Reduced-Rank Regression

Multivariate regression methodologies including classical reduced-rank regression (RRR) studied by Anderson (1951) and Reinsel and Velu (1998) , reduced-rank regression via adaptive nuclear norm penalization proposed by Chen et al. (2013) and Mukherjee et al. (2015) , robust reduced-rank regression (R4) proposed by She and Chen (2017) , generalized/mixed-response reduced-rank regression (mRRR) proposed by Luo et al. (2018) , row-sparse reduced-rank regression (SRRR) proposed by Chen and Huang (2012) , reduced-rank regression with a sparse singular value decomposition (RSSVD) proposed by Chen et al. (2012) and sparse and orthogonal factor regression (SOFAR) proposed by Uematsu et al. (2019) .


Reference manual

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0.1-11 by Kun Chen, 2 years ago

Browse source code at

Authors: Kun Chen [aut, cre] , Wenjie Wang [ctb] , Jun Yan [ctb]

Documentation:   PDF Manual  

GPL (>= 3) license

Imports ggplot2, glmnet, lassoshooting, MASS, Rcpp

Linking to Rcpp, RcppArmadillo

See at CRAN