So sánh phương pháp

	Hồi quy Bình phương Tối thiểu Thông thường (OLS)	Tổng bình phương nhỏ nhất tổng quát mạnh mẽ (Robust GLS)
Lĩnh vực	Kinh tế lượng	Kinh tế lượng
Họ	Regression model	Regression model
Năm ra đời	2019	1936 / 1980
Người khởi xướng	Wooldridge (textbook treatment); classical least squares	Aitken (GLS theory, 1936); White (robust covariance, 1980)
Loại	Linear regression	Robust linear regression
Công trình gốc	Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860	Greene, W. H. (2012). Econometric Analysis (7th ed.). Pearson. Chapter 9: The Generalized Regression Model and Heteroscedasticity. ISBN: 978-0131395381
Tên gọi khác	ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu	robust generalized least squares, GLS with robust standard errors, heteroscedasticity-consistent GLS, HC-GLS
Liên quan	5	5
Tóm tắt	Ordinary Least Squares is the classical linear regression method that explains a continuous outcome as a linear combination of predictors. It estimates the coefficients by minimising the sum of squared residuals, and under the Gauss-Markov assumptions these estimates are the best linear unbiased estimator (BLUE).	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.