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Moran's I robuste×Indicateurs Locaux Robustes d'Association Spatiale (LISA Robust)×
DomaineAnalyse spatialeAnalyse spatiale
FamilleRegression modelRegression model
Année d'origine1990s–2000s1995–2000s
Auteur d'origineExtension of Moran (1950); robust adaptations developed in spatial statistics literatureAnselin (LISA, 1995); robust extensions by Assuncao & Reis and subsequent spatial statisticians
TypeRobust spatial autocorrelation statisticLocal spatial autocorrelation statistic (robust variant)
Source fondatriceAnselin, 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 ↗
Aliasoutlier-resistant Moran's I, robust spatial autocorrelation test, median-based Moran statistic, robust global spatial associationRobust LISA, outlier-resistant LISA, robust local spatial autocorrelation, LISA with robust weights
Apparentées66
RésuméRobust Moran's I is an outlier-resistant adaptation of the classic Moran's I spatial autocorrelation statistic. By replacing the standard mean-based standardization with resistant measures of center and spread, it detects genuine geographic clustering without being distorted by a small number of extreme values in the attribute of interest.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.
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  1. v1
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  3. PUBLISHED

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ScholarGateComparer des méthodes: Robust Moran's I · Robust Local Indicators of Spatial Association. Consulté le 2026-06-19 sur https://scholargate.app/fr/compare