EM for Gaussian graphical model selection
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EMGS
codes
figures
.gitignore
EMGS_1.0.tar.gz
README.md

README.md

EMGS

This repository contains the R package EMGS (currently still developer's version), described in

Zehang R Li and Tyler H McCormick. An Expectation Conditional Maximization approach for Gaussian graphical models, 2018 arXiv

Using the package

You can install the package with devtools

install_github("richardli/EMGS", subdir = "EMGS")
library(EMGS)

First naive example

This example demonstrates the bias reduction of EMGS. It creates a plot (illustraion-emgs.pdf) under the figures/ directory.

setwd("codes/")
source("example1.R")

Second example

This example demonstrates the informative priors. It creates a plot (structure.pdf) under the figures/ directory.

setwd("codes/")
source("example2.R")

Simulation studies

Running the full version of the simulation as described in the paper takes a long time and is recommended to be implemented on a cluster. However the sim_gaussian.R and sim_mixed.R provide small examples with a few replications.