Employing a geovisual exploratory post-analysis for interpretation of results of a spatial statistical method

Traditional regression analysis describes a modelled relationship between a dependent variable and a set of independent variables. When applied to spatial data, the regression analysis often assumes that the modelled relationship is stationary over space and produces a global model that is supposed to describe the relationship at every location in the study area. This can be misleading, as the relationships in spatial data are often intrinsically different across space. One of the spatial statistical methods that attempts to solve this problem and explain local variation in complex relationships is Geographically Weighted Regression – GWR (Fotheringham et al. 2000)