A response to ‘A comment on geographically weighted regression with parameter-specific distance metrics’ |
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| Authors: | Binbin Lu Chris Brunsdon Martin Charlton Paul Harris |
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| Institution: | 1. School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China;2. National Centre for Geocomputation, Maynooth University, Maynooth, Co. Kildare, Ireland;3. Sustainable Soils and Grassland Systems, Rothamsted Research, Okehampton, UK |
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| Abstract: | In this article, we respond to ‘A comment on geographically weighted regression with parameter-specific distance metrics’ by Oshan et al. (2019), published in this journal, where several concerns on the parameter-specific distance metric geographically weighted regression (PSDM GWR) technique are raised. In doing so, we review the developmental timeline of the multiscale geographically weighed regression modelling framework with related and equivalent models, including flexible bandwidth GWR, conditional GWR and PSDM GWR. In our response, we have tried to answer all the concerns raised in terms of applicability, veracity, interpretability and computational efficiency of the PSDM GWR model. |
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| Keywords: | Multiscale GWmodel local regression spatial heterogeneity GWR |
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