Lu, Binbin and Harris, Paul and Charlton, Martin and Brunsdon, Chris
(2013)
The GWmodel R package: Further Topics for Exploring Spatial
Heterogeneity using Geographically Weighted Models.
Geo-spatial Information Science, 17 (2).
ISSN 1993-5153
Abstract
In this study, we present a collection of local models, termed geographically weighted
(GW) models, that can be found within the GWmodel R package. A GW model suits
situations when spatial data are poorly described by the global form, and for some
regions the localised fit provides a better description. The approach uses a moving
window weighting technique, where a collection of local models are estimated at target
locations. Commonly, model parameters or outputs are mapped so that the nature of
spatial heterogeneity can be explored and assessed. In particular, we present case
studies using: (i) GW summary statistics and a GW principal components analysis; (ii)
advanced GW regression fits and diagnostics; (iii) associated Monte Carlo significance
tests for non-stationarity; (iv) a GW discriminant analysis; and (v) enhanced kernel
bandwidth selection procedures. General Election data sets from the Republic of
Ireland and US are used for demonstration. This study is designed to complement a
companion GWmodel study, which focuses on basic and robust GW models.
| Item Type: |
Article
|
| Keywords: |
Principal Components Analysis; Semi-parametric GW regression;
Discriminant Analysis; Monte Carlo Tests; Election Data; |
| Academic Unit: |
Faculty of Science and Engineering > Research Institutes > National Centre for Geocomputation, NCG |
| Item ID: |
5752 |
| Depositing User: |
Martin Charlton
|
| Date Deposited: |
02 Feb 2015 12:04 |
| Journal or Publication Title: |
Geo-spatial Information Science |
| Publisher: |
Wuhan University |
| Refereed: |
Yes |
| URI: |
|
| 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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