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| Regression Ponderata Geograficamente su Dati Panel (Panel GWR)× | Regressione Geograficamente Ponderata (GWR)× | |
|---|---|---|
| Campo | Analisi spaziale | Analisi spaziale |
| Famiglia | Regression model | Regression model |
| Anno di origine≠ | 2000s–2010s | 2002 |
| Ideatore≠ | Fotheringham, Brunsdon & Charlton (foundational GWR); panel extension developed in spatial econometrics literature | Fotheringham, Brunsdon & Charlton |
| Tipo≠ | Local spatial regression with panel structure | Local spatial regression |
| Fonte seminale | 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 |
| Alias | Panel GWR, PGWR, spatiotemporal GWR, geographically weighted panel regression | GWR, local regression, spatially varying coefficient regression, Coğrafi Ağırlıklı Regresyon (GWR) |
| Correlati≠ | 4 | 5 |
| Sintesi≠ | 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. | 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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