Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
5077359 | Insurance: Mathematics and Economics | 2008 | 20 Pages |
Abstract
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 modelling 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.
Related Topics
Physical Sciences and Engineering
Mathematics
Statistics and Probability
Authors
Wilbert C.M. Kallenberg,