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Geographically Weighted Regression-Modelling Spatial Non-Stationarity
Chris Brunsdon, Stewart Fotheringham and Martin Charlton
Journal of the Royal Statistical Society. Series D (The Statistician)
Vol. 47, No. 3 (1998), pp. 431-443
Stable URL: http://www.jstor.org/stable/2988625
Page Count: 13
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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.
Journal of the Royal Statistical Society. Series D (The Statistician) © 1998 Royal Statistical Society