GWmodelS: a standalone software to train geographically weighted models

Lu, B., Hu, Y., Yang, D. et al. (5 more authors) (2024) GWmodelS: a standalone software to train geographically weighted models. Geo-spatial Information Science. ISSN 1009-5020

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Item Type: Article
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© 2024 Wuhan University. Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent.

Keywords: Spatial heterogeneity; spatial non-stationarity; visualization; high-performance; local techniques
Dates:
  • Published (online): 1 May 2024
  • Accepted: 9 April 2024
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: 10 Apr 2024 12:44
Last Modified: 17 May 2024 14:12
Published Version: https://www.tandfonline.com/doi/full/10.1080/10095...
Status: Published online
Publisher: Taylor & Francis Group
Identification Number: 10.1080/10095020.2024.2343011
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