Distributional Regression – Models and Applications

This tutorial, structured into two three-hour blocks, provides an interactive exploration of distributional regression, building on the foundational concepts of generalized linear and additive models. Participants will obtain a review of various distributional regression models and their applications, highlighting the advantages of modeling entire response distributions over traditional mean regression. The session will include hands-on exercises using R, with a focus Bayesian Additive Models for Location Scale and Shape and distributional regression for univariate responses and its extensions to multivariate responses. Through practical exercises and real-world illustrations, participants will gain insights into when and how to apply these models effectively. By the end of the workshop, attendees will have a solid understanding of distributional regression principles and practical skills in model building, estimation, and interpretation. The tutorial is organised by Nadja Klein and Lucas Kock.