So sánh phương pháp

	OLS mạnh mẽ (OLS với sai số chuẩn mạnh mẽ)	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	1980	1936 / 1980
Người khởi xướng	Halbert White	Aitken (GLS theory, 1936); White (robust covariance, 1980)
Loại	Linear regression with robust inference	Robust linear regression
Công trình gốc	White, H. (1980). A heteroskedasticity-consistent covariance matrix estimator and a direct test for heteroskedasticity. Econometrica, 48(4), 817–838.	Greene, W. H. (2012). Econometric Analysis (7th ed.). Pearson. Chapter 9: The Generalized Regression Model and Heteroscedasticity. ISBN: 978-0131395381
Tên gọi khác	HC robust regression, White robust OLS, sandwich estimator OLS, OLS with robust standard errors	robust generalized least squares, GLS with robust standard errors, heteroscedasticity-consistent GLS, HC-GLS
Liên quan	6	5
Tóm tắt	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.	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.