Robust Regression and Outlier Detection

Robust regression and outlier detection are statistical techniques used to analyze data that may contain outliers or deviations from model assumptions. ### Robust Regression Robust regression refers to a set of techniques that provide more reliable and stable estimates of regression coefficients in the presence of outliers or violations of traditional regression assumptions (such as normality and homoscedasticity). Traditional regression methods, like Ordinary Least Squares (OLS), minimize the sum of squared residuals, which can be heavily influenced by outliers.