题 目： Moment Kernel for Estimating Central Mean Subspace and Central Subspace

摘 要：The T-central subspace, introduced by Luo, Li and Yin (2014), 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. In this talk, 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.

报告人： 殷向荣 教授

肯塔基大学统计学系

 时间：2019年6月18日（星期二） 下午14:00-16:00

地点：数学科学学院424会议室

欢迎广大师生参加!

数学科学学院

  2019年6月13日