B0150
Title: Vine copula-based regression models
Authors: Claudia Czado - Technical University of Munich (Germany) [presenting]
Abstract: The aim is to model complex dependencies, including regression effects and time/space structures, using vine copula-based models. These allow the construction of high dimensional multivariate distributions for data, including different asymmetrical dependencies for each pair of variables. Computer-aided processes are developed/optimized for selection, estimation, and adaptation to complex data structures. Applications can be found in finance, insurance, engineering, earth and life sciences. Several cooperation agreements with various international scientists and industry representatives are in place, and further published work on analyzing dependent data with vine copulas is available.
