Abstract
Geographically Weighted Regression (GWR) and its variants are analysis methods that can cope with the multi-scale, spatially non-stationary relationships common to spatial data. They achieve this by using geographical sub-samples of the data for which one expects the complexity of any relationships to be simpler than over the whole study area.