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  • 标题:Asymptotic properties of the Bernstein density copula for dependent data
  • 本地全文:下载
  • 作者:Taoufik BOUEZMARNI ; Jeroen V.K. ROMBOUTS ; Abderrahim TAAMOUTI
  • 期刊名称:CORE Discussion Papers / Center for Operations Research and Econometrics (UCL), Louvain
  • 出版年度:2008
  • 卷号:1
  • 出版社:Center for Operations Research and Econometrics (UCL), Louvain
  • 摘要: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 α-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.
  • 关键词:nonparametric estimation, copula, Bernstein polynomial, α-mixing, asymptotic properties, boundary bias
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