Dependence Modeling (May 2021)

Multivariate radial symmetry of copula functions: finite sample comparison in the i.i.d case

  • Billio Monica,
  • Frattarolo Lorenzo,
  • Guégan Dominique

DOI
https://doi.org/10.1515/demo-2021-0102
Journal volume & issue
Vol. 9, no. 1
pp. 43 – 61

Abstract

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Given a d-dimensional random vector X = (X1, . . ., Xd), if the standard uniform vector U obtained by the component-wise probability integral transform (PIT) of X has the same distribution of its point reflection through the center of the unit hypercube, then X is said to have copula radial symmetry. We generalize to higher dimensions the bivariate test introduced in [11], using three different possibilities for estimating copula derivatives under the null. In a comprehensive simulation study, we assess the finite-sample properties of the resulting tests, comparing them with the finite-sample performance of the multivariate competitors introduced in [17] and [1].

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