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  • 标题:Method to Select Copula Functions
  • 作者:José Rafael Tovar-Cuevas ; José Rafael Tovar-Cuevas ; Jennyfer Portilla-Yela
  • 期刊名称:Revista Colombiana de Estadística
  • 印刷版ISSN:2389-8976
  • 出版年度:2019
  • 卷号:42
  • 期号:1
  • 页码:61-80
  • DOI:10.15446/rce.v42n1.71780
  • 语种:English
  • 出版社:Universidad Nacional de Colombia, sede Bogotá
  • 摘要:Copula functions have been extensively used in applied statistics, becoming a good alternative for modeling the dependence of multivariate data. Each copula function has a different dependence structure. An important issue in these applications is the choice of an appropriate copula function model for each one; thus common classical or Bayesian discrimination methods might not be appropriate for determining the best copula. Considering only the special case of bivariate data, we propose a procedure obtained from a recently introduced dependence measure for selecting an appropriate copula for the statistical data analyses.
  • 关键词:Copula functions;Selection method;discrimination of copulas;dependence measure;Ledwina measure;Funciones de cópula;Método de selección;discriminación de cópulas;medida de dependencia;Medida Ledwina
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