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

Lookup NU author(s): Dr Christopher Brunsdon, Emeritus Professor Murray Aitkin, Professor Alexander Fotheringham, M Charlton


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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.

Publication metadata

Author(s): Brunsdon CF, Aitkin M, Fotheringham AS, Charlton ME

Publication type: Article

Publication status: Published

Journal: Geographical and Environmental Modelling

Year: 1999

Volume: 3

Issue: 1

Pages: 47-62

Print publication date: 01/05/1999

ISSN (print): 1361-5939

ISSN (electronic): 1469-8323