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Robuste Getis-Ord Gi*-Statistik×Hot Spot Analysis (Getis-Ord Gi*)×
FachgebietRäumliche AnalyseRäumliche Analyse
FamilieRegression modelRegression model
Entstehungsjahr1992 (base); robust variants circa 2000s–2010s1992
UrheberGetis & Ord (base statistic); robust extensions developed in subsequent spatial statistics literatureArthur Getis and J. Keith Ord
TypLocal spatial statisticLocal spatial statistic
Wegweisende QuelleGetis, A., & Ord, J. K. (1992). The analysis of spatial association by use of distance statistics. Geographical Analysis, 24(3), 189–206. DOI ↗Getis, A., & Ord, J. K. (1992). The analysis of spatial association by use of distance statistics. Geographical Analysis, 24(3), 189-206. DOI ↗
AliasnamenRobust Gi*, Robust local Gi star, outlier-resistant hot spot analysis, robust local spatial autocorrelation Gi*Getis-Ord Gi* statistic, spatial hot spot detection, cluster and outlier analysis, HSA
Verwandt55
ZusammenfassungThe 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*.Hot Spot Analysis uses the Getis-Ord Gi* local spatial statistic to identify geographic locations where high or low attribute values cluster together to a degree that is statistically significant. Each feature is evaluated in relation to its neighbours, producing a z-score that flags genuine spatial hot spots and cold spots against a background of random variation.
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ScholarGateMethoden vergleichen: Robust Getis-Ord Gi* · Hot Spot Analysis. Abgerufen am 2026-06-18 von https://scholargate.app/de/compare