rags2ridges: A One-Stop-ℓ2-Shop for Graphical Modeling of High-Dimensional Precision Matrices

Dublin Core

Title

rags2ridges: A One-Stop-ℓ2-Shop for Graphical Modeling of High-Dimensional Precision Matrices

Subject

: graphical modeling, high-dimensional data, networks, regularization, R

Description

A graphical model is an undirected network representing the conditional independence
properties between random variables. Graphical modeling has become part and parcel
of systems or network approaches to multivariate data, in particular when the variable
dimension exceeds the observation dimension. rags2ridges is an R package for graphical
modeling of high-dimensional precision matrices through ridge (ℓ2) penalties. It provides
a modular framework for the extraction, visualization, and analysis of Gaussian graphical
models from high-dimensional data. Moreover, it can handle the incorporation of prior
information as well as multiple heterogeneous data classes. As such, it provides a one-stopℓ2-shop for graphical modeling of high-dimensional precision matrices. The functionality
of the package is illustrated with an example dataset pertaining to blood-based metabolite
measurements in persons suffering from Alzheimer’s disease.

Creator

Carel F. W. Peeters

Source

https://www.jstatsoft.org/article/view/v102i04

Publisher

Wageningen University
& Research

Date

April 2022

Contributor

Fajar bagus W

Format

PDF

Language

English

Type

Text

Files

Citation

Carel F. W. Peeters, “rags2ridges: A One-Stop-ℓ2-Shop for Graphical Modeling of High-Dimensional Precision Matrices,” Repository Horizon University Indonesia, accessed April 4, 2025, https://repository.horizon.ac.id/items/show/8250.