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Робусна просторна аутокорелација×Prostorna autokorelacija×
OblastProstorna analizaProstorna analiza
PorodicaRegression modelRegression model
Godina nastanka1981–19951950
TvoracCliff & Ord; extended by Anselin and colleaguesP. A. P. Moran (global measure, 1950); Roy Geary (Geary's C, 1954); Luc Anselin (LISA, 1995)
TipSpatial dependence test (robust variant)Spatial statistic / exploratory spatial data analysis
Temeljni izvorAnselin, 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 ↗Moran, P. A. P. (1950). Notes on continuous stochastic phenomena. Biometrika, 37(1/2), 17–23. DOI ↗
Drugi nazivirobust Moran's I, robust spatial dependence test, outlier-resistant spatial autocorrelation, RSAspatial dependence, geographic autocorrelation, spatial clustering measure, SA
Srodne55
SažetakRobust 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.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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ScholarGateUporedite metode: Robust Spatial Autocorrelation · Spatial Autocorrelation. Preuzeto 2026-06-17 sa https://scholargate.app/sr/compare