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drrglm: Doubly Regularized Matrix-Variate Regression

The doubly regularized matrix-variate regression solves a low-rank-plus-sparse structure for matrix-variate generalized linear models through a weighted combination of nuclear-norm and L1-norm. The methodology implemented by this package is described in the paper "Doubly Regularized Matrix-Variate Regression", which has been tentatively accepted for publication but does not yet have a DOI or URL. A formal citation will be added in a future update once the final publication details are available.

Version: 0.3.2
Depends: R (≥ 4.3.0)
Imports: data.table, glmnet, Rcpp, stats
LinkingTo: Rcpp, RcppArmadillo
Published: 2026-04-20
DOI: 10.32614/CRAN.package.drrglm (may not be active yet)
Author: Zengchao Xu [aut, cre, cph], Shan Luo [aut], Binyan Jiang [aut]
Maintainer: Zengchao Xu <zengc.xu at aliyun.com>
BugReports: https://github.com/paradoxical-rhapsody/drrglm/issues
License: AGPL-3
URL: https://github.com/paradoxical-rhapsody/drrglm
NeedsCompilation: yes
Materials: README, NEWS
CRAN checks: drrglm results

Documentation:

Reference manual: drrglm.html , drrglm.pdf

Downloads:

Package source: drrglm_0.3.2.tar.gz
Windows binaries: r-devel: drrglm_0.3.2.zip, r-release: not available, r-oldrel: not available
macOS binaries: r-release (arm64): drrglm_0.3.2.tgz, r-oldrel (arm64): not available, r-release (x86_64): drrglm_0.3.2.tgz, r-oldrel (x86_64): drrglm_0.3.2.tgz

Linking:

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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.