ZHANG ZhongZhan1 & WANG DaRong2 1College of Applied Sciences,Beijing University of Technology,Beijing 100124,China,2The Pilot College,Beijing 101101
Abstract:
In this paper, we propose a new criterion, named PICa, to simultaneously select explanatory variables in the mean model and variance model in heteroscedastic linear models based on the model structure. We show that the new criterion can select the true mean model and a correct variance model with probability tending to 1 under mild conditions. Simulation studies and a real example are presented to evaluate the new criterion, and it turns out that the proposed approach performs well.