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  • arXiv:2505. 22518v1 [stat. ML] 28 May 2025
    Copulas have become indispensable tools in multivariate analysis, enabling researchers to model complex dependencies among random variables by separating the marginal distributions from the dependence structure
  • Advances in special families of (multivariate) copulas: convergence . . .
    It is proved that the (d-1)-first partial derivatives of multivariate Archimedean copulas can exhibit pathological behavior similar to that of bivariate copulas Furthermore, article [03] demonstrates that the family of d-dimensional Archimedean copulas with this behavior is dense in the class of all d-dimensional Archimedean copulas w r t the
  • Modelling sample selection using Archimedean copulas
    The copula approach permits selection modelling based on multivariate non-normality Examples of self-selection models for labour supply and for duration of hospitalization illustrate the application of the copula approach to modelling
  • Advances in multivariate Archimedean copula modeling
    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





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