Using scoring functions to evaluate point process forecasts

Point process models are widely used tools to issue forecasts or assess risks. In order to check which models are useful in practice, they are examined by a variety of statistical methods. We transfer the concept of consistent scoring functions, which are principled statistical tools to compare forecasts, to the point process setting. The results provide a novel approach for the comparative assessment of forecasts and models and encompass some existing testing procedures.