Methoden vergelijken

	Lokaal Ruimtelijk Lag Model	Lokaal Spatiaal Durbin Model
Vakgebied	Ruimtelijke analyse	Ruimtelijke analyse
Familie	Regression model	Regression model
Jaar van ontstaan	1988 (global); 2000s (local extensions)	2002–2009
Grondlegger	Anselin (global SLM, 1988); local extension via Fotheringham, Brunsdon & Charlton (GWR framework, 2002)	LeSage & Pace (SDM foundation); local adaptation via Fotheringham et al. GWR framework
Type	Spatially varying regression model	Spatially varying regression model
Oorspronkelijke bron	Anselin, L. (1988). Spatial Econometrics: Methods and Models. Kluwer Academic Publishers. ISBN: 978-9024737215	LeSage, J. P., & Pace, R. K. (2009). Introduction to Spatial Econometrics. CRC Press / Taylor & Francis. ISBN: 978-1420064247
Aliassen	local SLM, geographically weighted spatial lag model, GW-SLM, spatially varying lag model	local SDM, geographically weighted Spatial Durbin Model, GW-SDM, spatially varying Durbin model
Verwant	5	5
Samenvatting	The Local Spatial Lag Model extends the classical spatial lag model by allowing both the spatial autocorrelation parameter and the regression coefficients to vary across geographic locations. Instead of one global estimate of how neighboring outcomes influence each observation, the model fits location-specific parameters using kernel-weighted local estimation, revealing spatial heterogeneity in spatial dependence.	The Local Spatial Durbin Model (Local SDM) extends the global Spatial Durbin Model by allowing regression coefficients to vary across geographic space. It combines the SDM's ability to capture both spatial lag of the dependent variable and spatial lags of covariates with a geographically weighted estimation framework, producing location-specific direct and indirect spillover effects.