New Robust Regression Model Beats Outliers, Promises More Accurate Predictions
The study compared different methods for analyzing data with outliers in a regression model. The OLS method showed big differences in results when outliers were present, while M-, MM-, and S-estimations were more stable. Among these, MM-estimation was the best, with a stable intercept and the smallest standard error.