A comparison of random coefficient modelling and geographically weighted regression for spatially non-stationary regression problems

C. Brunsdon, M. Aitkin, S. Fotheringham, M. Charlton

Research output: Contribution to journalArticlepeer-review

33 Scopus citations

Abstract

The problem of locally varying coefficients in geographical applications is considered. Two approaches to this are then discussed-geographically weighted regression and random coefficient models. The latter is considered in two forms: firstly, the case that only the intercept coefficient is random; and then the case in which all coefficients are random. All these techniques are applied to a data set derived from the 1991 UK Census of Population relating to limiting long-term illness.

Original languageEnglish (US)
Pages (from-to)47-62
Number of pages16
JournalGeographical and Environmental Modelling
Volume3
Issue number1
StatePublished - 1999

ASJC Scopus subject areas

  • Geography, Planning and Development
  • Earth and Planetary Sciences(all)

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