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Robustné vážené najmenšie štvorce (Robustné WLS)×Vážený spôsob najmenších štvorcov (WLS)×
OdborEkonometriaŠtatistika
RodinaRegression modelRegression model
Rok vzniku1964/19811935
TvorcaHuber, P. J.Alexander Craig Aitken
TypRobust weighted regressionWeighted linear estimator
Pôvodný zdrojHuber, P. J. (1981). Robust Statistics. Wiley. ISBN: 978-0471418054Aitken, A. C. (1935). IV.—On least squares and linear combination of observations. Proceedings of the Royal Society of Edinburgh, 55, 42–48. DOI ↗
Ďalšie názvyrobust weighted least squares, RWLS, heteroscedasticity-robust WLS, outlier-robust weighted regressionWLS, weighted regression, heteroscedasticity-corrected OLS, variance-weighted least squares
Príbuzné53
ZhrnutieRobust 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.Weighted Least Squares is a generalization of Ordinary Least Squares (OLS) regression that assigns each observation a weight inversely proportional to its error variance, thereby down-weighting high-variance data points and up-weighting precise ones. Introduced in its general matrix form by Alexander Craig Aitken in 1935, WLS is the canonical remedy when heteroscedasticity is present and the error variance structure is known or can be reliably estimated.
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ScholarGatePorovnať metódy: Robust WLS · Weighted Least Squares. Získané 2026-06-18 z https://scholargate.app/sk/compare