Geographically weighted regression - Modelling spatial non-stationarity

Chris Brunsdont, Stewart Fotheringham, Martin Charlton

Research output: Contribution to journalArticle

557 Scopus citations

Abstract

In regression models where the cases are geographical locations, sometimes regression coefficients do not remain fixed over space. A technique for exploring this phenomenon, geographically weighted regression is introduced. A related Monte Carlo significance test for spatial non-stationarity is also considered. Finally, an example of the method is given, using limiting long-term illness data from the 1991 UK census.

Original languageEnglish (US)
Pages (from-to)431-443
Number of pages13
JournalJournal of the Royal Statistical Society Series D: The Statistician
Volume47
Issue number3
DOIs
StatePublished - Jan 1 1998
Externally publishedYes

Keywords

  • Exploratory data analysis
  • Geographically weighted regression
  • Monte Carlo testing
  • Regression
  • Spatial non-stationarity

ASJC Scopus subject areas

  • Statistics and Probability

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