Journal
INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE
Volume 30, Issue 2, Pages 351-368Publisher
TAYLOR & FRANCIS LTD
DOI: 10.1080/13658816.2015.1087001
Keywords
Non-stationarity; GW model; Minkowski distance; simulation experiment
Categories
Funding
- National Natural Science Foundation of China [NSFC: 41401455, NSFC: 41331175]
- Strategic Research Cluster by the Science Foundation Ireland under the National Development Plan [07/SRC/I1168]
- Biotechnology and Biological Sciences Research Council of the UK [BBSRC BB/J004308]
- BBSRC [BBS/E/C/00005190] Funding Source: UKRI
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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.
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