ABSTRACT
In this study, the geographically weighted regression (GWR) model is adapted to benefit from a broad range of distance metrics, where it is demonstrated that a well-chosen distance metric can improve model performance. How to choose or define such a distance metric is key, and in this respect, a ‘Minkowski approach’ is proposed that enables the selection of an optimum distance metric for a given GWR model. This approach is evaluated within a simulation experiment consisting of three scenarios. The results are twofold: (1) a well-chosen distance metric can significantly improve the predictive accuracy of a GWR model; and (2) the approach allows a good approximation of the underlying ‘optimal distance metric’, which is considered useful when the ‘true’ distance metric is unknown.
ORCID
Chris Brunsdon http://orcid.org/0000-0003-4254-1780
Notes
1. The period of Equation (5) is , that is, very close to 1.57, so a rotation of 1.57 will be almost no different from a 0 rotation.
2. Coordinate rotations are invalid for ED, so the model is only calibrated once, when p is 2.