Fourier Methods for Estimating the Central Subspace and the Central Mean Subspace in Regression
用 Fourier 方法估计回归的中心子空间与中心均值子空间
In regression with a high-dimensional predictor vector, it is important to estimate the central and central mean subspaces that preserve sufficient information about the response and the mean response. Using the Fourier transform, we have derived the candidate matrices whose column spaces recover the central and central mean subspaces exhaustively. Under the normality assumption of the predictors, explicit estimates of the central and central mean subspaces are derived.…