Tsutsumida, N., Murakami, D., Yoshida, T. et al. (4 more authors) (2022) A Comparison of Geographically Weighted Principal Components Analysis Methodologies. In: Leibniz International Proceedings in Informatics, LIPIcs. 15th International Conference on Spatial Information Theory (COSIT 2022), 05-09 Sep 2022, Kobe, Japan. Schloss Dagstuhl - Leibniz-Zentrum für Informatik , Wadern, Germany , 21:1-21:6. ISBN 9783959772570
Abstract
Principal components analysis (PCA) is a useful analytical tool to represent key characteristics of multivariate data, but does not account for spatial effects when applied in geographical situations. A geographically weighted PCA (GWPCA) caters to this issue, specifically in terms of capturing spatial heterogeneity. However, in certain situations, a GWPCA provides outputs that vary discontinuously spatially, which are difficult to interpret and are not associated with the output from a conventional (global) PCA any more. This study underlines a GW non-negative PCA, a geographically weighted version of non-negative PCA, to overcome this issue by constraining loading values non-negatively. Case study results with a complex multivariate spatial dataset demonstrate such benefits, where GW non-negative PCA allows improved interpretations than that found with conventional GWPCA.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © Narumasa Tsutsumida, Daisuke Murakami, Takahiro Yoshida, Tomoki Nakaya, Binbin Lu, Paul Harris, and Alexis Comber; licensed under Creative Commons License CC-BY 4.0. |
Keywords: | Spatial heterogeneity, Geographically weighted, Sparsity, PCA |
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: | 18 Dec 2023 11:35 |
Last Modified: | 18 Dec 2023 11:52 |
Published Version: | https://drops.dagstuhl.de/entities/document/10.423... |
Status: | Published |
Publisher: | Schloss Dagstuhl - Leibniz-Zentrum für Informatik |
Identification Number: | 10.4230/LIPIcs.COSIT.2022.21 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:206672 |