# ------------------------------------------------ # CITATION.cff file created with {cffr} R package # See also: https://docs.ropensci.org/cffr/ # ------------------------------------------------ cff-version: 1.2.0 message: 'To cite package "AdaptiveGlasso" in publications use:' type: software license: MIT title: 'AdaptiveGlasso: Adaptive Graphical Lasso for Sparse Network Estimation' version: 1.0.0 doi: 10.32614/CRAN.package.AdaptiveGlasso abstract: 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. authors: - family-names: Amona given-names: Elizabeth B. email: amonaelizabeth1@gmail.com orcid: https://orcid.org/0000-0002-7575-788X repository: https://elizabethamona.r-universe.dev repository-code: https://github.com/elizabethamona/AdaptiveGlasso commit: 3a27aef313a16e575e61b605604a5367b6012f5d url: https://github.com/elizabethamona/AdaptiveGlasso date-released: '2026-10-13' contact: - family-names: Amona given-names: Elizabeth B. email: amonaelizabeth1@gmail.com orcid: https://orcid.org/0000-0002-7575-788X