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JGL  

Performs the Joint Graphical Lasso for Sparse Inverse Covariance Estimation on Multiple Classes
View on CRAN: Click here


Download and install JGL package within the R console
Install from CRAN:
install.packages("JGL")

Install from Github:
library("remotes")
install_github("cran/JGL")

Install by package version:
library("remotes")
install_version("JGL", "2.3.2")



Attach the package and use:
library("JGL")
Maintained by
Patrick Danaher
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2012-07-27
Latest Update: 2023-12-19
Description:
The Joint Graphical Lasso is a generalized method for estimating Gaussian graphical models/ sparse inverse covariance matrices/ biological networks on multiple classes of data. We solve JGL under two penalty functions: The Fused Graphical Lasso (FGL), which employs a fused penalty to encourage inverse covariance matrices to be similar across classes, and the Group Graphical Lasso (GGL), which encourages similar network structure between classes. FGL is recommended over GGL for most applications. Reference: Danaher P, Wang P, Witten DM. (2013) .
How to cite:
Patrick Danaher (2012). JGL: Performs the Joint Graphical Lasso for Sparse Inverse Covariance Estimation on Multiple Classes. R package version 2.3.2, https://cran.r-project.org/web/packages/JGL
Previous versions and publish date:
2.1 (2012-07-27 07:42), 2.2 (2012-08-17 19:44), 2.3.1 (2018-12-01 00:40), 2.3 (2013-04-16 21:27)
Other packages that cited JGL R package
View JGL citation profile
Other R packages that JGL depends, imports, suggests or enhances
Functions, R codes and Examples using the JGL R package
Some associated functions: JGL-internal . JGL-package . JGL . crit . example.data . gcrit . net.degree . net.edges . net.hubs . net.neighbors . screen.fgl . screen.ggl . subnetworks . 
Some associated R codes: crit.R . dsgl.R . flsa.general.R . flsa2.R . gcrit.R . make.adj.matrix.R . net.degree.R . net.edges.R . net.hubs.R . net.neighbors.R . penalty.as.matrix.R . screen.fgl.R . screen.ggl.R . soft.R . subnetworks.R .  Full JGL package functions and examples
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