| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 1144886 | Journal of the Korean Statistical Society | 2011 | 9 Pages |
Abstract
In this paper, we newly define a unified predictor hypothesis that is applicable to all sufficient dimension reduction (SDR) methodologies. To test the predictor hypothesis, we propose a bootstrap approach by measuring the distances between reference subspaces and bootstrap subspaces. To measure the distances between two subspaces, the vector correlation coefficient is considered. Simulation studies confirm the background reasoning of the proposed tests.
Related Topics
Physical Sciences and Engineering
Mathematics
Statistics and Probability
Authors
Jae Keun Yoo,