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Model lokalnog prostornog zaostajanja×Prostorna autokorelacija×
OblastProstorna analizaProstorna analiza
PorodicaRegression modelRegression model
Godina nastanka1988 (global); 2000s (local extensions)1950
TvoracAnselin (global SLM, 1988); local extension via Fotheringham, Brunsdon & Charlton (GWR framework, 2002)P. A. P. Moran (global measure, 1950); Roy Geary (Geary's C, 1954); Luc Anselin (LISA, 1995)
TipSpatially varying regression modelSpatial statistic / exploratory spatial data analysis
Temeljni izvorAnselin, L. (1988). Spatial Econometrics: Methods and Models. Kluwer Academic Publishers. ISBN: 978-9024737215Moran, P. A. P. (1950). Notes on continuous stochastic phenomena. Biometrika, 37(1/2), 17–23. DOI ↗
Drugi nazivilocal SLM, geographically weighted spatial lag model, GW-SLM, spatially varying lag modelspatial dependence, geographic autocorrelation, spatial clustering measure, SA
Srodne55
SažetakThe Local Spatial Lag Model extends the classical spatial lag model by allowing both the spatial autocorrelation parameter and the regression coefficients to vary across geographic locations. Instead of one global estimate of how neighboring outcomes influence each observation, the model fits location-specific parameters using kernel-weighted local estimation, revealing spatial heterogeneity in spatial dependence.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: Local Spatial Lag Model · Spatial Autocorrelation. Preuzeto 2026-06-17 sa https://scholargate.app/sr/compare