Package: clusterGGM 0.1.1

clusterGGM: Sparse Gaussian Graphical Modeling with Variable Clustering

Perform sparse estimation of a Gaussian graphical model (GGM) with node aggregation through variable clustering. Currently, the package implements the clusterpath estimator of the Gaussian graphical model (CGGM) (Touw, Alfons, Groenen & Wilms, 2025; <doi:10.48550/arXiv.2407.00644>).

Authors:Daniel J.W. Touw [aut], Andreas Alfons [aut, cre], Ines Wilms [aut], Patrick J.F. Groenen [ths]

clusterGGM_0.1.1.tar.gz
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clusterGGM_0.1.1.tgz(r-4.6-x86_64)clusterGGM_0.1.1.tgz(r-4.6-arm64)clusterGGM_0.1.1.tgz(r-4.5-x86_64)clusterGGM_0.1.1.tgz(r-4.5-arm64)
clusterGGM_0.1.1.tar.gz(r-4.7-arm64)clusterGGM_0.1.1.tar.gz(r-4.7-x86_64)clusterGGM_0.1.1.tar.gz(r-4.6-arm64)clusterGGM_0.1.1.tar.gz(r-4.6-x86_64)
clusterGGM_0.1.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
clusterGGM/json (API)
NEWS

# Install 'clusterGGM' in R:

install.packages('clusterGGM', repos = c('https://aalfons.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/aalfons/clusterggm/issues

Uses libs:

c++– GNU Standard C++ Library v3

On CRAN:

cpp

3.85 score 137 downloads 9 exports 17 dependencies

Last updated from:3fd96d778b. Checks:13 OK. Indexed: yes.

Target	Result	Time
linux-devel-arm64	OK	163
linux-devel-x86_64	OK	199
source / vignettes	OK	240
linux-release-arm64	OK	170
linux-release-x86_64	OK	156
macos-release-arm64	OK	124
macos-release-x86_64	OK	383
macos-oldrel-arm64	OK	136
macos-oldrel-x86_64	OK	217
windows-devel	OK	205
windows-release	OK	215
windows-oldrel	OK	167
wasm-release	OK	144

Exports:cggm cggm_cv cggm_refit clusterpath_weights cv_folds get_clusters get_Theta lasso_weights min_clusters

Dependencies:cli dplyr generics glue lifecycle magrittr pillar pkgconfig R6 Rcpp RcppEigen rlang tibble tidyselect utf8 vctrs withr

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Sparse Gaussian Graphical Modeling with Variable Clustering	clusterGGM-package clusterGGM
Clusterpath Estimator of the Gaussian Graphical Model	cggm
Cross Validation for the Clusterpath Estimator of the Gaussian Graphical Model	cggm_cv
Refit the Gaussian Graphical Model for a Given Aggregation and Sparsity Structure	cggm_refit
Compute the Weight Matrix for the Clusterpath Penalty	clusterpath_weights
Create Cross-Validation Folds	cv_folds
Extract the Cluster Assignment	get_clusters get_clusters.CGGM get_clusters.CGGM_CV get_clusters.CGGM_refit
Extract the Estimated Precision Matrix	get_Theta get_Theta.CGGM get_Theta.CGGM_CV get_Theta.CGGM_refit
Compute the Weight Matrix for the Lasso Penalty	lasso_weights
Calculate the Minimum Number of Clusters	min_clusters