Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4949237 | Computational Statistics & Data Analysis | 2017 | 12 Pages |
Abstract
By using Hilbert-Schmidt Independence Criterion, a sufficient dimension reduction method is proposed to estimate the directions in multiple-index models. A projection pursuit type of sufficient searching algorithm is introduced to reduce the computational complexity, as the original problem involves non-linear optimization over multidimensional Grassmann-manifold. A bootstrap procedure with additional jump point detection algorithm is used for determining the dimensionality. The proposed method demonstrates competitive performance compared with some well-known dimension reduction methods via simulation studies and an application to a real data.
Related Topics
Physical Sciences and Engineering
Computer Science
Computational Theory and Mathematics
Authors
Yuan Xue, Nan Zhang, Xiangrong Yin, Haitao Zheng,