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

Daniel A Griffith
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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

Environment and Planning A, 2008, vol. 40, issue 11, 2751-2769

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.

Date: 2008
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Persistent link: https://EconPapers.repec.org/RePEc:sae:envira:v:40:y:2008:i:11:p:2751-2769

DOI: 10.1068/a38218

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