Murakami, Daisuke and Lu, Binbin and Harris, Paul and Brunsdon, Chris and Charlton, Martin and Nakaya, Tomoki and Griffith, Daniel A. (2018) The Importance of Scale in Spatially Varying Coefficient Modeling. Annals of the American Association of Geographers, 109 (1). pp. 50-70. ISSN 2469-4452

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Abstract

Although spatially varying coefficient (SVC) models have attracted considerable attention in applied science, they have been criticized as being unstable. The objective of this study is to show that capturing the “spatial scale” of each data relationship is crucially important to make SVC modeling more stable and, in doing so, adds flexibility. Here, the analytical properties of six SVC models are summarized in terms of their characterization of scale. Models are examined through a series of Monte Carlo simulation experiments to assess the extent to which spatial scale influences model stability and the accuracy of their SVC estimates. The following models are studied: (1) geographically weighted regression (GWR) with a fixed distance or (2) an adaptive distance bandwidth (GWRa); (3) flexible bandwidth GWR (FB-GWR) with fixed distance or (4) adaptive distance bandwidths (FB-GWRa); (5) eigenvector spatial filtering (ESF); and (6) random effects ESF (RE-ESF). Results reveal that the SVC models designed to capture scale dependencies in local relationships (FB-GWR, FB-GWRa, and RE-ESF) most accurately estimate the simulated SVCs, where REESF is the most computationally efficient. Conversely, GWR and ESF, where SVC estimates are naï vely assumed to operate at the same spatial scale for each relationship, perform poorly. Results also confirm that the adaptive bandwidth GWR models (GWRa and FB-GWRa) are superior to their fixed bandwidth counterparts (GWR and FB-GWR).

Item Type:	Article
Keywords:	flexible bandwidth geographically weighted regression; Monte Carlo simulation; nonstationarity; random effects eigenvector spatial filtering; spatial scale;
Academic Unit:	Faculty of Science and Engineering > Research Institutes > National Centre for Geocomputation, NCG Faculty of Social Sciences > Geography
Item ID:	13054
Identification Number:	https://doi.org/10.1080/24694452.2018.1462691
Depositing User:	Prof. Chris Brunsdon
Date Deposited:	12 Jun 2020 14:56
Journal or Publication Title:	Annals of the American Association of Geographers
Publisher:	Taylor and Francis
Refereed:	Yes
URI:	Publisher
Use Licence:	This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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