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Lokalna geografski ponderirana regresija (GWR)×Lokalna prostorna autokorelacija×
PodručjeProstorna analizaProstorna analiza
ObiteljRegression modelRegression model
Godina nastanka19961995
TvoracBrunsdon, Fotheringham & CharltonLuc Anselin
VrstaSpatially varying coefficient regressionSpatial association analysis
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, geographically weighted regression, local spatial regression, spatially varying coefficient modellocal spatial association, local SA, LISA methods, local spatial clustering
Srodne56
SažetakLocal Geographically Weighted Regression (GWR) estimates a separate regression model at each location in the study area, allowing every coefficient to vary spatially. By weighting nearby observations more heavily than distant ones, GWR reveals how predictor-outcome relationships shift across geographic space rather than forcing a single global estimate on heterogeneous data.Local Spatial Autocorrelation methods decompose global spatial clustering into location-specific statistics, revealing where in a study area significant clustering or dispersion occurs. Each observation receives its own association score and significance value, enabling the detection of spatial hot spots, cold spots, and spatial outliers rather than reporting a single summary statistic.
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ScholarGateUsporedite metode: Local Geographically Weighted Regression · Local Spatial Autocorrelation. Preuzeto 2026-06-19 s https://scholargate.app/hr/compare