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AdaptiveGlasso: Adaptive Graphical Lasso for Sparse Network Estimation

Implements an adaptive graphical lasso method for sparse precision matrix and network estimation. The method combines ridge stabilization, cross-validated regularization, an initial graphical lasso estimate, and adaptive edge-specific penalties to estimate sparse conditional dependence structures. The method supports settings where the sample size is smaller than, equal to, or larger than the number of variables.

Version: 1.0.0
Imports: CVglasso, glasso
Suggests: testthat (≥ 3.0.0)
Published: 2026-10-24
DOI: 10.32614/CRAN.package.AdaptiveGlasso
Author: Elizabeth B. Amona ORCID iD [aut, cre, cph]
Maintainer: Elizabeth B. Amona <amonaelizabeth1 at gmail.com>
BugReports: https://github.com/elizabethamona/AdaptiveGlasso/issues
License: MIT + file LICENSE
URL: https://github.com/elizabethamona/AdaptiveGlasso
NeedsCompilation: no
Materials: README, NEWS
CRAN checks: AdaptiveGlasso results

Documentation:

Reference manual: AdaptiveGlasso.html , AdaptiveGlasso.pdf

Downloads:

Package source: AdaptiveGlasso_1.0.0.tar.gz
Windows binaries: r-devel: AdaptiveGlasso_1.0.0.zip, r-release: AdaptiveGlasso_1.0.0.zip, r-oldrel: AdaptiveGlasso_1.0.0.zip
macOS binaries: r-release (arm64): AdaptiveGlasso_1.0.0.tgz, r-oldrel (arm64): AdaptiveGlasso_1.0.0.tgz, r-release (x86_64): AdaptiveGlasso_1.0.0.tgz, r-oldrel (x86_64): AdaptiveGlasso_1.0.0.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.