Add to ORKGCopulas are extensively used for dependence modeling. In many cases the data does not reveal how the dependence can be modeled using a particular parametric copula. Nonparametric copulas do not share this problem since they are entirely data based. This paper proposes nonparametric estimation of the density copula for á-mixing data using Bernstein polynomials. We study the asymptotic properties of the Bernstein density copula, i.e., we provide the exact asymptotic bias and variance, we establish the uniform strong consistency and the asymptotic normality
A fundamental problem in statistics is the estimation of dependence between random variables. While ...
As relações de dependência entre variáveis aleatórias é um dos assuntos mais discutidos em probabili...
In this study, a new nonparametric approach using Bernstein copula approximation is proposed to esti...
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 th...
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 widely used for modeling the dependence structure of multivariate data. Many methods for...
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 ...
We study the asymptotic properties of the Bernstein estimator for unbounded density copula functions...
We study the asymptotic properties of the Bernstein estimator for unbounded density copula function...
Measuring the dependence between random variables is one of the most fundamental problems in statist...
42 pages, 6 figures, 9 tablesIn this paper we study nonparametric estimators of copulas and copula d...
A fundamental problem in statistics is the estimation of dependence between random variables. While ...
As relações de dependência entre variáveis aleatórias é um dos assuntos mais discutidos em probabili...
In this study, a new nonparametric approach using Bernstein copula approximation is proposed to esti...
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 th...
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 widely used for modeling the dependence structure of multivariate data. Many methods for...
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 ...
We study the asymptotic properties of the Bernstein estimator for unbounded density copula functions...
We study the asymptotic properties of the Bernstein estimator for unbounded density copula function...
Measuring the dependence between random variables is one of the most fundamental problems in statist...
42 pages, 6 figures, 9 tablesIn this paper we study nonparametric estimators of copulas and copula d...
A fundamental problem in statistics is the estimation of dependence between random variables. While ...
As relações de dependência entre variáveis aleatórias é um dos assuntos mais discutidos em probabili...
In this study, a new nonparametric approach using Bernstein copula approximation is proposed to esti...