Envelope-based sparse reduced-rank regression for multivariate linear model

Envelope models were first proposed by Cook et al. (2010) as a method to reduce estimative and predictive variations in multivariate regression. Sparse reduced-rank regression, introduced by Chen and Huang (2012), is a widely used technique that performs dimension reduction and variable selection simultaneously in multivariate regression. In this work, we combine envelope models and sparse reduced-rank regression method to propose an …