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Prostorno-vremenska prostorna regresija×Geographically Weighted Regression (GWR)×
OblastProstorna analizaProstorna analiza
PorodicaRegression modelRegression model
Godina nastanka1990s–2000s2002
TvoracAnselin, LeSage, Pace and colleagues in spatial econometricsFotheringham, Brunsdon & Charlton
TipSpatio-temporal regression modelLocal spatial regression
Temeljni izvorLeSage, J. P., & Pace, R. K. (2009). Introduction to Spatial Econometrics. CRC Press / Taylor & Francis. ISBN: 978-1420064247Fotheringham, A. S., Brunsdon, C., & Charlton, M. (2002). Geographically Weighted Regression: The Analysis of Spatially Varying Relationships. Wiley. ISBN: 978-0471496168
Drugi nazivispatio-temporal regression, spatial panel regression, space-time regression, ST spatial regressionGWR, local regression, spatially varying coefficient regression, Coğrafi Ağırlıklı Regresyon (GWR)
Srodne65
SažetakSpace-Time Spatial Regression extends classical spatial regression to panel settings where georeferenced units are observed across multiple time periods. By embedding a spatial weights matrix into a panel regression framework, it simultaneously controls for spatial dependence among cross-sectional units and temporal dynamics, yielding unbiased and consistent estimates in spatio-temporal data.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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ScholarGateUporedite metode: Space-Time Spatial Regression · Geographically Weighted Regression. Preuzeto 2026-06-18 sa https://scholargate.app/sr/compare