Σύγκριση μεθόδων

	Τοπικό Μοντέλο Χωρικού Durbin	Τοπική Χωρική Παλινδρόμηση
Πεδίο	Χωρική Ανάλυση	Χωρική Ανάλυση
Οικογένεια	Regression model	Regression model
Έτος προέλευσης	2002–2009	1996
Δημιουργός	LeSage & Pace (SDM foundation); local adaptation via Fotheringham et al. GWR framework	Brunsdon, Fotheringham & Charlton
Τύπος	Spatially varying regression model	Spatially varying coefficient regression
Θεμελιώδης πηγή	LeSage, J. P., & Pace, R. K. (2009). Introduction to Spatial Econometrics. CRC Press / Taylor & Francis. ISBN: 978-1420064247	Fotheringham, A. S., Brunsdon, C., & Charlton, M. (2002). Geographically Weighted Regression: The Analysis of Spatially Varying Relationships. Wiley. ISBN: 978-0471496168
Εναλλακτικές ονομασίες	local SDM, geographically weighted Spatial Durbin Model, GW-SDM, spatially varying Durbin model	locally weighted spatial regression, spatially varying coefficient model, local spatial model, place-based regression
Συναφείς	5	6
Σύνοψη	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.	Local Spatial Regression fits a separate regression model at each location in a study area, allowing regression coefficients to vary continuously across space. Rather than forcing one global slope on all observations, it reveals where and how the relationship between predictors and an outcome changes geographically — producing a map of coefficients rather than a single number.