Salīdzināt metodes

	Telpiskais kļūdu modelis (SEM)	Telpiskās nobīdes modelis (SAR / Telpiskais autoregresīvais)
Nozare	Telpiskā analīze	Telpiskā analīze
Saime	Regression model	Regression model
Izcelsmes gads	1988	1988
Autors	Anselin	Anselin (textbook formalisation); LeSage & Pace
Tips	Spatial regression (spatially autocorrelated errors)	Spatial autoregressive regression
Pirmavots	Anselin, L. (1988). Spatial Econometrics: Methods and Models. Kluwer Academic.	Anselin, L. (1988). Spatial Econometrics: Methods and Models. Kluwer Academic.
Citi nosaukumi	SEM, spatial error regression, spatial autoregressive error model, Uzamsal Hata Modeli (SEM / Spatial Error)	SAR model, spatial autoregressive model, spatial lag, Uzamsal Gecikme Modeli (SAR / Spatial Lag)
Saistītās	5	5
Kopsavilkums	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.	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.