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Spatial-Filtering-Based Contributions to a Critique of Geographically Weighted Regression (GWR)

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  • Daniel A Griffith

    (Ashbel Smith Professor, School of Economic, Political and Policy Sciences, University of Texas at Dallas, Richardson, TX, 75080-3021, USA)

Abstract

Interaction terms are constructed with georeferenced attribute variables and spatial filter eigenvectors, and then used to compute geographically varying regression coefficients. These coefficients, which are analogous to geographically weighted regression (GWR) coefficients, display preferable properties, and this specification is used to critique selected features of GWR. Comparisons are illustrated with the Georgia data appearing in the standard GWR tutorial.

Suggested Citation

  • Daniel A Griffith, 2008. "Spatial-Filtering-Based Contributions to a Critique of Geographically Weighted Regression (GWR)," Environment and Planning A, , vol. 40(11), pages 2751-2769, November.
    • Handle: RePEc:sae:envira:v:40:y:2008:i:11:p:2751-2769
    DOI: 10.1068/a38218
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    References listed on IDEAS

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    1. Daniel A. Griffith, 2000. "A linear regression solution to the spatial autocorrelation problem," Journal of Geographical Systems, Springer, vol. 2(2), pages 141-156, July.
    2. David Wheeler & Michael Tiefelsdorf, 2005. "Multicollinearity and correlation among local regression coefficients in geographically weighted regression," Journal of Geographical Systems, Springer, vol. 7(2), pages 161-187, June.
    3. Daniel A. Griffith, 2003. "Spatial Autocorrelation and Spatial Filtering," Advances in Spatial Science, Springer, number 978-3-540-24806-4.
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    Cited by:

    1. Jinjun Tang & Fan Gao & Fang Liu & Wenhui Zhang & Yong Qi, 2019. "Understanding Spatio-Temporal Characteristics of Urban Travel Demand Based on the Combination of GWR and GLM," Sustainability, MDPI, vol. 11(19), pages 1-19, October.
    2. Daisuke Murakami & Daniel Griffith, 2015. "Random effects specifications in eigenvector spatial filtering: a simulation study," Journal of Geographical Systems, Springer, vol. 17(4), pages 311-331, October.

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