Methoden vergelijken
Bekijk de geselecteerde methoden naast elkaar; rijen die verschillen zijn gemarkeerd.
| Ruimtelijk Foutenmodel (SEM)× | Ruimtelijk Durbin Model (SDM)× | |
|---|---|---|
| Vakgebied | Ruimtelijke analyse | Ruimtelijke analyse |
| Familie | Regression model | Regression model |
| Jaar van ontstaan≠ | 1988 | 2009 |
| Grondlegger≠ | Anselin | LeSage & Pace |
| Type≠ | Spatial regression (spatially autocorrelated errors) | Spatial regression model |
| Oorspronkelijke bron≠ | Anselin, L. (1988). Spatial Econometrics: Methods and Models. Kluwer Academic. DOI ↗ | LeSage, J. & Pace, R. K. (2009). Introduction to Spatial Econometrics. CRC Press. DOI ↗ |
| Aliassen≠ | SEM, spatial error regression, spatial autoregressive error model, Uzamsal Hata Modeli (SEM / Spatial Error) | SDM, spatial mixed model, uzamsal durbin modeli |
| Verwant | 5 | 5 |
| Samenvatting≠ | The Spatial Error Model, developed within Anselin's spatial econometrics framework (1988), is a regression model that assumes spatial dependence enters through the error term: the disturbances of neighbouring units are correlated. It is used when unobserved shared factors make the errors of nearby observations move together, and it is estimated by maximum likelihood or GMM rather than ordinary least squares. | 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 ↗ |
|
|