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Efficiently implements the Graphical Lasso algorithm, utilizing the 'Armadillo' 'C++' library for rapid computation. This algorithm introduces an L1 penalty to derive sparse inverse covariance matrices from observations of multivariate normal distributions. Features include the generation of random and structured sparse covariance matrices, beneficial for simulations, statistical method testing, and educational purposes in graphical modeling. A unique function for regularization parameter selection based on predefined sparsity levels is also offered, catering to users with specific sparsity requirements in their models. The methodology for sparse inverse covariance estimation implemented in this package is based on the work of Friedman, Hastie, and Tibshirani (2008) <doi:10.1093/biostatistics/kxm045>.
| Version: | 1.1.1 |
| Depends: | R (≥ 3.3) |
| Imports: | stats, Rcpp (≥ 0.12), RcppArmadillo |
| LinkingTo: | Rcpp (≥ 0.12), RcppArmadillo |
| Suggests: | knitr, rmarkdown |
| Published: | 2023-12-15 |
| DOI: | 10.32614/CRAN.package.Glarmadillo |
| Author: | Alessandro Meng [aut, cre] |
| Maintainer: | Alessandro Meng <mengfangeng at ruc.edu.cn> |
| License: | GPL (≥ 3) |
| NeedsCompilation: | yes |
| Materials: | README |
| CRAN checks: | Glarmadillo results |
| Reference manual: | Glarmadillo.pdf |
| Vignettes: |
An Introduction to Glarmadillo |
| Package source: | Glarmadillo_1.1.1.tar.gz |
| Windows binaries: | r-devel: Glarmadillo_1.1.1.zip, r-release: Glarmadillo_1.1.1.zip, r-oldrel: Glarmadillo_1.1.1.zip |
| macOS binaries: | r-release (arm64): Glarmadillo_1.1.1.tgz, r-oldrel (arm64): Glarmadillo_1.1.1.tgz, r-release (x86_64): Glarmadillo_1.1.1.tgz, r-oldrel (x86_64): Glarmadillo_1.1.1.tgz |
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