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  • 标题:kdecopula: An R Package for the Kernel Estimation of Bivariate Copula Densities
  • 本地全文:下载
  • 作者:Thomas Nagler
  • 期刊名称:Journal of Statistical Software
  • 印刷版ISSN:1548-7660
  • 电子版ISSN:1548-7660
  • 出版年度:2018
  • 卷号:84
  • 期号:1
  • 页码:1-22
  • DOI:10.18637/jss.v084.i07
  • 语种:English
  • 出版社:University of California, Los Angeles
  • 摘要:We describe the R package kdecopula (current version 0.9.2), which provides fast implementations of various kernel estimators for the copula density. Due to a variety of available plotting options it is particularly useful for the exploratory analysis of dependence structures. It can be further used for accurate nonparametric estimation of copula densities and resampling. The implementation features spline interpolation of the estimates to allow for fast evaluation of density estimates and integrals thereof. We utilize this for a fast renormalization scheme that ensures that estimates are bona fide copula densities and additionally improves the estimators' accuracy. The performance of the methods is illustrated by simulations.
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