rrpack: Reduced-Rank Regression
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>.
Version: |
0.1-13 |
Depends: |
R (≥ 3.4.0) |
Imports: |
ggplot2, glmnet, MASS, Rcpp (≥ 0.12.0) |
LinkingTo: |
Rcpp, RcppArmadillo |
Published: |
2022-06-16 |
Author: |
Kun Chen [aut,
cre],
Wenjie Wang [aut],
Jun Yan [ctb] |
Maintainer: |
Kun Chen <kun.chen at uconn.edu> |
License: |
GPL (≥ 3) |
NeedsCompilation: |
yes |
CRAN checks: |
rrpack results |
Documentation:
Downloads:
Reverse dependencies:
Linking:
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