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Geographically Weighted Regression (GWR)×LISA×
OblastProstorna analizaProstorna analiza
PorodicaRegression modelRegression model
Godina nastanka20021995
TvoracFotheringham, Brunsdon & CharltonLuc Anselin
TipLocal spatial regressionLocal spatial autocorrelation statistic
Temeljni izvorFotheringham, A. S., Brunsdon, C., & Charlton, M. (2002). Geographically Weighted Regression: The Analysis of Spatially Varying Relationships. Wiley. ISBN: 978-0471496168Anselin, L. (1995). Local Indicators of Spatial Association — LISA. Geographical Analysis, 27(2), 93–115. DOI ↗
Drugi naziviGWR, local regression, spatially varying coefficient regression, Coğrafi Ağırlıklı Regresyon (GWR)local Moran's I, local spatial autocorrelation, LISA cluster analysis, LISA — Yerel Uzamsal Otokorelasyon (Local Moran's I)
Srodne55
SažetakGeographically Weighted Regression is a local regression method, introduced by Fotheringham, Brunsdon and Charlton (2002), that allows the regression coefficients to vary across space. Instead of one global equation, it fits a separate set of coefficients at every location, capturing spatial heterogeneity in the relationships.LISA, introduced by Luc Anselin in 1995, is a local statistic that computes spatial autocorrelation separately for every observation rather than for the map as a whole. It pinpoints where high or low values cluster and where spatial outliers sit, decomposing the global Moran's I into a contribution from each location.
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ScholarGateUporedite metode: Geographically Weighted Regression · LISA. Preuzeto 2026-06-18 sa https://scholargate.app/sr/compare