6 citations · 13 across the 5 of their papers we have counts for
3 papers · 1 filter
Using model distances to investigate the simplifying assumption, model selection and truncation levels for vine copulas
Matthias Killiches, Daniel Kraus, Claudia Czado
Vine copulas are a useful statistical tool to describe the dependence structure between several random variables, especially when the number of variables is very large. When modeli…
Vine copula based likelihood estimation of dependence patterns in multivariate event time data
Nicole Barthel, Candida Geerdens, Matthias Killiches +2
In many studies multivariate event time data are generated from clusters having a possibly complex association pattern. Flexible models are needed to capture this dependence. Vine…
Examination and visualisation of the simplifying assumption for vine copulas in three dimensions
Matthias Killiches, Daniel Kraus, Claudia Czado
Vine copulas are a highly flexible class of dependence models, which are based on the decomposition of the density into bivariate building blocks. For applications one usually make…