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Lokala geografski ponderisana regresija (GWR)×Model prostorne greške (SEM)×
OblastProstorna analizaProstorna analiza
PorodicaRegression modelRegression model
Godina nastanka19961988
TvoracBrunsdon, Fotheringham & CharltonAnselin
TipSpatially varying coefficient regressionSpatial regression (spatially autocorrelated errors)
Temeljni izvorFotheringham, A. S., Brunsdon, C., & Charlton, M. (2002). Geographically Weighted Regression: The Analysis of Spatially Varying Relationships. Wiley. ISBN: 978-0471496168Anselin, L. (1988). Spatial Econometrics: Methods and Models. Kluwer Academic. DOI ↗
Drugi naziviGWR, geographically weighted regression, local spatial regression, spatially varying coefficient modelSEM, spatial error regression, spatial autoregressive error model, Uzamsal Hata Modeli (SEM / Spatial Error)
Srodne55
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.The Spatial Error Model, developed within Anselin's spatial econometrics framework (1988), is a regression model that assumes spatial dependence enters through the error term: the disturbances of neighbouring units are correlated. It is used when unobserved shared factors make the errors of nearby observations move together, and it is estimated by maximum likelihood or GMM rather than ordinary least squares.
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ScholarGateUporedite metode: Local Geographically Weighted Regression · Spatial Error Model. Preuzeto 2026-06-17 sa https://scholargate.app/sr/compare