Geographically Weighted Regression

Most statistical techniques assume that relationships are constant over space (the assumption of spatial stationarity). Geographically weighted regression (GWR) is a statistical technique that allows relationships to vary spatially within a study region (it therefore allows spatial nonstationarity). The relaxation of the stationarity assumption in regression has proven to be effective in modeling many spatial processes. This entry summarizes the conceptual and mathematical background to GWR.


Regression analysis, in various guises, is without much doubt the most popular form of statistical analysis practiced. Its popularity arises because it allows researchers to quantify the relationship between two variables while accounting for (holding constant) the potentially confounding relationships between other variables. This is an extremely useful feature that can be employed in a wide variety of application areas. ...

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