Dimension Reduction in Regressions Through Cumulative Slicing Estimation
通过累积切片估计实现回归充分降维
In this paper we offer a complete methodology of cumulative slicing estimation to sufficient dimension reduction. In parallel to the classical slicing estimation, we develop three methods that are termed, respectively, as cumulative mean estimation, cumulative variance estimation, and cumulative directional regression. The strong consistency for p=O(n1 / 2 / log n) and the asymptotic normality for p=o(n1 / 2) are established, where p is the dimension of the predictors and n…