CVglasso: Lasso Penalized Precision Matrix Estimation

Estimates a lasso penalized precision matrix via blockwise coordinate descent (BCD). This package is a simple wrapper around the popular 'glasso' package and extends and enhances its capabilities. These enhancements include built-in cross validation and visualizations. See Friedman et al. (2008) <doi:10.1093/biostatistics/kxm045> for details regarding the estimation method.

Version: 1.0.1
Imports: doParallel, dplyr, foreach, ggplot2, glasso, parallel, stats
Suggests: testthat, rmarkdown, knitr, pkgdown, microbenchmark
Published: 2026-05-20
DOI: 10.32614/CRAN.package.CVglasso
Author: Matt Galloway [aut], James Curran [aut, cre]
Maintainer: James Curran <j.curran at auckland.ac.nz>
BugReports: https://github.com/jmcurran/CVglasso/issues
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://github.com/jmcurran/CVglasso
NeedsCompilation: no
Materials: NEWS
CRAN checks: CVglasso results

Documentation:

Reference manual: CVglasso.html , CVglasso.pdf
Vignettes: Benchmarks (source, R code)
CVglasso Tutorial (source, R code)

Downloads:

Package source: CVglasso_1.0.1.tar.gz
Windows binaries: r-devel: CVglasso_1.0.zip, r-release: CVglasso_1.0.zip, r-oldrel: CVglasso_1.0.zip
macOS binaries: r-release (arm64): CVglasso_1.0.tgz, r-oldrel (arm64): CVglasso_1.0.tgz, r-release (x86_64): CVglasso_1.0.1.tgz, r-oldrel (x86_64): CVglasso_1.0.1.tgz
Old sources: CVglasso archive

Reverse dependencies:

Reverse imports: comparison, GGRidge

Linking:

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