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Diagnostics for the Validity of the Simplifying Assumption for Vine Copulas

In: Statistical Dependence Modeling

Author

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  • Harry Joe

    (University of British Columbia)

Abstract

Diagnostic methods are given for assessing the simplifying assumption for vine copulas. These include (a) measures of central and tail-weighted dependence applied to conditional distributions, so that they are functions of the conditioning variables, and (b) comparisons of the fit of several different vine copulas. The methods are applied to simulated data sets from some low-dimensional non-simplified vine copulas, and from the multivariate gamma factor model for which no conditioning satisfies the simplifying assumption. The methods are also applied to some real data sets. The examples verify that methods work well and can suggest copula models to fit without the simplifying assumption.

Suggested Citation

  • Harry Joe, 2026. "Diagnostics for the Validity of the Simplifying Assumption for Vine Copulas," Springer Books, in: Thomas Nagler & Dorota Kurowicka & Roger Cooke & Harry Joe (ed.), Statistical Dependence Modeling, pages 77-107, Springer.
    • Handle: RePEc:spr:sprchp:978-3-032-14252-8_5
    DOI: 10.1007/978-3-032-14252-8_5
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