence modeling. In many cases the data does not reveal how the...
Copulas are extensively used for dependence modeling. In many cases the data does not reveal how the...
AbstractCopulas are extensively used for dependence modeling. In many cases the data does not reveal...
Copulas are extensively used for dependence modeling. In many cases the data does not reveal how the...
AbstractThe copula density is estimated using Bernstein–Kantorovich polynomials. The estimator is th...
Nonparametric estimation of the copula function using Bernstein polynomials is studied. Convergence ...
The copula function is considered within the context of financial multivariate data sets that are n...
Abstract: In this paper we estimate density functions for positive multivariate data. We propose a s...
Exposé aux Gemeinsame Jahrestagung der Deutschen Mathematiker-Vereinigung und der Gesellschaft für D...
42 pages, 6 figures, 9 tablesIn this paper we study nonparametric estimators of copulas and copula d...
In this study, a new nonparametric approach using Bernstein copula approximation is proposed to esti...