  Optimum experimental design theory has recently been extended for parameter
estimation in copula models. However, the choice of the correct dependence
structure still requires wider analyses. In this work the issue of copula
selection is treated by using discrimination design techniques. The new
proposed approach consists in the use of $D_s$-optimality following an
extension of corresponding equivalence theory. We also present some examples
and highlight the strength of such a criterion as a way to discriminate between
various classes of dependences.
