Geographically Weighted Regression
{"Image DocumentName": "Geographically Weighted Regression", "Image ImageDescription": "In fact, the idea of calculating Local Indicators can be applied to any standard statistic (O&U p. 205) You simply calculate the statistic for every polygon and its neighbors, then map the result. Mathematically, this can be achieved by applying the weights matrix to the standard formulae for the statistic of interest. The recent idea of geographically weighted regression, simply calculates a separate regression for each polygon and its neighbors, then maps the parameters from the model, such as the regression coefficient (b) or its significance value. Again, that\u2019s a topic for another course. See Fotheringham, Brunsdon and Charlton Geographically Weighted Regression Wiley, Briggs UT-Dallas GISC 6382 Spring 2007.", "Image XResolution": "37", "Image YResolution": "37", "Image ResolutionUnit": "Pixels/Centimeter", "Image Software": "SlidePlayer", "Image YCbCrPositioning": "Centered"}