विधियों की तुलना करें

	ग्लोबल स्पैशियल डर्बिन मॉडल (SDM)	स्पेशल एरर मॉडल (SEM)
क्षेत्र	स्थानिक विश्लेषण	स्थानिक विश्लेषण
परिवार	Regression model	Regression model
उद्भव वर्ष	2009	1988
प्रवर्तक	Durbin (1960); adapted to spatial context by LeSage & Pace (2009)	Anselin
प्रकार	Spatial regression model	Spatial regression (spatially autocorrelated errors)
मौलिक स्रोत	LeSage, J. P., & Pace, R. K. (2009). Introduction to Spatial Econometrics. CRC Press / Taylor & Francis. ISBN: 978-1420064247	Anselin, L. (1988). Spatial Econometrics: Methods and Models. Kluwer Academic.
उपनाम	SDM, Spatial Durbin Model, global SDM, spatially lagged X model with spatial lag	SEM, spatial error regression, spatial autoregressive error model, Uzamsal Hata Modeli (SEM / Spatial Error)
संबंधित	5	5
सारांश	The Global Spatial Durbin Model extends the spatial lag model by including not only a spatially lagged dependent variable but also spatially lagged independent variables (WX). A single set of global coefficients applies uniformly across all locations, making it suitable for estimating average spillover effects when spatial dependence is pervasive throughout the study region.	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.