fasjem: A Fast and Scalable Joint Estimator for Learning Multiple Related Sparse Gaussian Graphical Models

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 <http://proceedings.mlr.press/v54/wang17e/wang17e.pdf>.

Package details

AuthorBeilun Wang [aut, cre], Yanjun Qi [aut]
MaintainerBeilun Wang <bw4mw@virginia.edu>
LicenseGPL-2
Version1.1.2
URL https://github.com/QData/JEM
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("fasjem")

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fasjem documentation built on May 2, 2019, 9:19 a.m.