A response to "A comment on geographically weighted regression with parameter-specific distance metrics'

被引:20
|
作者
Lu, Binbin [1 ]
Brunsdon, Chris [2 ]
Charlton, Martin [2 ]
Harris, Paul [3 ]
机构
[1] Wuhan Univ, Sch Remote Sensing & Informat Engn, Wuhan, Hubei, Peoples R China
[2] Maynooth Univ, Natl Ctr Geocomputat, Maynooth, Co Kildare, Ireland
[3] Rothamsted Res, Sustainable Soils & Grassland Syst, Okehampton EX20 2SB, Devon, England
基金
中国国家自然科学基金; 英国生物技术与生命科学研究理事会;
关键词
Multiscale; GWmodel; local regression; spatial heterogeneity; GWR; MODELS; COEFFICIENTS;
D O I
10.1080/13658816.2019.1585541
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页码:1300 / 1312
页数:13
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