Σύγκριση μεθόδων

	Τοπική Χωρική Παλινδρόμηση	Μοντέλο Χωρικού Σφάλματος (SEM)
Πεδίο	Χωρική Ανάλυση	Χωρική Ανάλυση
Οικογένεια	Regression model	Regression model
Έτος προέλευσης	1996	1988
Δημιουργός	Brunsdon, Fotheringham & Charlton	Anselin
Τύπος	Spatially varying coefficient regression	Spatial regression (spatially autocorrelated errors)
Θεμελιώδης πηγή	Fotheringham, A. S., Brunsdon, C., & Charlton, M. (2002). Geographically Weighted Regression: The Analysis of Spatially Varying Relationships. Wiley. ISBN: 978-0471496168	Anselin, L. (1988). Spatial Econometrics: Methods and Models. Kluwer Academic.
Εναλλακτικές ονομασίες	locally weighted spatial regression, spatially varying coefficient model, local spatial model, place-based regression	SEM, spatial error regression, spatial autoregressive error model, Uzamsal Hata Modeli (SEM / Spatial Error)
Συναφείς	6	5
Σύνοψη	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.	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.