手法を比較

	局所地理加重回帰 (GWR)	空間誤差モデル（SEM）
分野	空間分析	空間分析
系統	Regression model	Regression model
提唱年	1996	1988
提唱者	Brunsdon, Fotheringham & Charlton	Anselin
種類	Spatially varying coefficient regression	Spatial regression (spatially autocorrelated errors)
原典	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.
別名	GWR, geographically weighted regression, local spatial regression, spatially varying coefficient model	SEM, spatial error regression, spatial autoregressive error model, Uzamsal Hata Modeli (SEM / Spatial Error)
関連	5	5
概要	Local Geographically Weighted Regression (GWR) estimates a separate regression model at each location in the study area, allowing every coefficient to vary spatially. By weighting nearby observations more heavily than distant ones, GWR reveals how predictor-outcome relationships shift across geographic space rather than forcing a single global estimate on heterogeneous data.	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.