rrpack

Multivariate regression methodologies including classical reduced-rank regression (RRR) studied by Anderson (1951) doi:10.1214/aoms/1177729580 and Reinsel and Velu (1998) doi:10.1007/978-1-4757-2853-8, reduced-rank regression via adaptive nuclear norm penalization proposed by Chen et al. (2013) doi:10.1093/biomet/ast036 and Mukherjee et al. (2015) doi:10.1093/biomet/asx080, robust reduced-rank regression (R4) proposed by She and Chen (2017) doi:10.1093/biomet/asx032, generalized/mixed-response reduced-rank regression (mRRR) proposed by Luo et al. (2018) doi:10.1016/j.jmva.2018.04.011, row-sparse reduced-rank regression (SRRR) proposed by Chen and Huang (2012) doi:10.1080/01621459.2012.734178, reduced-rank regression with a sparse singular value decomposition (RSSVD) proposed by Chen et al. (2012) doi:10.1111/j.1467-9868.2011.01002.x and sparse and orthogonal factor regression (SOFAR) proposed by Uematsu et al. (2019) doi:10.1109/TIT.2019.2909889.

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