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Regresi Berwajaran Geografi Panel (Panel GWR)×Model Ralat Spatial Panel×
BidangAnalisis ReruangAnalisis Reruang
KeluargaRegression modelRegression model
Tahun asal2000s–2010s1988 / 2003
PengasasFotheringham, Brunsdon & Charlton (foundational GWR); panel extension developed in spatial econometrics literatureAnselin (1988); extended to panels by Elhorst (2003, 2014)
JenisLocal spatial regression with panel structureSpatial econometric panel model
Sumber perintisFotheringham, A. S., Brunsdon, C., & Charlton, M. (2002). Geographically Weighted Regression: The Analysis of Spatially Varying Relationships. Wiley. ISBN: 978-0471496168Elhorst, J. P. (2014). Spatial Econometrics: From Cross-Sectional Data to Spatial Panels. Springer. ISBN: 978-3642403408
AliasPanel GWR, PGWR, spatiotemporal GWR, geographically weighted panel regressionpanel SEM, spatial error panel model, panel spatial autocorrelation error model, SEM panel
Berkaitan45
RingkasanPanel 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.The Panel Spatial Error Model (panel SEM) extends the classical spatial error model to panel data, allowing spatial dependence to enter through the error term across cross-sectional units over multiple time periods. It accounts for spatially correlated omitted variables without imposing a substantive spatial spillover in the outcome itself.
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ScholarGateBandingkan kaedah: Panel Geographically Weighted Regression · Panel Spatial Error Model. Dicapai 2026-06-17 daripada https://scholargate.app/ms/compare