Nonparametric identification of copula structures

Bo Li, Marc G. Genton

Research output: Contribution to journalArticlepeer-review


We propose a unified framework for testing a variety of assumptions commonly made about the structure of copulas, including symmetry, radial symmetry, joint symmetry, associativity and Archimedeanity, and max-stability. Our test is nonparametric and based on the asymptotic distribution of the empirical copula process.We perform simulation experiments to evaluate our test and conclude that our method is reliable and powerful for assessing common assumptions on the structure of copulas, particularly when the sample size is moderately large. We illustrate our testing approach on two datasets.

Original languageEnglish (US)
Pages (from-to)666-675
Number of pages10
JournalJournal of the American Statistical Association
Issue number502
StatePublished - 2013
Externally publishedYes


  • Archimedeanity
  • Associativity
  • Asymptotic normality
  • Max-stability
  • Symmetry
  • Test

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty


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