Copula函数的选择方法

Q3 Mathematics
J. R. Tovar-Cuevas, Jennyfer Portilla-Yela, J. Achcar
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引用次数: 2

摘要

Copula函数在应用统计学中得到了广泛的应用,成为多变量数据相关性建模的一种很好的替代方法。每个联结函数都有不同的依赖结构。在这些应用中一个重要的问题是为每一个选择合适的联结函数模型;因此,常用的经典或贝叶斯判别方法可能不适用于确定最佳交配体。考虑到双变量数据的特殊情况,我们提出了一个从最近引入的依赖度量中获得的程序,用于选择统计数据分析的适当联结。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Method to Select Copula Functions
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.
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来源期刊
Revista Colombiana De Estadistica
Revista Colombiana De Estadistica STATISTICS & PROBABILITY-
CiteScore
1.20
自引率
0.00%
发文量
0
审稿时长
>12 weeks
期刊介绍: The Colombian Journal of Statistics publishes original articles of theoretical, methodological and educational kind in any branch of Statistics. Purely theoretical papers should include illustration of the techniques presented with real data or at least simulation experiments in order to verify the usefulness of the contents presented. Informative articles of high quality methodologies or statistical techniques applied in different fields of knowledge are also considered. Only articles in English language are considered for publication. The Editorial Committee assumes that the works submitted for evaluation have not been previously published and are not being given simultaneously for publication elsewhere, and will not be without prior consent of the Committee, unless, as a result of the assessment, decides not publish in the journal. It is further assumed that when the authors deliver a document for publication in the Colombian Journal of Statistics, they know the above conditions and agree with them.
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