Reduced rank stochastic regression with a sparse singular value decomposition

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Envelopes and reduced-rank regression (2015, background): “Chen et al. (2012) and Chen35 and Huang (2012) extended reduced-rank regression to high-dimensional settings and demon-36 strated the advantages of parsimoniously reducing model parameters and interrelating response37 variables.38 Envelope regression, which was first proposed by Cook et al. (2010),…”