Thordis L. Thorarinsdottirr: Model selection for point process models Abstract: The theory of point processes offers a realistic class of models for many processes that arise in fields such as epidemiology, ecology, and geology. However, these models are often difficult to analyse due to their computational complexity and model selection methods have not been adequately investigated. The primary focus of existing model selection methodology aims to detect repulsion or aggregation in the point pattern. While this is an important first step in the modelling of spatial and spatio-temporal processes, there can be a need to directly compare different repulsion or aggregation models, for which a more formal procedures for model comparison are called for. In this talk, I will discuss a general Bayesian framework that allows for such comparisons to be naturally conducted while simultaneously performing parameter inference and out of sample prediction.