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Compound Archimedean Copulas

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  • Moshe Kelner
  • Zinoviy Landsman
  • Udi E. Makov

Abstract

The copula function is an effective and elegant tool useful for modeling dependence between random variables. Among the many families of this function, one of the most prominent family of copula is the Archimedean family, which has its unique structure and features. Most of the copula functions in this family have only a single dependence parameter which limits the scope of the dependence structure. In this paper we modify the generator of Archimedean copulas in a way which maintains membership in the family while increasing the number of dependence parameters and, consequently, creating new copulas having more flexible dependence structure.

Suggested Citation

  • 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.
    • Handle: RePEc:ibn:ijspjl:v:10:y:2021:i:3:p:126
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    References listed on IDEAS

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    Cited by:

    1. Moshe Kelner & Zinoviy Landsman & Udi E. Makov, 2022. "Probabilistic Peak Demand Estimation Using Members of the Clayton Generalized Gamma Copula Family," Energies, MDPI, vol. 15(16), pages 1-15, August.
    2. Moshe Kelner & Zinoviy Landsman & Udi E. Makov, 2021. "Fitting Compound Archimedean Copulas to Data for Modeling Electricity Demand," International Journal of Statistics and Probability, Canadian Center of Science and Education, vol. 10(5), pages 1-20, September.

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    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

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