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Robust viktad minsta kvadrat-metod (Robust WLS)×Robust Generaliserad Minsta Kvadrat (Robust GLS)×
ÄmnesområdeEkonometriEkonometri
FamiljRegression modelRegression model
Ursprungsår1964/19811936 / 1980
UpphovspersonHuber, P. J.Aitken (GLS theory, 1936); White (robust covariance, 1980)
TypRobust weighted regressionRobust linear regression
UrsprungskällaHuber, P. J. (1981). Robust Statistics. Wiley. ISBN: 978-0471418054Greene, W. H. (2012). Econometric Analysis (7th ed.). Pearson. Chapter 9: The Generalized Regression Model and Heteroscedasticity. ISBN: 978-0131395381
Aliasrobust weighted least squares, RWLS, heteroscedasticity-robust WLS, outlier-robust weighted regressionrobust generalized least squares, GLS with robust standard errors, heteroscedasticity-consistent GLS, HC-GLS
Närliggande55
SammanfattningRobust WLS combines weighted least squares — which corrects for known or estimated heteroscedasticity — with robust M-estimation that down-weights influential outliers. The result is a regression estimator that is simultaneously efficient under non-constant error variance and resistant to observations that would otherwise distort coefficient estimates.Robust GLS extends classical Generalized Least Squares by pairing GLS coefficient estimation with heteroscedasticity- and autocorrelation-consistent (HAC) standard errors, or by using M-estimation within the GLS framework. It corrects for non-spherical errors — heteroscedasticity, autocorrelation, or both — while also guarding inference against misspecification of the error covariance structure.
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ScholarGateJämför metoder: Robust WLS · Robust GLS. Hämtad 2026-06-17 från https://scholargate.app/sv/compare