Reduced-Rank Regression
Mixed-response reduced-rank regression with rank selected by cross val...
Reduced-rank regression with rank selected by cross validation
Sparse orthognal factor regression tuned by cross validation
Row-sparse reduced-rank regression tuned by cross validation
Generalized or mixed-response reduced-rank regression
Scatter Plot
Robust reduced-rank regression
Estimated coefficients
Cook's distance in reduced-rank regression for model diagnostics
Fitting reduced-rank regression with a specific rank
Leverage scores and Cook's distance in reduced-rank regression for mod...
Multivariate reduced-rank linear regression
Simulation model 1
Simulation model 2
Simulation model 3
Simulation model 4
Simulation model 5
Fitting reduced-rank ridge regression with given rank and shrinkage pe...
Reduced-rank regression with a sparse singular value decomposition
Sparse orthogonal factor regression
Row-sparse reduced-eank regresssion
Summarize rrpack Objects
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>.