So sánh phương pháp

	Hồi quy Huber	Hồi quy Quantile
Lĩnh vực	Thống kê	Kinh tế lượng
Họ	Regression model	Regression model
Năm ra đời	1964	1978
Người khởi xướng	Peter J. Huber	Koenker & Bassett
Loại	Robust linear regression (M-estimation)	Conditional quantile regression
Công trình gốc	Huber, P. J. (1964). Robust Estimation of a Location Parameter. Annals of Mathematical Statistics, 35(1), 73-101.	Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50.
Tên gọi khác	Huber M-estimator, Huber loss regression, robust regression, Huber Regresyonu	conditional quantile regression, regression quantiles, Kantil Regresyon
Liên quan	5	5
Tóm tắt	Huber regression is a robust linear regression method, introduced by Peter J. Huber in 1964, that resists the influence of outliers by treating small and large residuals differently. It applies a squared (OLS-like) loss to small residuals and a milder absolute-value loss to large ones, so extreme observations cannot dominate the fit.	Quantile regression models conditional quantiles of an outcome - the median, the 25th or 75th percentile, and so on - rather than the conditional mean that OLS targets. Introduced by Koenker and Bassett in 1978, it reveals how predictors act across the whole distribution, including its tails.