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Paikallinen spatiaalisen viiveen malli×Paikallisesti painotettu regressio (GWR)×
TieteenalaSpatiaalianalyysiSpatiaalianalyysi
MenetelmäperheRegression modelRegression model
Syntyvuosi1988 (global); 2000s (local extensions)2002
KehittäjäAnselin (global SLM, 1988); local extension via Fotheringham, Brunsdon & Charlton (GWR framework, 2002)Fotheringham, Brunsdon & Charlton
TyyppiSpatially varying regression modelLocal spatial regression
AlkuperäislähdeAnselin, 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
Rinnakkaisnimetlocal SLM, geographically weighted spatial lag model, GW-SLM, spatially varying lag modelGWR, local regression, spatially varying coefficient regression, Coğrafi Ağırlıklı Regresyon (GWR)
Liittyvät55
TiivistelmäThe 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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ScholarGateVertaile menetelmiä: Local Spatial Lag Model · Geographically Weighted Regression. Haettu 2026-06-18 osoitteesta https://scholargate.app/fi/compare