Additive Mixed Models for Location, Scale and Shape via Gradient Boosting Techniques

In this work we adapt recent findings from statistical boosting in order to construct an estimation approach for distributional regression including random effects. The algorithm is applied to registry data provided by the German Cystic Fibrosis Registry where the subject-specific evolution of each patients lung function and its corresponding distributional parameters are modelled.