Pınar, M. Ç.2015-07-282015-07-281997-070893-9659http://hdl.handle.net/11693/10871The robust linear regression problem using Huber's piecewise-quadratic M-estimator function is considered. Without exception, computational algorithms for this problem have been primal in nature. In this note, a dual formulation of this problem is derived using Lagrangean duality. It is shown that the dual problem is a strictly convex separable quadratic minimization problem with linear equality and box constraints. Furthermore, the primal solution (Huber's M-estimate) is obtained as the optimal values of the Lagrange multipliers associated with the dual problem. As a result, Huber's M-estimate can be computed using off-the-shelf optimization software.EnglishLagrangean dualityHuber's M-estimatorRobust regressionQuadratic programmingArticle10.1016/S0893-9659(97)00061-X