Comparar métodos

	Regressão Geograficamente Ponderada em Painel (Panel GWR)	Regressão Geograficamente Ponderada Local (GWR)
Área	Análise espacial	Análise espacial
Família	Regression model	Regression model
Ano de origem	2000s–2010s	1996
Autor original	Fotheringham, Brunsdon & Charlton (foundational GWR); panel extension developed in spatial econometrics literature	Brunsdon, Fotheringham & Charlton
Tipo	Local spatial regression with panel structure	Spatially varying coefficient regression
Fonte seminal	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
Outros nomes	Panel GWR, PGWR, spatiotemporal GWR, geographically weighted panel regression	GWR, geographically weighted regression, local spatial regression, spatially varying coefficient model
Relacionados	4	5
Resumo	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.	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.