Abstract
Geographically weighted regression and the expansion method are two statistical techniques which can be used to examine the spatial variability of regression results across a region and so inform on the presence of spatial nonstationarity. Rather than accept one set of 'global' regression results, both techniques allow the possibility of producing 'local' regression results from any point within the region so that the output from the analysis is a set of mappable statistics which denote local relationships. Within the paper, the application of each technique to a set of health data from northeast England is compared. Geographically weighted regression is shown to produce more informative results regarding parameter variation over space.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 1905-1927 |
| Number of pages | 23 |
| Journal | Environment and Planning A |
| Volume | 30 |
| Issue number | 11 |
| State | Published - 1998 |
| Externally published | Yes |
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ASJC Scopus subject areas
- Environmental Science (miscellaneous)
- Geography, Planning and Development
Cite this
Geographically weighted regression : a natural evolution of the expansion method for spatial data analysis. / Fotheringham, Stewart; Charlton, M. E.; Brunsdon, C.
In: Environment and Planning A, Vol. 30, No. 11, 1998, p. 1905-1927.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Geographically weighted regression
T2 - a natural evolution of the expansion method for spatial data analysis
AU - Fotheringham, Stewart
AU - Charlton, M. E.
AU - Brunsdon, C.
PY - 1998
Y1 - 1998
N2 - Geographically weighted regression and the expansion method are two statistical techniques which can be used to examine the spatial variability of regression results across a region and so inform on the presence of spatial nonstationarity. Rather than accept one set of 'global' regression results, both techniques allow the possibility of producing 'local' regression results from any point within the region so that the output from the analysis is a set of mappable statistics which denote local relationships. Within the paper, the application of each technique to a set of health data from northeast England is compared. Geographically weighted regression is shown to produce more informative results regarding parameter variation over space.
AB - Geographically weighted regression and the expansion method are two statistical techniques which can be used to examine the spatial variability of regression results across a region and so inform on the presence of spatial nonstationarity. Rather than accept one set of 'global' regression results, both techniques allow the possibility of producing 'local' regression results from any point within the region so that the output from the analysis is a set of mappable statistics which denote local relationships. Within the paper, the application of each technique to a set of health data from northeast England is compared. Geographically weighted regression is shown to produce more informative results regarding parameter variation over space.
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UR - http://www.scopus.com/inward/citedby.url?scp=0032434789&partnerID=8YFLogxK
M3 - Article
AN - SCOPUS:0032434789
VL - 30
SP - 1905
EP - 1927
JO - Environment and Planning A
JF - Environment and Planning A
SN - 0308-518X
IS - 11
ER -