Salīdzināt metodes

	Telpiskās nobīdes modelis (SAR / Telpiskais autoregresīvais)	Telpiskais kļūdu modelis (SEM)
Nozare	Telpiskā analīze	Telpiskā analīze
Saime	Regression model	Regression model
Izcelsmes gads	1988	1988
Autors	Anselin (textbook formalisation); LeSage & Pace	Anselin
Tips	Spatial autoregressive regression	Spatial regression (spatially autocorrelated errors)
Pirmavots	Anselin, L. (1988). Spatial Econometrics: Methods and Models. Kluwer Academic.	Anselin, L. (1988). Spatial Econometrics: Methods and Models. Kluwer Academic.
Citi nosaukumi	SAR model, spatial autoregressive model, spatial lag, Uzamsal Gecikme Modeli (SAR / Spatial Lag)	SEM, spatial error regression, spatial autoregressive error model, Uzamsal Hata Modeli (SEM / Spatial Error)
Saistītās	5	5
Kopsavilkums	The Spatial Lag Model is an autoregressive regression that assumes spatial dependence in the dependent variable itself: the outcome values of neighbouring units enter the model as an explanatory term (ρWy). It was formalised in Anselin's Spatial Econometrics (1988) and developed further by LeSage and Pace (2009), and it decomposes spillover effects into direct, indirect, and total impacts.	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.