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• W2114878423 abstract "Copulas 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 a-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." @default.
• W2114878423 created "2016-06-24" @default.
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• W2114878423 date "2008-01-01" @default.
• W2114878423 modified "2023-09-26" @default.
• W2114878423 title "Asymptotic properties of the Bernstein density copula for dependent data" @default.
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• W2114878423 hasPublicationYear "2008" @default.
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