Ultrahigh dimensional feature screening for additive model with multivariate response
We consider feature screening for ultrahigh dimensional additive model with multivariate response in this paper. A new method named generalized correlation based projection screening is proposed by using generalized correlation between each predictor and multivariate response. The sure screening and ranking consistency properties are established under some regularized conditions for the proposed procedure. In addition, we construct an iterative version of the proposed screening procedure to enhance the finite sample screening performance. Both simulation studies and the real data analysis demonstrate that the proposed method works effectively.