Comparer des méthodes

	Régression Géographiquement Pondérée sur Données de Panel (Panel GWR)	Régression Pondérée Géographiquement (GWR)
Domaine	Analyse spatiale	Analyse spatiale
Famille	Regression model	Regression model
Année d'origine	2000s–2010s	2002
Auteur d'origine	Fotheringham, Brunsdon & Charlton (foundational GWR); panel extension developed in spatial econometrics literature	Fotheringham, Brunsdon & Charlton
Type	Local spatial regression with panel structure	Local spatial regression
Source fondatrice	Fotheringham, A. S., Brunsdon, C., & Charlton, M. (2002). Geographically Weighted Regression: The Analysis of Spatially Varying Relationships. Wiley. ISBN: 978-0471496168	Fotheringham, A. S., Brunsdon, C., & Charlton, M. (2002). Geographically Weighted Regression: The Analysis of Spatially Varying Relationships. Wiley. ISBN: 978-0471496168
Alias	Panel GWR, PGWR, spatiotemporal GWR, geographically weighted panel regression	GWR, local regression, spatially varying coefficient regression, Coğrafi Ağırlıklı Regresyon (GWR)
Apparentées	4	5
Résumé	Panel 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.	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.