| 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 Author | Comber, Alexis(a.comber@leeds.ac.uk) ; Lu, Binbin(binbinlu@whu.edu.cn) |
| 2022-01-09 | |
| Source Publication | GEOGRAPHICAL ANALYSIS
 |
| ISSN | 0016-7363 |
| Pages | 24 |
| Abstract | Geographically 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. |
| DOI | 10.1111/gean.12316 |
| WOS Keyword | SPATIALLY VARYING RELATIONSHIPS ; AUTOCORRELATION ; HETEROGENEITY ; SELECTION ; MODELS ; REGULARIZATION |
| Indexed By | SCI ; SCI |
| Language | 英语 |
| Funding Project | Natural 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 Area | Geography |
| Funding Organization | Natural 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 Subject | Geography |
| WOS ID | WOS:000740628900001 |
| Publisher | WILEY |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://ir.ieecas.cn/handle/361006/17366 |
| Collection | 生态环境研究室 |
| Corresponding Author | Comber, Alexis; Lu, Binbin |
| Affiliation | 1.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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