So sánh phương pháp

	Hồi quy phân vị mạnh mẽ	Hồi quy tuyến tính bội vững chắc
Lĩnh vực	Thống kê	Thống kê
Họ	Regression model	Regression model
Năm ra đời	1993–1997	1964–1980s
Người khởi xướng	Koenker & Bassett (1978); robust extensions by Machado (1993) and He (1997)	Peter J. Huber (M-estimators, 1964); extended by Rousseeuw, Yohai, and Maronna
Loại	Robust semiparametric regression	Robust linear regression
Công trình gốc	Koenker, R. (2005). Quantile Regression. Cambridge University Press. ISBN: 978-0521608275	Huber, P. J. (1964). Robust estimation of a location parameter. Annals of Mathematical Statistics, 35(1), 73–101.
Tên gọi khác	robust QR, outlier-resistant quantile regression, bounded-influence quantile regression, RQR	robust MLR, M-estimator regression, resistant multiple regression, robust OLS
Liên quan	6	6
Tóm tắt	Robust Quantile Regression estimates conditional quantiles of a response variable while simultaneously downweighting the influence of outliers. By combining the asymmetric loss function of standard quantile regression with bounded-influence or M-estimation weights, it provides reliable quantile estimates even when data contain extreme observations or heavy-tailed error distributions.	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.