Learn R Programming

hglasso (version 1.3)

plot.hglasso: Plot an object of class hglasso, hcov, or hbn

Description

This function plots an object hglasso or hcov --- graphical representation of the estimated inverse covariance matrix from hglasso, covariance matrix from hcov, or binary network from hbn

Usage

# S3 method for hglasso
plot(x, layout=NULL,…)

Arguments

x

an object of class hglasso, hcov, or hbn.

layout

the layout of the graph to use. If not specified, layout.kamada.kawai is used.

…

additional parameters to be passed to plot.igraph.

Details

This function plots a graphical representation of the estimated inverse covariance matrix or covariance matrix. The hubs are colored in red and has a large vertex size. Features indices for hubs are shown.

References

Tan et al. (2014). Learning graphical models with hubs. To appear in Journal of Machine Learning Research. arXiv.org/pdf/1402.7349.pdf.

See Also

image.hglasso summary.hglasso hglasso hcov hbn

Examples

Run this code
# NOT RUN {
##############################################
# Example from Figure 1 in the manuscript
# A toy example to illustrate the results from 
# Hub Graphical Lasso
##############################################
library(mvtnorm)
set.seed(1)
n=100
p=100

# A network with 4 hubs
Theta<-HubNetwork(p,0.99,4,0.1)$Theta

# Generate data matrix x
x <- rmvnorm(n,rep(0,p),solve(Theta))
x <- scale(x)

# Run Hub Graphical Lasso to estimate the inverse covariance matrix
res1 <- hglasso(cov(x),0.3,0.3,1.5)

# Graphical representation of the estimated Theta
plot(res1,main="conditional independence graph")

# }

Run the code above in your browser using DataLab