So sánh phương pháp

	Hồi quy tuyến tính bội vững chắc	Hồi quy mạnh mẽ
Lĩnh vực	Thống kê	Thống kê
Họ	Regression model	Regression model
Năm ra đời	1964–1980s	1964
Người khởi xướng	Peter J. Huber (M-estimators, 1964); extended by Rousseeuw, Yohai, and Maronna	Peter J. Huber (M-estimation, 1964); Frank Hampel (influence function, 1974)
Loại	Robust linear regression	Regression with outlier resistance
Công trình gốc	Huber, P. J. (1964). Robust estimation of a location parameter. Annals of Mathematical Statistics, 35(1), 73–101.	Huber, P. J. (1964). Robust estimation of a location parameter. The Annals of Mathematical Statistics, 35(1), 73–101.
Tên gọi khác	robust MLR, M-estimator regression, resistant multiple regression, robust OLS	M-estimation regression, robust linear regression, outlier-resistant regression, MM-estimation
Liên quan	6	6
Tóm tắt	Robust multiple linear regression estimates the linear relationship between a continuous outcome and several predictors while being resistant to outliers and violations of the normality assumption. Instead of minimising the sum of squared residuals, it uses a bounded loss function — most commonly Huber's or Tukey's bisquare — so that extreme observations receive limited influence on the estimated coefficients.	Robust regression estimates the linear relationship between a continuous outcome and predictors while sharply reducing the influence of outliers and leverage points. Unlike OLS, which is highly sensitive to extreme observations, robust methods assign down-weighted influence to atypical data points, producing coefficient estimates that remain stable even when a fraction of the data is contaminated or non-normally distributed.