Prof. Dr. T. Dickhaus
Multivariate multiple test procedures have received growing attention recently. This is due to the fact that data generated by modern applications typically are high-dimensional, but possess pronounced dependencies due to the technical mechanisms involved in the experiments. Hence, it is possible and often necessary to exploit these dependencies in order to achieve reasonable power. We express dependency structures in the most general manner, namely, by means of copula functions. Utilizing copula estimation techniques, some (empirically calibrated) multivariate multiple tests are derived.