विधियों की तुलना करें

	स्थानीय स्थानिक प्रतिगमन (Local Spatial Regression)	स्पेशल एरर मॉडल (SEM)
क्षेत्र	स्थानिक विश्लेषण	स्थानिक विश्लेषण
परिवार	Regression model	Regression model
उद्भव वर्ष	1996	1988
प्रवर्तक	Brunsdon, Fotheringham & Charlton	Anselin
प्रकार	Spatially varying coefficient regression	Spatial regression (spatially autocorrelated errors)
मौलिक स्रोत	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.
उपनाम	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)
संबंधित	6	5
सारांश	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.