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# CITATION.cff file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
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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
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://cran.r-universe.dev
repository-code: https://github.com/elizabethamona/AdaptiveGlasso
commit: e28f9c16fc233466d516b2bc3f1cc5f810912814
url: https://github.com/elizabethamona/AdaptiveGlasso
date-released: '2026-10-24'
contact:
- family-names: Amona
  given-names: Elizabeth B.
  email: amonaelizabeth1@gmail.com
  orcid: https://orcid.org/0000-0002-7575-788X