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Spatial-filtering-based contributions to a critique of geographically weighted regression (GWR)

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  • Daniel A Griffith

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.

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  • Daniel A Griffith, 2008. "Spatial-filtering-based contributions to a critique of geographically weighted regression (GWR)," Environment and Planning A, Pion Ltd, London, vol. 40(11), pages 2751-2769, November.
  • Handle: RePEc:pio:envira:v:40:y:2008:i:11:p:2751-2769
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    Citations

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    Cited by:

    1. Dean Hanink & Robert Cromley & Avraham Ebenstein, 2012. "Wage-based evidence of returns to external scale in China’s manufacturing: a spatial analysis," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 49(1), pages 1-16, August.
    2. Enrico Marelli & Roberto Patuelli & Marcello Signorelli, 2012. "Regional unemployment in the EU before and after the global crisis," Post-Communist Economies, Taylor & Francis Journals, vol. 24(2), pages 155-175, January.
    3. Sandy Burden & Noel Cressie & David G. Steel, 2015. "The SAR Model for Very Large Datasets: A Reduced Rank Approach," Econometrics, MDPI, Open Access Journal, vol. 3(2), pages 1-22, May.
    4. M. Mayor-Fernández & R. Patuelli, 2012. "Short-Run Regional Forecasts: Spatial Models through Varying Cross-Sectional and Temporal Dimensions," Working Papers wp835, Dipartimento Scienze Economiche, Universita' di Bologna.
    5. M. Bárcena & P. Menéndez & M. Palacios & F. Tusell, 2014. "Alleviating the effect of collinearity in geographically weighted regression," Journal of Geographical Systems, Springer, vol. 16(4), pages 441-466, October.
    6. Giuseppe Ricciardo Lamonica & Barbara Zagaglia, 2013. "The determinants of internal mobility in Italy, 1995-2006," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 29(16), pages 407-440, September.
    7. Dean Hanink & Robert Cromley & Avraham Ebenstein, 2012. "Spatial Variation in the Determinants of House Prices and Apartment Rents in China," The Journal of Real Estate Finance and Economics, Springer, vol. 45(2), pages 347-363, August.
    8. 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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