Linganisha mbinu

	Local Spatial Durbin Model	Regressioni Angani za Kienyeji
Nyanja	Uchanganuzi wa Kimaeneo	Uchanganuzi wa Kimaeneo
Familia	Regression model	Regression model
Mwaka wa asili	2002–2009	1996
Mwanzilishi	LeSage & Pace (SDM foundation); local adaptation via Fotheringham et al. GWR framework	Brunsdon, Fotheringham & Charlton
Aina	Spatially varying regression model	Spatially varying coefficient regression
Chanzo asilia	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
Majina mbadala	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
Zinazohusiana	5	6
Muhtasari	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.