Using scoring functions to evaluate point process forecasts
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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.
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