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GLS ze złamaniem strukturalnym×Metoda najmniejszych kwadratów uogólnionych (GLS)×
DziedzinaEkonometriaStatystyka
RodzinaRegression modelRegression model
Rok powstania1998 (structural break GLS formalization)1935
TwórcaBai & Perron (1998); GLS framework by Aitken (1936)Alexander Craig Aitken
TypRegression estimatorLinear estimator
Źródło pierwotneBai, J., & Perron, P. (1998). Estimating and testing linear models with multiple structural changes. Econometrica, 66(1), 47–78. DOI ↗Aitken, A. C. (1935). IV.—On least squares and linear combination of observations. Proceedings of the Royal Society of Edinburgh, 55, 42–48. DOI ↗
Inne nazwyGLS with structural breaks, break-adjusted GLS, structural change GLS, regime-switching GLSGLS, Aitken estimator, EGLS, feasible GLS
Pokrewne63
PodsumowanieStructural Break GLS combines Generalized Least Squares estimation with explicit allowance for regime shifts in the data-generating process. The method estimates separate coefficient vectors for each segment defined by detected break dates while correcting for non-spherical errors — heteroscedasticity or autocorrelation — that frequently accompany structural change, yielding consistent and efficient estimates across all regimes.Generalized Least Squares (GLS) is a linear regression estimator that extends ordinary least squares to handle situations where the error terms are correlated or have non-constant variance (heteroscedasticity). Introduced by Alexander Craig Aitken in 1935, GLS achieves the Best Linear Unbiased Estimator (BLUE) under a general error covariance structure by weighting observations according to their precision, providing a theoretical bridge between OLS and modern linear mixed models.
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ScholarGatePorównaj metody: Structural Break GLS · Generalized Least Squares. Pobrano 2026-06-18 z https://scholargate.app/pl/compare