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Circular Data Modelling

PhD project: Kees Mulder

Bayesian circular models in the intrinsic approach

Kees Mulder’s project employs the intrinsic approach in circular data modeling, which focuses on distributions defined directly on the circle, such as the von Mises distribution. These models have simpler form than many other circular data models, but face a multitude of practical problems. In this project, we attempt to solve issues in the intrinsic approach within the Bayesian framework. Currently the focus is on developing a general GLM-like model that allows for a wide variety of models as restrictions of the more general model. Initial research will focus on performing estimation through MCMC-methods, while later hypothesis testing and model comparison will be included, as well.

Code for this project is available on GitHub.