Distributional Regression – Models and Applications: Our Tutorial at DAGstat 2025

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. You can register through the DAGStat Website.

Material

All material for the course is available through github. Please download the data files and have a recent version of R and the package bamlss installed. We recommend the use of RStudio.