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| Indicateurs Locaux Robustes d'Association Spatiale (LISA Robust)× | Indicateur local d'association spatiale (LISA) C de Geary local× | |
|---|---|---|
| Domaine | Analyse spatiale | Analyse spatiale |
| Famille | Regression model | Regression model |
| Année d'origine≠ | 1995–2000s | 1995 |
| Auteur d'origine≠ | Anselin (LISA, 1995); robust extensions by Assuncao & Reis and subsequent spatial statisticians | Luc Anselin |
| Type≠ | Local spatial autocorrelation statistic (robust variant) | Local spatial statistic |
| Source fondatrice≠ | Anselin, L. (1995). Local indicators of spatial association—LISA. Geographical Analysis, 27(2), 93–115. DOI ↗ | Anselin, L. (1995). Local indicators of spatial association — LISA. Geographical Analysis, 27(2), 93–115. DOI ↗ |
| Alias | Robust LISA, outlier-resistant LISA, robust local spatial autocorrelation, LISA with robust weights | Local Geary, local spatial contiguity ratio, LISA Geary, local c statistic |
| Apparentées | 6 | 6 |
| Résumé≠ | Robust Local Indicators of Spatial Association extend Anselin's LISA framework to handle outliers, extreme values, and spatially heterogeneous populations. By applying outlier-resistant adjustments to the spatial weights or the standardised values, Robust LISA identifies statistically significant local clusters and spatial outliers without the distortions caused by highly influential observations. | Local Geary's C is a local indicator of spatial association (LISA) that measures, for each location, how dissimilar its value is from its immediate neighbours. Unlike Local Moran's I, which detects clustering of similar values, Local Geary's C focuses on squared value differences and is especially sensitive to local spatial outliers and local heterogeneity. |
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