Simultaneous selection of predictors and responses for high dimensional multivariate linear regression

Baiguo An and Beibei Zhang

Statistics & Probability Letters, 2017, vol. 127, issue C, 173-177

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: Canonical correlation; Group lasso; High dimensional; Multivariate linear regression; Variable selection (search for similar items in EconPapers)
Date: 2017
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DOI: 10.1016/j.spl.2017.04.008

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