Research

We particularly aim at investigating and developing techniques for the analysis of high-dimensional data. We are both interested in parametric and nonparametric statistics as well as machine learning approaches. A further focus of our work is on statistical methodology for functional and categorical data, and the application of (modern) statistical methods in the agricultural sciences.


Potential Bachelor/Master Theses:

• Bachelor Thesis: Ebergeruch – wie verlässlich ist die Detektion?
• Master Thesis: Ordinale Regressionsmodelle zur Leistungsmessung bei Springpferden