Statistics and Computing

, Volume 26, Issue 5, pp 965–979 | Cite as

A flexible and tractable class of one-factor copulas

  • Gildas Mazo
  • Stéphane Girard
  • Florence Forbes


Copulas are a useful tool to model multivariate distributions. While there exist various families of bivariate copulas, the construction of flexible and yet tractable copulas suitable for high-dimensional applications is much more challenging. This is even more true if one is concerned with the analysis of extreme values. In this paper, we construct a class of one-factor copulas and a family of extreme-value copulas well suited for high-dimensional applications and exhibiting a good balance between tractability and flexibility. The inference for these copulas is performed by using a least-squares estimator based on dependence coefficients. The modeling capabilities of the copulas are illustrated on simulated and real datasets.


Extreme-value copula Factor model Multivariate copula High-dimension 



The authors thank “Banque HYDRO du Ministère de l’Écologie, du Développement durable et de l’Énergie” for providing the data, and Benjamin Renard for fruitful discussions about statistical issues in hydrological science. The authors also thank the two anonymous referees and the associate editor for their helpful suggestions and comments.


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Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  • Gildas Mazo
    • 1
  • Stéphane Girard
    • 1
  • Florence Forbes
    • 1
  1. 1.MISTIS, Inria - Laboratoire Jean KuntzmannGrenobleFrance

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