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Robusni lokalni indikatori prostorne asocijacije (Robust LISA)×Робусна просторна аутокорелација×
OblastProstorna analizaProstorna analiza
PorodicaRegression modelRegression model
Godina nastanka1995–2000s1981–1995
TvoracAnselin (LISA, 1995); robust extensions by Assuncao & Reis and subsequent spatial statisticiansCliff & Ord; extended by Anselin and colleagues
TipLocal spatial autocorrelation statistic (robust variant)Spatial dependence test (robust variant)
Temeljni izvorAnselin, L. (1995). Local indicators of spatial association—LISA. Geographical Analysis, 27(2), 93–115. DOI ↗Anselin, L., & Florax, R. J. G. M. (1995). Small sample properties of tests for spatial dependence in regression models: some further results. In Anselin, L. & Florax, R. J. G. M. (Eds.), New Directions in Spatial Econometrics. Springer, Berlin. link ↗
Drugi naziviRobust LISA, outlier-resistant LISA, robust local spatial autocorrelation, LISA with robust weightsrobust Moran's I, robust spatial dependence test, outlier-resistant spatial autocorrelation, RSA
Srodne65
SažetakRobust 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.Robust spatial autocorrelation methods measure the degree to which nearby geographic units share similar values, while explicitly controlling for the distorting influence of spatial outliers and extreme observations. They extend classical statistics such as Moran's I by down-weighting or trimming observations that would otherwise inflate or deflate the autocorrelation signal.
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ScholarGateUporedite metode: Robust Local Indicators of Spatial Association · Robust Spatial Autocorrelation. Preuzeto 2026-06-19 sa https://scholargate.app/sr/compare