Robust High-Dimensional Regression with Coefficient Thresholding and Its Application to Imaging Data Analysis
系数阈值化的稳健高维回归及影像数据应用
It is important to develop statistical techniques to analyze high-dimensional data in the presence of both complex dependence and possible heavy tails and outliers in real-world applications such as imaging data analyses. We propose a new robust high-dimensional regression with coefficient thresholding, in which an efficient nonconvex estimation procedure is proposed through a thresholding function and the robust Huber loss. The proposed regularization method accounts for…