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Panel Geographically Weighted Regression (Panel GWR)×Lokala geografski ponderisana regresija (GWR)×
OblastProstorna analizaProstorna analiza
PorodicaRegression modelRegression model
Godina nastanka2000s–2010s1996
TvoracFotheringham, Brunsdon & Charlton (foundational GWR); panel extension developed in spatial econometrics literatureBrunsdon, Fotheringham & Charlton
TipLocal spatial regression with panel structureSpatially varying coefficient regression
Temeljni izvorFotheringham, A. S., Brunsdon, C., & Charlton, M. (2002). Geographically Weighted Regression: The Analysis of Spatially Varying Relationships. Wiley. ISBN: 978-0471496168Fotheringham, A. S., Brunsdon, C., & Charlton, M. (2002). Geographically Weighted Regression: The Analysis of Spatially Varying Relationships. Wiley. ISBN: 978-0471496168
Drugi naziviPanel GWR, PGWR, spatiotemporal GWR, geographically weighted panel regressionGWR, geographically weighted regression, local spatial regression, spatially varying coefficient model
Srodne45
SažetakPanel Geographically Weighted Regression (Panel GWR) extends the standard GWR framework to panel data, allowing regression coefficients to vary both across geographic locations and over time. It captures spatially non-stationary relationships in longitudinal or repeated-measures spatial datasets, combining local spatial estimation with panel-data controls for unit-specific heterogeneity.Local 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.
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ScholarGateUporedite metode: Panel Geographically Weighted Regression · Local Geographically Weighted Regression. Preuzeto 2026-06-19 sa https://scholargate.app/sr/compare