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

A. S. Fotheringham; M. E. Charlton; C. Brunsdon

doi:10.1068/a301905

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

A. S. Fotheringham, M. E. Charlton, C. Brunsdon

CLAS-SS: Geographical Sciences and Urban Planning, School of (SGSUP)

Research output: Contribution to journal › Article › peer-review

507 Scopus citations

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
DOIs	https://doi.org/10.1068/a301905
State	Published - 1998

ASJC Scopus subject areas

Geography, Planning and Development
Environmental Science (miscellaneous)

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