Bandingkan metode

	Model Kesalahan Spasial Global (SEM)	Autokorelasi Spasial
Bidang	Analisis Spasial	Analisis Spasial
Keluarga	Regression model	Regression model
Tahun asal	1988	1950
Pencetus	Luc Anselin	P. A. P. Moran (global measure, 1950); Roy Geary (Geary's C, 1954); Luc Anselin (LISA, 1995)
Tipe	Spatial regression model	Spatial statistic / exploratory spatial data analysis
Sumber perintis	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.
Alias	SEM, spatial error model, spatial error regression, global SEM	spatial dependence, geographic autocorrelation, spatial clustering measure, SA
Terkait	5	5
Ringkasan	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.