Discussion of "Least angle regression" by Efron et al
1. Introduction. We congratulate the authors on their excellent work. The paper combines elegant theory and useful practical results in an intriguing manner. The LAR–Lasso–boosting relationship opens the door for new insights on existing methods' underlying statistical mechanisms and for the development of new and promising methodology. Two issues in particular have captured our attention, as their implications go beyond the squared error loss case presented in this paper, into wider statistical domains: robust fitting, classification, machine learning and more. We concentrate our discussion on these two results and their extensions.