A new way of choosing a suitable copula to model dependence is introduced. Instead of relying on a given parametric family of copulas or applying the other extreme of modeling dependence in a nonparametric way, an intermediate approach is proposed, based on a sequence of parametric models containing more and more dependency aspects. In contrast to a similar way of thinking in testing theory, the method here, intended for estimating the copula, often requires a somewhat larger number of steps. One approach is based on exponential families, another on contamination families. An extensive numerical investigation is supplied on a large number of well known copulas. The method based on contamination families is recommended. A Gaussian start in this approximation looks very promising.
|Name||Applied Mathematics Memoranda|
|Publisher||Department of Applied Mathematics, University of Twente|