On the classification and treatment of outliers in a spatial context: A Bayesian Updating approach

Abstract Checking and treating extreme values is commonplace in modelling workflows. The main methods to manage outliers may be categorized into graphical, Kriging- and simulation-based approaches. While graphical methods usually classify outliers from a global perspective, geostatistical methods evaluate outliers in a local context. Ordinary-Kriging based approaches are affected by conditional bias associated with the distribution tail(s), impacting on the correct classification of extreme values; the simulation method is based on the fact that geostatistical simulation is robust for outlier ...