Regression model
MM-Estimation for Robust Regression
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.
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Sources
- Yohai, V. J. (1987). High Breakdown-Point and High Efficiency Robust Estimates for Regression. Annals of Statistics, 15(2), 642-656. DOI: 10.1214/aos/1176350366 ↗
- Koller, M. & Stahel, W. A. (2011). Sharpening Wald-type Inference in Robust Regression for Small Samples. Computational Statistics & Data Analysis, 55(8), 2504-2515. DOI: 10.1016/j.csda.2011.02.014 ↗