Assessment of Point Process Models for Earthquake Forecasting
classification
📊 stat.ME
keywords
modelsforecastingdataearthquakemethodsresidualtestsagree
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Models for forecasting earthquakes are currently tested prospectively in well-organized testing centers, using data collected after the models and their parameters are completely specified. The extent to which these models agree with the data is typically assessed using a variety of numerical tests, which unfortunately have low power and may be misleading for model comparison purposes. Promising alternatives exist, especially residual methods such as super-thinning and Voronoi residuals. This article reviews some of these tests and residual methods for determining the goodness of fit of earthquake forecasting models.
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