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A Route Map for Successful Applications of Geographically Weighted Regression
Comber, Alexis1; Brunsdon, Christopher2; Charlton, Martin2; Dong, Guanpeng3; Harris, Richard4; Lu, Binbin5; Lu, Yihe6; Murakami, Daisuke7; Nakaya, Tomoki8; Wang, Yunqiang9; Harris, Paul10
Corresponding AuthorComber, Alexis(a.comber@leeds.ac.uk) ; Lu, Binbin(binbinlu@whu.edu.cn)
2022-01-09
Source PublicationGEOGRAPHICAL ANALYSIS
ISSN0016-7363
Pages24
AbstractGeographically Weighted Regression (GWR) is increasingly used in spatial analyses of social and environmental data. It allows spatial heterogeneities in processes and relationships to be investigated through a series of local regression models rather than a single global one. Standard GWR assumes that relationships between the response and predictor variables operate at the same spatial scale, which is frequently not the case. To address this, several GWR variants have been proposed. This paper describes a route map to decide whether to use a GWR model or not, and if so which of three core variants to apply: a standard GWR, a mixed GWR or a multiscale GWR (MS-GWR). The route map comprises 3 primary steps that should always be undertaken: (1) a basic linear regression, (2) a MS-GWR, and (3) investigations of the results of these in order to decide whether to use a GWR approach, and if so for determining the appropriate GWR variant. The paper also highlights the importance of investigating a number of secondary issues at global and local scales including collinearity, the influence of outliers, and dependent error terms. Code and data for the case study used to illustrate the route map are provided.
DOI10.1111/gean.12316
WOS KeywordSPATIALLY VARYING RELATIONSHIPS ; AUTOCORRELATION ; HETEROGENEITY ; SELECTION ; MODELS ; REGULARIZATION
Indexed BySCI ; SCI
Language英语
Funding ProjectNatural Environment Research Council Newton Fund Grant[NE/N007433/1] ; Natural Environment Research Council Newton Fund Grant[NE/S009124/1] ; Biotechnology and Biological Sciences Research Council[BBS/E/C/000J0100] ; Biotechnology and Biological Sciences Research Council[BBS/E/C/000I0320] ; Biotechnology and Biological Sciences Research Council[BBS/E/C/000I0330] ; National Natural Science Foundation of China[41571130083] ; National Natural Science Foundation of China[42071368] ; National Key Research and Development Program of China[2016YFC0501601]
WOS Research AreaGeography
Funding OrganizationNatural Environment Research Council Newton Fund Grant ; Biotechnology and Biological Sciences Research Council ; National Natural Science Foundation of China ; National Key Research and Development Program of China
WOS SubjectGeography
WOS IDWOS:000740628900001
PublisherWILEY
Citation statistics
Cited Times:50[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ieecas.cn/handle/361006/17366
Collection生态环境研究室
Corresponding AuthorComber, Alexis; Lu, Binbin
Affiliation1.Univ Leeds, Sch Geog, Woodhouse Lane, Leeds LS2 9JT, W Yorkshire, England
2.Maynooth Univ, Natl Ctr Geocomputat, Maynooth, Kildare, Ireland
3.Henan Univ, Key Res Inst Yellow River Civilizat & Sustainable, Kaifeng, Peoples R China
4.Univ Bristol, Sch Geog Sci, Bristol, Avon, England
5.Wuhan Univ, Sch Remote Sensing & Informat Engn, Wuhan 430072, Hubei, Peoples R China
6.Chinese Acad Sci, Res Ctr Ecoenvironm Sci, Joint Ctr Global Change Studies, State Key Lab Urban & Reg Ecol, Beijing, Peoples R China
7.Inst Stat Math, Dept Stat Data Sci, Tachikawa, Tokyo, Japan
8.Tohoku Univ, Grad Sch Environm Studies, Sendai, Miyagi, Japan
9.Chinese Acad Sci, Inst Earth Environm, State Key Lab Loess & Quaternary Geol, Xian, Peoples R China
10.Rothamsted Res, Sustainable Agr Sci, North Wyke, Okehampton, England
Recommended Citation
GB/T 7714
Comber, Alexis,Brunsdon, Christopher,Charlton, Martin,et al. A Route Map for Successful Applications of Geographically Weighted Regression[J]. GEOGRAPHICAL ANALYSIS,2022:24.
APA Comber, Alexis.,Brunsdon, Christopher.,Charlton, Martin.,Dong, Guanpeng.,Harris, Richard.,...&Harris, Paul.(2022).A Route Map for Successful Applications of Geographically Weighted Regression.GEOGRAPHICAL ANALYSIS,24.
MLA Comber, Alexis,et al."A Route Map for Successful Applications of Geographically Weighted Regression".GEOGRAPHICAL ANALYSIS (2022):24.
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