Improvements to the calibration of a geographically weighted regression with parameter-specific distance metrics and bandwidths

doi:10.1016/j.compenvurbsys.2018.03.012

	Improvements to the calibration of a geographically weighted regression with parameter-specific distance metrics and bandwidths
	Lu, Binbin 1,2; Yang, Wenbai 3; Ge, Yong 4; Harris, Paul 5
刊名	COMPUTERS ENVIRONMENT AND URBAN SYSTEMS
	2018-09-01
卷号	71 页码:41-57
关键词	Local regression Spatial heterogeneity Bandwidth selection Multi-scale GWmodel
ISSN号	0198-9715
DOI	10.1016/j.compenvurbsys.2018.03.012
通讯作者	Lu, Binbin(binbinlu@whu.edu.cn)
英文摘要	In standard geographically weighted regression (GWR), the spatially-varying relationships between the dependent and each independent variable are explored under a constant and fixed scale, but for many processes their variation intensity may differ with respect to location and direction. To address this short-coming, a GWR model with parameter-specific distance metrics (PSDM GWR) can be used, which by default, also specifies parameter specific bandwidths. In doing so, PSDM GWR provides a scale-dependent extension of GWR. Commonly however, an ideal distance metric for a given independent variable parameter is not immediately obvious. Thus, in this article, PSDM GWR is investigated with respect to distance metric choice. Here, it is demonstrated that the optimum (distance metric specific) bandwidth corresponding to a given independent variable remains essentially constant, independent of the choices made for the other independent variables. This result allows for a considerable saving in computational overheads, permitting a much simpler searching procedure for multiple bandwidth optimization. Results are first demonstrated empirically, and then a simulation experiment is conducted to objectively verify the same findings. Computational savings are vital to the uptake of PSDM GWR, where ultimately, it should be considered the default choice in any GWR-based study of spatially-varying relationships, as standard GWR, mixed (or semi-parametric) GWR, flexible bandwidth (or multi-scale) GWR and the global regression are specific cases thereof.
资助项目	Natural Science Foundation of China[NSFC: U1533102] ; Natural Science Foundation of China[41331175] ; open research fund by State Key Laboratory of Resources and Environmental Information System[1610] ; open Research Fund Program of Shenzhen Key Laboratory of Spatial Smart Sensing and Services (Shenzhen University)[1712] ; UK Biotechnology and Biological Sciences Research Council Grant[BBSRC BB/J004308/1]
WOS关键词	HOUSE PRICE DATA ; SPATIAL ASSOCIATION ; MONTE-CARLO ; MODELS ; SELECTION ; GWR
WOS研究方向	Computer Science ; Engineering ; Environmental Sciences & Ecology ; Geography ; Operations Research & Management Science
语种	英语
出版者	ELSEVIER SCI LTD
WOS记录号	WOS:000445169400004
资助机构	Natural Science Foundation of China ; open research fund by State Key Laboratory of Resources and Environmental Information System ; open Research Fund Program of Shenzhen Key Laboratory of Spatial Smart Sensing and Services (Shenzhen University) ; UK Biotechnology and Biological Sciences Research Council Grant
内容类型	期刊论文
源URL	[http://ir.igsnrr.ac.cn/handle/311030/52901]
专题	中国科学院地理科学与资源研究所
通讯作者	Lu, Binbin
作者单位	1.Wuhan Univ, Sch Remote Sensing & Informat Engn, 129 Luoyu Rd, Wuhan 430079, Hubei, Peoples R China 2.Wuhan Univ, Natl Adm Surveying Mapping & Geoinformat, Key Lab Natl Geog Census & Monitoring, 129 Luoyu Rd, Wuhan 430079, Hubei, Peoples R China 3.Reed Elsevier Informat Technol Beijing Co Ltd, Beijing, Peoples R China 4.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing, Peoples R China 5.Rothamsted Res, Sustainable Soils & Grassland Syst, North Wyke, Okehampton, England
推荐引用方式 GB/T 7714	Lu, Binbin,Yang, Wenbai,Ge, Yong,et al. Improvements to the calibration of a geographically weighted regression with parameter-specific distance metrics and bandwidths[J]. COMPUTERS ENVIRONMENT AND URBAN SYSTEMS,2018,71:41-57.
APA	Lu, Binbin,Yang, Wenbai,Ge, Yong,&Harris, Paul.(2018).Improvements to the calibration of a geographically weighted regression with parameter-specific distance metrics and bandwidths.COMPUTERS ENVIRONMENT AND URBAN SYSTEMS,71,41-57.
MLA	Lu, Binbin,et al."Improvements to the calibration of a geographically weighted regression with parameter-specific distance metrics and bandwidths".COMPUTERS ENVIRONMENT AND URBAN SYSTEMS 71(2018):41-57.