So sánh phương pháp

	Ước lượng MM cho hồi quy vững mạnh	Hồi quy Bình phương Nhỏ nhất Cắt tỉa (Least Trimmed Squares - LTS)
Lĩnh vực	Thống kê	Thống kê
Họ	Regression model	Regression model
Năm ra đời	1987	1984
Người khởi xướng	Victor J. Yohai	Peter J. Rousseeuw
Loại	Robust linear regression	Robust linear regression
Công trình gốc	Yohai, V. J. (1987). High Breakdown-Point and High Efficiency Robust Estimates for Regression. Annals of Statistics, 15(2), 642-656.	Rousseeuw, P. J. (1984). Least Median of Squares Regression. Journal of the American Statistical Association, 79(388), 871-880.
Tên gọi khác	MM-estimation, MM robust regression, high-breakdown high-efficiency estimator, MM-Tahmin Edici	LTS, least trimmed squares regression, trimmed least squares, robust regression
Liên quan	5	5
Tóm tắt	The MM-estimator is a robust linear regression method introduced by Victor J. Yohai in 1987. It combines the high breakdown point of an S-estimator with the high efficiency of an M-estimator, so it resists outliers strongly while still using the data efficiently when errors are well-behaved.	Least Trimmed Squares is a robust linear regression method introduced by Peter J. Rousseeuw in 1984. Instead of fitting all residuals, it estimates the coefficients by minimising the sum of only the h smallest squared residuals, which gives it a breakdown point of up to 50% and reliable estimates on data heavily contaminated by outliers.