Geographically weighted regression: a natural evolution of the expansion method for spatial data analysis

Stewart Fotheringham, M. E. Charlton, C. Brunsdon

Research output: Contribution to journalArticle

424 Citations (Scopus)

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 languageEnglish (US)
Pages (from-to)1905-1927
Number of pages23
JournalEnvironment and Planning A
Volume30
Issue number11
StatePublished - 1998
Externally publishedYes

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spatial data
data analysis
regression
statistics
method
health
analysis
parameter

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 journalArticle

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