So sánh phương pháp

	Hồi quy phân vị mạnh mẽ	Hồi quy Bình phương Tối thiểu Thông thường (OLS)
Lĩnh vực	Thống kê	Kinh tế lượng
Họ	Regression model	Regression model
Năm ra đời	1993–1997	2019
Người khởi xướng	Koenker & Bassett (1978); robust extensions by Machado (1993) and He (1997)	Wooldridge (textbook treatment); classical least squares
Loại	Robust semiparametric regression	Linear regression
Công trình gốc	Koenker, R. (2005). Quantile Regression. Cambridge University Press. ISBN: 978-0521608275	Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860
Tên gọi khác	robust QR, outlier-resistant quantile regression, bounded-influence quantile regression, RQR	ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu
Liên quan	6	5
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.	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).