plot.hglasso | R Documentation |
hglasso
, hcov
, or hbn
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
## S3 method for class 'hglasso' plot(x, layout=NULL,...)
x |
an object of class |
layout |
the layout of the graph to use. If not specified, |
... |
additional parameters to be passed to |
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.
Kean Ming Tan
Tan et al. (2014). Learning graphical models with hubs. To appear in Journal of Machine Learning Research. arXiv.org/pdf/1402.7349.pdf.
image.hglasso
summary.hglasso
hglasso
hcov
hbn
############################################## # 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")
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