Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
5129698 | Statistics & Probability Letters | 2017 | 5 Pages |
Abstract
Most existing variable selection methods for multivariate linear models focus only on predictor selection. In this article, we propose a two-step (double group lasso step and sparse canonical correlation step) method to conduct variable selection for predictors and responses simultaneously.
Keywords
Related Topics
Physical Sciences and Engineering
Mathematics
Statistics and Probability
Authors
Baiguo An, Beibei Zhang,