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Constructing Generalized FGM Copulas by Means of Certain Univariate Distributions

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Abstract

In this paper we focus on specific generalized Fairlie- Gumbel-Morgenstern (or Sarmanov) copulas which are generated by a single function (so-called generator or generator function) defined on the unit interval. In particular, we introduce a class of generators based on density-quantile functions of certain univariate distributions. Many of the generator functions from the literature are recovered as special cases. Moreover, two new generators are suggested, implying to new copulas. Finally, the opposite way around, it is shown how to calculate the univariate distribution which belongs to a given copula generator function.

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References

  • Amblard C, Girard S (2002) Symmetry and dependence properties within a semiparametric family of bivariate copulas. Nonparametr Stat 14(6):715–727

    Article  MATH  MathSciNet  Google Scholar 

  • Amblard C, Girard S (2004) Estimation procedures for a semiparametric family of bivariate copulas. J Comput Graphi Stat to appear

  • Bairamov I, Kotz S (2002) Dependence structure and symmetry of Huang-Kotz FGM distributions and their extensions. Metrika 56:55–72

    Article  MathSciNet  Google Scholar 

  • Blum P, Dias A, Embrechts P (2002). The ART of dependence modelling: the latest advances in correlation analysis. In: Lane M (eds). Alternative risk strategies. Risk Books, London, pp. 339–356

    Google Scholar 

  • Bronstein IN, Semendyayev KA (2000) Handbook of mathematics. Springer, Berlin Heidelberg New York

    Google Scholar 

  • Embrechts P, McNeil AJ, Straumann D (2002). Correlation and dependence in risk management: properties and pitfalls. In: Dempster MAH (eds). Risk management: value at risk and beyond. Cambridge University Press, Cambridge, pp. 176–223

    Google Scholar 

  • Fairlie DJG (1960) The performance of some correlation coefficients for a general bivariate distribution. Biometrika 47:307–323

    MathSciNet  Google Scholar 

  • Gumbel EJ (1960) Bivariate exponential distributions. J Am Stat Assoc 55:698–707

    Article  MATH  MathSciNet  Google Scholar 

  • Huang JS, Kotz S (1999) Modifications of the Fairlie-Gumbel-Morgenstern distributions. Metrika 49:135–145

    Article  MATH  MathSciNet  Google Scholar 

  • Ince EL (1956) Ordinary differential equations. Dover Publication, New York

    Google Scholar 

  • Joe H (2001) Multivariate models and dependence concepts. Chapman & Hall, London

    Google Scholar 

  • Joiner BL, Hall DL (1983) The ubiquitous role of f’/f in efficient estimation of location. J Am Stat Assoc 37:128–133

    MathSciNet  Google Scholar 

  • Junker M, May A (2002) Measurement of aggregate risk with copulas. CAESAR Preprint, Center of Advanced European Studies and Research, Bonn

    Google Scholar 

  • Lai CD, Xie M (2000) A new family of positive quadrant dependent bivariate distributions. Stat Probab Lett 46:359–364

    Article  MATH  MathSciNet  Google Scholar 

  • Lee MT (1996) Properties and applications of the Sarmanov family of bivariate distributions. Commun Stat Theory Methods 25(6):1207–1222

    Article  MATH  Google Scholar 

  • Mari DD, Kotz S (2001) Correlation and dependence. Imperial College Press, London

    MATH  Google Scholar 

  • Morgenstern D (1956) Einfache Beispiele zweidimensionaler Verteilungen. Mitteilungsblatt für Mathematische Statistik 8:234–235

    MathSciNet  Google Scholar 

  • Parzen E (1979) Nonparametric statistical modeling. J Am Stat Assoc 74:105–122

    Article  MATH  MathSciNet  Google Scholar 

  • Sarmanov OV (1966) Generalized normal correlation and two-dimensional Frechet classes. Doklady Akademii Nauk SSSR 168(1):596–599

    MathSciNet  Google Scholar 

  • Scheffner A (1998) Das fQ-System. PhD Thesis, University of Dortmund, Dortmund

    Google Scholar 

  • Shubina M, Lee MT (2004) On maximum attainable correlation and other measures of dependence for the Sarmanov family of bivariate distributions. Commun Stat Theory Methods 33(5):1031–1052

    Article  MATH  MathSciNet  Google Scholar 

  • Sklar A (1959) Fonctions de répartition á n dimensions et leurs marges. Publ. Inst. Statist. University of Paris 8:229–231

    MathSciNet  Google Scholar 

  • Vaughan DC (2002) The generalized hyperbolic secant distribution and its application. Commun Stat Theory Methods 31(2):219–238

    Article  MATH  MathSciNet  Google Scholar 

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Correspondence to Matthias Fischer.

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Fischer, M., Klein, I. Constructing Generalized FGM Copulas by Means of Certain Univariate Distributions. Metrika 65, 243–260 (2007). https://doi.org/10.1007/s00184-006-0075-6

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