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On a generalization of Archimedean copula family

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  • Xie, Jiehua
  • Lin, Feng
  • Yang, Jingping

Abstract

This paper introduces a new family of multivariate copula functions defined by two generators, which is a multi-dimensional extension of the bivariate copula presented in Durante et al. (2007a). The copula family is also a generalization of Archimedean copula family to allow for tail dependence. The probabilistic structure of the copula function is given. Some properties of the copula function are discussed, such as multivariate tail dependence and uniqueness.

Suggested Citation

  • Xie, Jiehua & Lin, Feng & Yang, Jingping, 2017. "On a generalization of Archimedean copula family," Statistics & Probability Letters, Elsevier, vol. 125(C), pages 121-129.
    • Handle: RePEc:eee:stapro:v:125:y:2017:i:c:p:121-129
    DOI: 10.1016/j.spl.2017.02.001
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    References listed on IDEAS

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    7. Lajmi Lakhal & Louis-Paul Rivest & Belkacem Abdous, 2008. "Estimating Survival and Association in a Semicompeting Risks Model," Biometrics, The International Biometric Society, vol. 64(1), pages 180-188, March.
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    Cited by:

    1. Moshe Kelner & Zinoviy Landsman & Udi E. Makov, 2021. "Compound Archimedean Copulas," International Journal of Statistics and Probability, Canadian Center of Science and Education, vol. 10(3), pages 126-126, June.

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