Comparer des méthodes

	Panel Multiscale Geographically Weighted Regression	Régression Géographiquement Pondérée Multiscale (MGWR)
Domaine	Analyse spatiale	Analyse spatiale
Famille	Regression model	Regression model
Année d'origine	2017-2020	2017
Auteur d'origine	Fotheringham, Yang & Kang (MGWR base); panel extension developed in spatial econometrics literature	A. Stewart Fotheringham, Wei Yang, and Wei Kang
Type	Spatially varying coefficient panel regression	Local spatial regression
Source fondatrice	Fotheringham, A. S., Yang, W., & Kang, W. (2017). Multiscale Geographically Weighted Regression (MGWR). Annals of the American Association of Geographers, 107(6), 1247-1265.	Fotheringham, A. S., Yang, W., & Kang, W. (2017). Multiscale geographically weighted regression (MGWR). Annals of the American Association of Geographers, 107(6), 1247-1265.
Alias	Panel MGWR, MGWR panel data, multiscale GWR panel, panel spatially varying coefficient model	MGWR, multiscale GWR, multi-scale geographically weighted regression, variable-bandwidth GWR
Apparentées	5	5
Résumé	Panel MGWR extends Multiscale Geographically Weighted Regression to repeated-observations (panel) data, allowing each predictor to operate at its own spatial bandwidth while controlling for unit-specific or time-specific fixed effects. It is used when both spatial heterogeneity and temporal structure matter simultaneously.	Multiscale Geographically Weighted Regression (MGWR) is a local spatial regression framework that relaxes the single-bandwidth constraint of standard GWR by allowing each predictor to operate at its own spatial scale. Each coefficient surface is calibrated with its own bandwidth, enabling the model to distinguish drivers that vary slowly across space from those that vary sharply.