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Lokální model prostorového zpoždění×Geograficky vážená regrese (GWR)×
OborProstorová analýzaProstorová analýza
RodinaRegression modelRegression model
Rok vzniku1988 (global); 2000s (local extensions)2002
TvůrceAnselin (global SLM, 1988); local extension via Fotheringham, Brunsdon & Charlton (GWR framework, 2002)Fotheringham, Brunsdon & Charlton
TypSpatially varying regression modelLocal spatial regression
Původní zdrojAnselin, L. (1988). Spatial Econometrics: Methods and Models. Kluwer Academic Publishers. ISBN: 978-9024737215Fotheringham, A. S., Brunsdon, C., & Charlton, M. (2002). Geographically Weighted Regression: The Analysis of Spatially Varying Relationships. Wiley. ISBN: 978-0471496168
Další názvylocal SLM, geographically weighted spatial lag model, GW-SLM, spatially varying lag modelGWR, local regression, spatially varying coefficient regression, Coğrafi Ağırlıklı Regresyon (GWR)
Příbuzné55
ShrnutíThe 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.Geographically 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.
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ScholarGatePorovnat metody: Local Spatial Lag Model · Geographically Weighted Regression. Získáno 2026-06-18 z https://scholargate.app/cs/compare