Methods of Constructing Copulas

  • Roger B. Nelsen
Part of the Lecture Notes in Statistics book series (LNS, volume 139)


If we have a collection of copulas then, as a consequence of Sklar’s theorem, we automatically have a collection of bivariate or multivariate distributions with whatever marginal distributions we desire. Clearly this can be useful in modeling and simulation. Furthermore, by virtue of Theorem 2.4.3, the nonparametric nature of the dependence between two random variables, is expressed by the copula. Thus the study of concepts and measures of nonparametric dependence is a study of properties of copulas—a topic we will pursue in Chapter 5. For this study, it is advantageous to have a variety of copulas at our disposal.


Bivariate Distribution Continuous Random Variable Archimedean Copula Joint Distribution Function Bivariate Exponential Distribution 


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Copyright information

© Springer Science+Business Media New York 1999

Authors and Affiliations

  • Roger B. Nelsen
    • 1
  1. 1.Department of Mathematical SciencesLewis & Clark CollegePortlandUSA

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