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Sammenlign metoder

Gjennomgå de valgte metodene side om side; rader som avviker, er uthevet.

Romlig regresjon (romlig etterslep og romlige feilmodeller)×Seemingly Unrelated Regressions (SUR)×
FagfeltØkonometriØkonometri
FamilieRegression modelRegression model
Opprinnelsesår19881962
OpphavspersonLuc AnselinArnold Zellner
TypeSpatial regression (cross-sectional)System regression (multi-equation)
Opprinnelig kildeAnselin, L. (1988). Spatial Econometrics: Methods and Models. Kluwer Academic Publishers. DOI ↗Zellner, A. (1962). An Efficient Method of Estimating Seemingly Unrelated Regressions and Tests for Aggregation Bias. Journal of the American Statistical Association, 57(298), 348-368. DOI ↗
Aliasspatial econometrics, spatial lag model, spatial error model, SAR / SEMSUR, Zellner's SUR, seemingly unrelated regression equations, Görünürde İlişkisiz Regresyon (SUR)
Relaterte55
SammendragSpatial regression is a family of regression models that build geographic neighbourhood relationships directly into the model, introduced by Luc Anselin in his 1988 treatment of spatial econometrics. It splits into a spatial lag model, where spatial dependence sits in the dependent variable, and a spatial error model, where the dependence sits in the error term.Seemingly Unrelated Regressions, introduced by Arnold Zellner in 1962, is a system regression method that estimates several linear equations jointly when their error terms are correlated across equations. By exploiting that cross-equation correlation through generalized least squares, it is more efficient than estimating each equation separately by OLS.
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ScholarGateSammenlign metoder: Spatial Regression · Seemingly Unrelated Regression. Hentet 2026-06-18 fra https://scholargate.app/no/compare