  Spatial statistics is a growing discipline providing important analytical
techniques in a wide range of disciplines in the natural and social sciences.
In the R package GWmodel, we introduce techniques from a particular branch of
spatial statistics, termed geographically weighted (GW) models. GW models suit
situations when data are not described well by some global model, but where
there are spatial regions where a suitably localised calibration provides a
better description. The approach uses a moving window weighting technique,
where localised models are found at target locations. Outputs are mapped to
provide a useful exploratory tool into the nature of the data spatial
heterogeneity. GWmodel includes: GW summary statistics, GW principal components
analysis, GW regression, GW regression with a local ridge compensation, and GW
regression for prediction; some of which are provided in basic and robust
forms.
