Paul Wiemann

My research focuses on methods in the Bayesian framework. This includes variable and model selection as well as the issue of sample selection in the context of distributional regression models. I’m also interested in MCMC algorithms and software for Bayesian inference and the application of Bayesian methods in quantitative sciences, especially psychometrics and economics.

I hold degrees in computer science and applied statistics. Since November 2015, I work as a research assistant at the chair of statistics. In the last two years, I have taught courses on linear models and the programming language R. In addition, my teaching includes a course on Mixed Models and Spatial Statistics and I’ve been teaching at the Data Science Summer School Goettingen 2017.