Outlier Detection and Robust Variable Selection for Least Angle Regression KU Leuven
The problem of selecting a parsimonious subset of variables from a large number of predictors in a regression model is a topic of high importance. When the data contains vertical outliers and/or leverage points, outlier detection and variable selection are inseparable problems. Therefore a robust method that can simultaneously detect outliers and select variables is needed. An outlier detection and robust variable selection method is introduced ...