Statistics@SLU seminar: Geographically weighted regression model – identifying spatially differentiated relationships and trends

Geographically Weighted Regression (GWR) is a spatial statistical technique to model spatially varying relationships between variables. Unlike traditional regression models that assume a constant relationship across space, GWR recognizes that relationships between variables may vary depending on location.

In this talk, we cover the basics of GWR including assumptions and model choices. We illustrate how the models can be used to identify and visualize spatially differentiated relationships or – if there is a temporal component – temporal trends.