So sánh phương pháp

	Tổng bình phương nhỏ nhất tổng quát mạnh mẽ (Robust GLS)	OLS mạnh mẽ (OLS với sai số chuẩn mạnh mẽ)
Lĩnh vực	Kinh tế lượng	Kinh tế lượng
Họ	Regression model	Regression model
Năm ra đời	1936 / 1980	1980
Người khởi xướng	Aitken (GLS theory, 1936); White (robust covariance, 1980)	Halbert White
Loại	Robust linear regression	Linear regression with robust inference
Công trình gốc	Greene, W. H. (2012). Econometric Analysis (7th ed.). Pearson. Chapter 9: The Generalized Regression Model and Heteroscedasticity. ISBN: 978-0131395381	White, H. (1980). A heteroskedasticity-consistent covariance matrix estimator and a direct test for heteroskedasticity. Econometrica, 48(4), 817–838.
Tên gọi khác	robust generalized least squares, GLS with robust standard errors, heteroscedasticity-consistent GLS, HC-GLS	HC robust regression, White robust OLS, sandwich estimator OLS, OLS with robust standard errors
Liên quan	5	6
Tóm tắt	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.	Robust OLS applies ordinary least squares to estimate coefficients and then replaces the classical standard errors with heteroscedasticity-consistent (HC) standard errors — commonly called White standard errors. This leaves the point estimates unchanged while yielding valid t-statistics and confidence intervals even when the error variance is not constant across observations.