Regression modelGIS / spatial

Robust Spatial Autocorrelation

Robust spatial autocorrelation methods measure the degree to which nearby geographic units share similar values, while explicitly controlling for the distorting influence of spatial outliers and extreme observations. They extend classical statistics such as Moran's I by down-weighting or trimming observations that would otherwise inflate or deflate the autocorrelation signal.

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Sources

  1. Anselin, L., & Florax, R. J. G. M. (1995). Small sample properties of tests for spatial dependence in regression models: some further results. In Anselin, L. & Florax, R. J. G. M. (Eds.), New Directions in Spatial Econometrics. Springer, Berlin. link
  2. Cliff, A. D., & Ord, J. K. (1981). Spatial Processes: Models and Applications. Pion, London. ISBN: 0850860814

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Referenced by

ScholarGateRobust Spatial Autocorrelation (Robust Spatial Autocorrelation Analysis). Retrieved 2026-06-04 from https://scholargate.app/en/spatial-analysis/robust-spatial-autocorrelation