Regression modelGIS / spatial

Local Spatial Regression

Local Spatial Regression fits a separate regression model at each location in a study area, allowing regression coefficients to vary continuously across space. Rather than forcing one global slope on all observations, it reveals where and how the relationship between predictors and an outcome changes geographically — producing a map of coefficients rather than a single number.

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Sources

  1. Fotheringham, A. S., Brunsdon, C., & Charlton, M. (2002). Geographically Weighted Regression: The Analysis of Spatially Varying Relationships. Wiley. ISBN: 978-0471496168
  2. Brunsdon, C., Fotheringham, A. S., & Charlton, M. (1996). Geographically weighted regression: A method for exploring spatial nonstationarity. Geographical Analysis, 28(4), 281-298. DOI: 10.1111/j.1538-4632.1996.tb00936.x

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Referenced by

ScholarGateLocal Spatial Regression (Local Spatial Regression). Retrieved 2026-06-04 from https://scholargate.app/en/spatial-analysis/local-spatial-regression