QData/JointNets: Sparse Gaussian Graphical Model Estimation, Visualization and Evaluation

A set of tools for performing sparse Gaussian graphical model (joint, multiple and difference) estimation from high dimensional dataset. It contains a general purpose visualization function as well as a specialized function for 3d brain network. Simulation and evaluation modules are available. It also contains a simple GUI built in shiny for easy graph visualization. Methods include SIMULE (Wang B et al. (2017) <doi:10.1007/s10994-017-5635-7>), WSIMULE (Singh C et al. (2017) <arXiv:1709.04090v2>), DIFFEE (Wang B et al. (2018) <arXiv:1710.11223>), FASJEM (Wang B et al. (2018) <arXiv:1702.02715v3>), JEEK (Wang B et al. (2018) <arXiv:1806.00548>) and DIFFEEK (Wang B et al, under final review for publication).

Getting started

Package details

AuthorBeilun Wang [aut], Yanjun Qi [aut], Zhaoyang Wang [aut, cre]
MaintainerZhaoyang Wang <[email protected]>
LicenseGPL-2
Version1.0.0
URL https://github.com/QData/JointNets
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("devtools")
library(devtools)
install_github("QData/JointNets")
QData/JointNets documentation built on Dec. 26, 2018, 11:14 a.m.