net.neighbors: Get neighbors of a node in each graph in the input list of...

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

Description

For each graph in the input list of multiple graphs, returns the name of neighbor nodes connected to a given node.

Usage

net.neighbors(theta, index)

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.)
index	The row number of the node to be investigated.

Value

neighbors, a length K list. Each element in the list is a vector including row names of the neighbor nodes for the index node in 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 neighbors of node 50:
net.neighbors(result, index=50)

## End(Not run)

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