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Comber, A orcid.org/0000-0002-3652-7846, Brunsdon, C, Charlton, M et al. (8 more authors) (2023) A route map for successful applications of Geographically Weighted Regression. Geographical Analysis, 55 (1). pp. 155-178. ISSN 0016-7363
Abstract
Geographically Weighted Regression (GWR) is increasingly used in spatial analyses of social and environmental data. It allows spatial heterogeneities in processes and relationships to be investigated through a series of local regression models rather than a single global one. Standard GWR assumes that relationships between the response and predictor variables operate at the same spatial scale, which is frequently not the case. To address this, several GWR variants have been proposed. This paper describes a route map to decide whether to use a GWR model or not, and if so which of three core variants to apply: a standard GWR, a mixed GWR or a multiscale GWR (MS-GWR). The route map comprises 3 primary steps that should always be undertaken: (1) a basic linear regression, (2) a MS-GWR, and (3) investigations of the results of these in order to decide whether to use a GWR approach, and if so for determining the appropriate GWR variant. The paper also highlights the importance of investigating a number of secondary issues at global and local scales including collinearity, the influence of outliers, and dependent error terms. Code and data for the case study used to illustrate the route map are provided.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2022 The Authors. Geographical Analysis published by Wiley Periodicals LLC on behalf of The Ohio State University. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Environment (Leeds) > School of Geography (Leeds) > Centre for Spatial Analysis & Policy (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 04 Jan 2022 16:00 |
Last Modified: | 09 Jan 2025 11:55 |
Status: | Published |
Publisher: | Wiley |
Identification Number: | 10.1111/gean.12316 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:181740 |
Available Versions of this Item
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The GWR route map: a guide to the informed application of Geographically Weighted Regression. (deposited 09 Jan 2025 11:56)
- A route map for successful applications of Geographically Weighted Regression. (deposited 04 Jan 2022 16:00) [Currently Displayed]