Brunsdon, Chris and 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
Keywords:	Geographically Weighted; Discriminant Analysis;
Academic Unit:	Faculty of Science and Engineering > Research Institutes > National Centre for Geocomputation, NCG
Item ID:	5814
Identification Number:	https://doi.org/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
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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