Comparer des méthodes
Examinez les méthodes sélectionnées côte à côte ; les lignes qui diffèrent sont mises en évidence.
| Modèle autorégressif spatial à décalage espace-temps× | Régression Pondérée Géographiquement (GWR)× | |
|---|---|---|
| Domaine | Analyse spatiale | Analyse spatiale |
| Famille | Regression model | Regression model |
| Année d'origine≠ | 2003-2008 | 2002 |
| Auteur d'origine≠ | Anselin, Le Gallo & Jayet; Elhorst | Fotheringham, Brunsdon & Charlton |
| Type≠ | Spatial panel regression | Local spatial regression |
| Source fondatrice≠ | Anselin, 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 |
| Alias | ST-SAR, spatial-temporal lag model, spatiotemporal autoregressive model, space-time SAR model | GWR, local regression, spatially varying coefficient regression, Coğrafi Ağırlıklı Regresyon (GWR) |
| Apparentées | 5 | 5 |
| Résumé≠ | The 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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