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grasps: Groupwise Regularized Adaptive Sparse Precision Solution

Provides a unified framework for sparse-group regularization and precision matrix estimation in Gaussian graphical models. It implements multiple sparse-group penalties, including sparse-group lasso, sparse-group adaptive lasso, sparse-group SCAD, and sparse-group MCP, and solves them efficiently using ADMM-based optimization. The package is designed for high-dimensional network inference where both sparsity and group structure are present.

Version: 0.1.0
Imports: igraph, ggforce, ggplot2, grDevices, Rcpp, Rdpack, scales
LinkingTo: Rcpp, RcppArmadillo
Suggests: knitr, MASS, quarto, rmarkdown
Published: 2025-11-27
DOI: 10.32614/CRAN.package.grasps
Author: Shiying Xiao ORCID iD [aut, cre]
Maintainer: Shiying Xiao <shiying.xiao at outlook.com>
BugReports: https://github.com/Carol-seven/grasps/issues
License: GPL (≥ 3)
URL: https://github.com/Carol-seven/grasps, https://shiying-xiao.com/grasps/
NeedsCompilation: yes
Materials: README
CRAN checks: grasps results

Documentation:

Reference manual: grasps.html , grasps.pdf
Vignettes: crit (source)
pen_est (source, R code)

Downloads:

Package source: grasps_0.1.0.tar.gz
Windows binaries: r-devel: grasps_0.1.0.zip, r-release: grasps_0.1.0.zip, r-oldrel: grasps_0.1.0.zip
macOS binaries: r-release (arm64): grasps_0.1.0.tgz, r-oldrel (arm64): grasps_0.1.0.tgz, r-release (x86_64): grasps_0.1.0.tgz, r-oldrel (x86_64): grasps_0.1.0.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.
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