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Examine os métodos selecionados lado a lado; as linhas que diferem ficam destacadas.

Modelo de Lag Espacial Espaço-Temporal×Regressão Geograficamente Ponderada (GWR)×
ÁreaAnálise espacialAnálise espacial
FamíliaRegression modelRegression model
Ano de origem2003-20082002
Autor originalAnselin, Le Gallo & Jayet; ElhorstFotheringham, Brunsdon & Charlton
TipoSpatial panel regressionLocal spatial regression
Fonte seminalAnselin, L., Le Gallo, J., & Jayet, H. (2008). Spatial Panel Econometrics. In L. Matyas & P. Sevestre (Eds.), The Econometrics of Panel Data (pp. 625-660). Springer. link ↗Fotheringham, A. S., Brunsdon, C., & Charlton, M. (2002). Geographically Weighted Regression: The Analysis of Spatially Varying Relationships. Wiley. ISBN: 978-0471496168
Outros nomesST-SAR, spatial-temporal lag model, spatiotemporal autoregressive model, space-time SAR modelGWR, local regression, spatially varying coefficient regression, Coğrafi Ağırlıklı Regresyon (GWR)
Relacionados55
ResumoThe Space-Time Spatial Lag Model extends the classic spatial autoregressive (SAR) lag model to panel data, capturing how the outcome in each location at each time point is influenced by the contemporaneous outcomes of neighboring locations, while also controlling for unit-specific and time-specific fixed effects.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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ScholarGateComparar métodos: Space-Time Spatial Lag Model · Geographically Weighted Regression. Recuperado em 2026-06-18 de https://scholargate.app/pt/compare