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Model Espacial Global de Durbin (SDM)×Regressió Ponderada Geogràficament (GWR)×
CampAnàlisi espacialAnàlisi espacial
FamíliaRegression modelRegression model
Any d'origen20092002
Autor originalDurbin (1960); adapted to spatial context by LeSage & Pace (2009)Fotheringham, Brunsdon & Charlton
TipusSpatial regression modelLocal spatial regression
Font seminalLeSage, J. P., & Pace, R. K. (2009). Introduction to Spatial Econometrics. CRC Press / Taylor & Francis. ISBN: 978-1420064247Fotheringham, A. S., Brunsdon, C., & Charlton, M. (2002). Geographically Weighted Regression: The Analysis of Spatially Varying Relationships. Wiley. ISBN: 978-0471496168
ÀliesSDM, Spatial Durbin Model, global SDM, spatially lagged X model with spatial lagGWR, local regression, spatially varying coefficient regression, Coğrafi Ağırlıklı Regresyon (GWR)
Relacionats55
ResumThe Global Spatial Durbin Model extends the spatial lag model by including not only a spatially lagged dependent variable but also spatially lagged independent variables (WX). A single set of global coefficients applies uniformly across all locations, making it suitable for estimating average spillover effects when spatial dependence is pervasive throughout the study region.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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ScholarGateCompara mètodes: Global Spatial Durbin Model · Geographically Weighted Regression. Recuperat el 2026-06-18 de https://scholargate.app/ca/compare