Brunsdon, Chris, Fotheringham, Stewart and Charlton, Martin (2007) Geographically Weighted Discriminant Analysis. Geographical Analysis, 39 (4). pp. 376-396. ISSN 1538-4632
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Abstract
n this article, we propose a novel analysis technique for geographical data, Geo-
graphically Weighted Discriminant Analysis. This approach adapts the method of
Geographically Weighted Regression (GWR), allowing the modeling and prediction of
categorical response variables. As with GWR, the relationship between predictor and
response variables may alter over space, and calibration is achieved using a moving
kernel window approach. The methodology is outlined and is illustrated with an ex-
ample analysis of voting patterns in the 2005 UK general election. The example shows
that similar social conditions can lead to different voting outcomes in different parts of
England and Wales. Also discussed are techniques for visualizing the results of the
analysis and methods for choosing the extent of the moving kernel window.
Item Type: | Article |
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Keywords: | Geographically Weighted; Discriminant Analysis; |
Academic Unit: | Faculty of Science and Engineering > Research Institutes > National Centre for Geocomputation, NCG |
Item ID: | 5814 |
Identification Number: | 10.1111/j.1538-4632.2007.00709.x |
Depositing User: | Martin Charlton |
Date Deposited: | 10 Feb 2015 17:31 |
Journal or Publication Title: | Geographical Analysis |
Publisher: | Wiley |
Refereed: | Yes |
Related URLs: | |
URI: | https://mu.eprints-hosting.org/id/eprint/5814 |
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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