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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.
Package details |
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| Author | Shiying Xiao [aut, cre] (ORCID: <https://orcid.org/0000-0002-8846-3258>) |
| Maintainer | Shiying Xiao <shiying.xiao@outlook.com> |
| License | GPL (>= 3) |
| Version | 0.1.0 |
| URL | https://github.com/Carol-seven/grasps https://shiying-xiao.com/grasps/ |
| Package repository | View on CRAN |
| Installation |
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