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| Robuster Geary's C× | Räumliche Autokorrelation× | |
|---|---|---|
| Fachgebiet | Räumliche Analyse | Räumliche Analyse |
| Familie | Regression model | Regression model |
| Entstehungsjahr≠ | 1954 (base); robust variants: 1990s–2000s | 1950 |
| Urheber≠ | Geary (1954); robust extensions by Anselin and spatial statisticians | P. A. P. Moran (global measure, 1950); Roy Geary (Geary's C, 1954); Luc Anselin (LISA, 1995) |
| Typ≠ | Robust spatial autocorrelation statistic | Spatial statistic / exploratory spatial data analysis |
| Wegweisende Quelle≠ | Geary, R. C. (1954). The contiguity ratio and statistical mapping. The Incorporated Statistician, 5(3), 115–145. DOI ↗ | Moran, P. A. P. (1950). Notes on continuous stochastic phenomena. Biometrika, 37(1/2), 17–23. DOI ↗ |
| Aliasnamen | robust Geary contiguity ratio, outlier-resistant Geary's C, robust spatial contiguity statistic, robust Geary C | spatial dependence, geographic autocorrelation, spatial clustering measure, SA |
| Verwandt≠ | 6 | 5 |
| Zusammenfassung≠ | Robust Geary's C adapts the classical Geary contiguity ratio — a measure of spatial autocorrelation based on pairwise squared differences between neighbouring locations — to resist distortion by spatial outliers and influential observations. It retains the local sensitivity of Geary's C while producing more reliable inferences when the spatial data contain extreme values or non-normal distributions. | Spatial autocorrelation quantifies the degree to which a variable's values at nearby locations resemble each other more (positive autocorrelation) or less (negative autocorrelation) than expected by chance. Global indices such as Moran's I summarise the pattern across the entire study area, while local variants reveal clusters and outliers at the level of individual observations. |
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