Robust Getis-Ord Gi*
The Robust Getis-Ord Gi* statistic extends the classical Gi* hot-spot measure to handle outliers in spatial data. By using robust estimators of the mean and variance — such as trimmed means, medians, or down-weighted influential observations — it identifies statistically significant spatial clusters of high or low values even when the attribute distribution contains extreme values that would distort the standard Gi*.
Source record
Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.
- Getis, A., & Ord, J. K. (1992). The analysis of spatial association by use of distance statistics. Geographical Analysis, 24(3), 189–206. · DOI 10.1111/j.1538-4632.1992.tb00261.x
- Anselin, L., & Liu, X. (2010). Spatial panel econometrics. In Handbook of Applied Economic Statistics. Robust spatial statistics variants are discussed in the context of outlier-resistant local indicators. See also: Anselin, L. (2018). A local indicator of multivariate spatial association. Geographical Analysis, 51(2), 133–150. · URL
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