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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
DOI: 10.32614/CRAN.package.rrpack
Author: Kun Chen ORCID iD [aut, cre], Wenjie Wang ORCID iD [aut], Jun Yan ORCID iD [ctb]
Maintainer: Kun Chen <kun.chen at uconn.edu>
License: GPL (≥ 3)
NeedsCompilation: yes
CRAN checks: rrpack results

Documentation:

Reference manual: rrpack.pdf

Downloads:

Package source: rrpack_0.1-13.tar.gz
Windows binaries: r-devel: rrpack_0.1-13.zip, r-release: rrpack_0.1-13.zip, r-oldrel: rrpack_0.1-13.zip
macOS binaries: r-release (arm64): rrpack_0.1-13.tgz, r-oldrel (arm64): rrpack_0.1-13.tgz, r-release (x86_64): rrpack_0.1-13.tgz, r-oldrel (x86_64): rrpack_0.1-13.tgz
Old sources: rrpack archive

Reverse dependencies:

Reverse imports: gofar, nbfar
Reverse suggests: rrMixture

Linking:

Please use the canonical form https://CRAN.R-project.org/package=rrpack to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.