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Lokálna geograficky vážená regresia (GWR)×Model priestorového oneskorenia (SAR / priestorovo autoregresný)×
OdborPriestorová analýzaPriestorová analýza
RodinaRegression modelRegression model
Rok vzniku19961988
TvorcaBrunsdon, Fotheringham & CharltonAnselin (textbook formalisation); LeSage & Pace
TypSpatially varying coefficient regressionSpatial autoregressive regression
Pôvodný zdrojFotheringham, 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 ↗
Ďalšie názvyGWR, geographically weighted regression, local spatial regression, spatially varying coefficient modelSAR model, spatial autoregressive model, spatial lag, Uzamsal Gecikme Modeli (SAR / Spatial Lag)
Príbuzné55
ZhrnutieLocal 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 Lag Model is an autoregressive regression that assumes spatial dependence in the dependent variable itself: the outcome values of neighbouring units enter the model as an explanatory term (ρWy). It was formalised in Anselin's Spatial Econometrics (1988) and developed further by LeSage and Pace (2009), and it decomposes spillover effects into direct, indirect, and total impacts.
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ScholarGatePorovnať metódy: Local Geographically Weighted Regression · Spatial Lag Model. Získané 2026-06-18 z https://scholargate.app/sk/compare