قارن الطرق

	تقدير الانحدار العاملي المربعات الصغرى الهيكلي	التقدير المربعات الصغرى المعممة (GLS)
المجال	الاقتصاد القياسي	الإحصاء
العائلة	Regression model	Regression model
سنة النشأة	1998 (structural break GLS formalization)	1935
صاحب الطريقة	Bai & Perron (1998); GLS framework by Aitken (1936)	Alexander Craig Aitken
النوع	Regression estimator	Linear estimator
المصدر التأسيسي	Bai, J., & Perron, P. (1998). Estimating and testing linear models with multiple structural changes. Econometrica, 66(1), 47–78.	Aitken, A. C. (1935). IV.—On least squares and linear combination of observations. Proceedings of the Royal Society of Edinburgh, 55, 42–48.
الأسماء البديلة	GLS with structural breaks, break-adjusted GLS, structural change GLS, regime-switching GLS	GLS, Aitken estimator, EGLS, feasible GLS
ذات صلة	6	3
الملخص	Structural 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.