Group variable selection for relative error regression

This paper considers an adaptive method based on relative error criteria to select grouped variables and estimate parameters simultaneously for the multiplicative regression model. The oracle properties of the proposed method are established. Simulation studies indicate that the proposed relative error approach has better performance to detect effective groups relative to several existing methods based on absolute error criteria, for example, the least squares and the least absolute deviation. Application is illustrated with the body fat and the birth weight datasets.