Title: Moment kernel for estimating central mean subspace and central subspace
Authors: Xiangrong Yin - University of Kentucky (United States) [presenting]
Weihang Ren - University of Kentucky (United States)
Dennis Cook - University of Minnesota (United States)
Abstract: The T-central subspace allows one to perform sufficient dimension reduction for any statistical functional of interest. We propose a general estimator using (third) moment kernel to estimate the T-central subspace. We particularly focus on central mean subspace via the regression mean function, and central subspace via Fourier transform or slicing. Theoretical results are established and simulation studies show the advantages of our proposed methods.