Gollini, Isabella and Lu, Binbin and Charlton, Martin and Brunsdon, Chris and Harris, Paul (2015) GWmodel: An R Package for Exploring Spatial Heterogeneity Using Geographically Weighted Models. Journal of Statistical Software, 63. pp. 1-50. ISSN 1548-7660

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Abstract

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 present techniques from a particular branch of spatial statistics, termed geographi- cally 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 localized calibration provides a better description. The approach uses a moving window weighting technique, where localized models are found at target locations. Outputs are mapped to provide a useful exploratory tool into the nature of the data spatial heterogeneity. Cur- rently, GWmodel includes functions for: GW summary statistics, GW principal compo- nents analysis, GW regression, and GW discriminant analysis; some of which are provided in basic and robust forms.

Item Type:	Article
Keywords:	geographically weighted regression; geographically weighted principal components analysis; spatial prediction; robust; R package;
Academic Unit:	Faculty of Science and Engineering > Research Institutes > National Centre for Geocomputation, NCG
Item ID:	8050
Depositing User:	Prof. Chris Brunsdon
Date Deposited:	23 Mar 2017 11:50
Journal or Publication Title:	Journal of Statistical Software
Publisher:	Foundation for Open Access Statistics
Refereed:	Yes
URI:	Publisher
Use Licence:	This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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