Copula in a multivariate mixed discrete–continuous model

The use of different copula-based models to represent the joint distribution of an eight-dimensional mixed discrete and continuous problem consisting of five discrete and three continuous variables is investigated. The discussion starts with the theoretical properties of the copula-based models. Four different models are constructed for the data collected for the purpose of predicting the length of disruption caused by problems with the train detection system in the Dutch railway network and their performance is tested. The more complex models turn out to represent the data better. Nevertheless, it is shown that the simpler eight dimensional Normal copula still constitutes a statistically sound model for the data.