So sánh phương pháp

	Ước lượng MM cho hồi quy vững mạnh	Hồi quy RANSAC
Lĩnh vực	Thống kê	Thống kê
Họ	Regression model	Regression model
Năm ra đời	1987	1981
Người khởi xướng	Victor J. Yohai	Fischler & Bolles
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.	Fischler, M. A. & Bolles, R. C. (1981). Random Sample Consensus: A Paradigm for Model Fitting with Applications to Image Analysis and Automated Cartography. Communications of the ACM, 24(6), 381-395.
Tên gọi khác	MM-estimation, MM robust regression, high-breakdown high-efficiency estimator, MM-Tahmin Edici	random sample consensus, RANSAC, robust regression, RANSAC Regresyonu
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.	RANSAC Regression is a robust linear regression method introduced by Fischler and Bolles in 1981 that fits a model to the inlier points of a dataset while automatically excluding outliers. Instead of fitting all the data at once, it repeatedly samples small subsets, fits a candidate model, and keeps the model that wins the largest consensus of agreeing points.