Compară metode

	Modelul Global al Erorilor Spațiale (SEM)	Autocorelația spațială
Domeniu	Analiză spațială	Analiză spațială
Familie	Regression model	Regression model
Anul apariției	1988	1950
Autorul original	Luc Anselin	P. A. P. Moran (global measure, 1950); Roy Geary (Geary's C, 1954); Luc Anselin (LISA, 1995)
Tip	Spatial regression model	Spatial statistic / exploratory spatial data analysis
Sursa seminală	Anselin, L. (1988). Spatial Econometrics: Methods and Models. Kluwer Academic Publishers. ISBN: 978-9024737322	Moran, P. A. P. (1950). Notes on continuous stochastic phenomena. Biometrika, 37(1/2), 17–23.
Denumiri alternative	SEM, spatial error model, spatial error regression, global SEM	spatial dependence, geographic autocorrelation, spatial clustering measure, SA
Înrudite	5	5
Rezumat	The Global Spatial Error Model (SEM) is a spatial regression technique that accounts for spatially autocorrelated error terms using a single, globally constant spatial parameter. It separates genuine predictor effects from spatial nuisance dependence in the residuals, yielding unbiased and efficient coefficient estimates when spatial error correlation is present across all observations.	Spatial autocorrelation quantifies the degree to which a variable's values at nearby locations resemble each other more (positive autocorrelation) or less (negative autocorrelation) than expected by chance. Global indices such as Moran's I summarise the pattern across the entire study area, while local variants reveal clusters and outliers at the level of individual observations.