LaMAsE: Least Asymmetric Mean Absolute Scaled Error Estimation
Wang, Jianqiang.C ; Guler, Kemal
Keyword(s): Asymmetric loss; quantile regression; forecast evaluation
Abstract: We consider Asymmetric Mean Absolute Scaled Error (aMAsE), a parameterized extension of scaled absolute error, that penalizes negative and positive errors asymmetrically. We study the theoretical properties of estimates when this measure is used as the loss criterion to be minimized.
External Posting Date: December 8, 2011 [Abstract]. Approved for External Publication
Internal Posting Date: November 8, 2011 [Fulltext]