Nonparametric Independence Screening in Sparse Ultra-High-Dimensional Varying Coefficient Models
稀疏超高维变系数模型中的非参数独立筛选
The varying-coefficient model is an important nonparametric statistical model that allows us to examine how the effects of covariates vary with exposure variables. When the number of covariates is big, the issue of variable selection arrives. In this paper, we propose and investigate marginal nonparametric screening methods to screen variables in ultra-high dimensional sparse varying-coefficient models. The proposed nonparametric independence screening (NIS) selects…