net.edges: List the edges of each graph in the input list of multiple...

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

Description

List every estimated edge in the form of pair of connected nodes for each graph in the input list of multiple graphs.

Usage

net.edges(theta)

Arguments

theta

An input list of multiple graphs. Each graph is represented as a pXp matrix. (For example, the result of the fasjem algorithm: a list of pXp matrices in which each matrix represents an estimated sparse inverse covariance matrix.)

Value

edges, a length K list, each element of the list represents an igraph.es object which is the detail of all pairs of connected nodes of each graph in the input list of multiple graphs.

Author(s)

Beilun Wang

References

Beilun Wang, Ji Gao, Yanjun Qi (2017). A Fast and Scalable Joint Estimator for Learning Multiple Related Sparse Gaussian Graphical Models. <http://proceedings.mlr.press/v54/wang17e/wang17e.pdf>

Examples

## Not run: 
## load an example multi-task dataset with K=2 tasks, p=100 features, and n=200 samples per task:
data(exampleData)
##run
result = fasjem(X = exampleData, method = "fasjem-g", 0.1, 0.1, 0.1, 0.05, 10)
## get edges list:
net.edges(result)

## End(Not run)

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