An evaluation of KL-optimum designs to discriminate between rival copula models

The problem of model discrimination has prompted a great amount of research over last years. According to the specific characteristics of the rival models (nested, non-nested, linear or not) different optimum criteria have been proposed to select design points with the aim to discriminate between rival models. Ds-, T- and KL-criteria are the most known. Up to our knowledge, in the literature there is not any study to evaluate the performance of these discrimination criteria. In this work, via a simulation study and focusing on rival copula models, we analyze the performance of the KL-optimum design applying the likelihood ratio test for nonnested models.