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Regresión Espacial de Panel×Regresión Geográficamente Ponderada (GWR)×
CampoAnálisis espacialAnálisis espacial
FamiliaRegression modelRegression model
Año de origen1988-20142002
Autor originalAnselin, Elhorst, and colleagues in spatial econometricsFotheringham, Brunsdon & Charlton
TipoSpatial panel regressionLocal spatial regression
Fuente seminalElhorst, J. P. (2014). Spatial Econometrics: From Cross-Sectional Data to Spatial Panels. Springer. ISBN: 978-3642403408Fotheringham, A. S., Brunsdon, C., & Charlton, M. (2002). Geographically Weighted Regression: The Analysis of Spatially Varying Relationships. Wiley. ISBN: 978-0471496168
Aliasspatial panel model, panel spatial econometrics, spatial panel data regression, PSRGWR, local regression, spatially varying coefficient regression, Coğrafi Ağırlıklı Regresyon (GWR)
Relacionados65
ResumenPanel Spatial Regression extends standard panel data models by explicitly accounting for spatial dependence among cross-sectional units observed over time. It combines the temporal control of panel fixed or random effects with a spatial weights matrix that encodes geographic or network proximity, yielding unbiased and efficient estimates when observations are spatially correlated across units.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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  3. PUBLISHED

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ScholarGateComparar métodos: Panel Spatial Regression · Geographically Weighted Regression. Recuperado el 2026-06-17 de https://scholargate.app/es/compare