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A New Frailty Model Based Archimedean Bivariate Copula That Models Only Positive Dependency

Author

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  • Attia, Iman M.

    (faculty of graduate studies for statistical research Cairo university)

Abstract

In this paper, the author utilizes the frailty model to construct a new Archimedean copula. This copula depends on the transformed Median Based Unit Rayleigh (MBUR) distribution to an unbounded distribution defined on the interval from zero to infinity. The copula only models the positive dependency. In the paper, the joint PDF and CDF of the copula are derived for two bivariate distributions. The singularity of the copula is explained. The generator and inverse generator of the new copula are explored with various graphs to depict the decreasing and convex nature of the generator with different dependency parameter values. The Kendall tau measure of dependency is derived. For this copula, the lower and upper tail dependencies exist. The formula for each one is derived. This new copula is one of the parametric Archimedean copulas. Unfortunately, the Archimedean copulas are not widely used.

Suggested Citation

  • Attia, Iman M., 2025. "A New Frailty Model Based Archimedean Bivariate Copula That Models Only Positive Dependency," OSF Preprints y6pjc_v1, Center for Open Science.
    • Handle: RePEc:osf:osfxxx:y6pjc_v1
    DOI: 10.31219/osf.io/y6pjc_v1
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    References listed on IDEAS

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    1. repec:icf:icfjfe:v:05:y:2007:i:3:p:28-41 is not listed on IDEAS
    2. Joe, Harry, 1990. "Families of min-stable multivariate exponential and multivariate extreme value distributions," Statistics & Probability Letters, Elsevier, vol. 9(1), pages 75-81, January.
    3. Joe, H., 1993. "Parametric Families of Multivariate Distributions with Given Margins," Journal of Multivariate Analysis, Elsevier, vol. 46(2), pages 262-282, August.
    4. Patton, Andrew J., 2012. "A review of copula models for economic time series," Journal of Multivariate Analysis, Elsevier, vol. 110(C), pages 4-18.
    5. Attia, Iman M., 2025. "New Three Different Generators for Constructing New Three Different Bivariate Copulas," OSF Preprints zc4pu_v1, Center for Open Science.
    6. Hans Manner & Olga Reznikova, 2012. "A Survey on Time-Varying Copulas: Specification, Simulations, and Application," Econometric Reviews, Taylor & Francis Journals, vol. 31(6), pages 654-687, November.
    7. Yannick Malevergne & Didier Sornette, 2006. "Extreme Financial Risks : From Dependence to Risk Management," Post-Print hal-02298069, HAL.
    8. Joe, Harry & Hu, Taizhong, 1996. "Multivariate Distributions from Mixtures of Max-Infinitely Divisible Distributions," Journal of Multivariate Analysis, Elsevier, vol. 57(2), pages 240-265, May.
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