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fasjem  

A Fast and Scalable Joint Estimator for Learning Multiple Related Sparse Gaussian Graphical Models
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("fasjem", "1.1.2")



Attach the package and use:
library("fasjem")
Maintained by
Beilun Wang
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2017-04-21
Latest Update: 2017-08-01
Description:
This is an R implementation of "A Fast and Scalable Joint Estimator for Learning Multiple Related Sparse Gaussian Graphical Models" (FASJEM). The FASJEM algorithm can be used to estimate multiple related precision matrices. For instance, it can identify context-specific gene networks from multi-context gene expression datasets. By performing data-driven network inference from high-dimensional and heterogonous data sets, this tool can help users effectively translate aggregated data into knowledge that take the form of graphs among entities. Please run demo(fasjem) to learn the basic functions provided by this package. For more details, please see .
How to cite:
Beilun Wang (2017). fasjem: A Fast and Scalable Joint Estimator for Learning Multiple Related Sparse Gaussian Graphical Models. R package version 1.1.2, https://cran.r-project.org/web/packages/fasjem. Accessed 21 Nov. 2024.
Previous versions and publish date:
1.0.0 (2017-04-21 20:27), 1.1.0 (2017-05-25 23:13), 1.1.1 (2017-07-12 18:11)
Other packages that cited fasjem R package
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Complete documentation for fasjem
Functions, R codes and Examples using the fasjem R package
Some associated functions: exampleData . fasjem-package . fasjem . net.degree . net.edges . net.hubs . net.neighbors . plot.fasjem . 
Some associated R codes: fasjem.R . net.degree.R . net.edges.R . net.hubs.R . net.neighbors.R .  Full fasjem package functions and examples
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