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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