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A New Class of Estimators Based on a General Relative Loss Function
Motivated by the relative loss estimator of the median, we propose a new class of estimators for linear quantile models using a general relative loss function defined by the Box–Cox transformation function. The proposed method is very flexible. It includes a traditional quantile regression and median regression under the relative loss as special cases. Compared to the traditional linear quantile estimator, the proposed estimator has smaller variance and hence is more efficient in makingdoi:10.3390/math9101138 fatcat:ddepjsj7yvf2nfdjexszpexmo4