Methoden vergelijken
Bekijk de geselecteerde methoden naast elkaar; rijen die verschillen zijn gemarkeerd.
| Ruimtelijke Regressie voor Ruimte-Tijd× | Ruimtelijk Durbin Model (SDM)× | |
|---|---|---|
| Vakgebied | Ruimtelijke analyse | Ruimtelijke analyse |
| Familie | Regression model | Regression model |
| Jaar van ontstaan≠ | 1990s–2000s | 2009 |
| Grondlegger≠ | Anselin, LeSage, Pace and colleagues in spatial econometrics | LeSage & Pace |
| Type≠ | Spatio-temporal regression model | Spatial regression model |
| Oorspronkelijke bron≠ | LeSage, J. P., & Pace, R. K. (2009). Introduction to Spatial Econometrics. CRC Press / Taylor & Francis. ISBN: 978-1420064247 | LeSage, J. & Pace, R. K. (2009). Introduction to Spatial Econometrics. CRC Press. DOI ↗ |
| Aliassen≠ | spatio-temporal regression, spatial panel regression, space-time regression, ST spatial regression | SDM, spatial mixed model, uzamsal durbin modeli |
| Verwant≠ | 6 | 5 |
| Samenvatting≠ | Space-Time Spatial Regression extends classical spatial regression to panel settings where georeferenced units are observed across multiple time periods. By embedding a spatial weights matrix into a panel regression framework, it simultaneously controls for spatial dependence among cross-sectional units and temporal dynamics, yielding unbiased and consistent estimates in spatio-temporal data. | The Spatial Durbin Model is a general spatial regression model that includes a spatial lag of both the dependent variable (ρWy) and the explanatory variables (WXθ). Introduced as the recommended starting point by LeSage and Pace (2009), it nests the spatial autoregressive (SAR) and spatial error (SEM) models as special cases. |
| ScholarGateGegevensset ↗ |
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