networkInferenceGlassoBIC {shock}

Network inference using the glasso algorithm

Description

This function performs network inference using the glasso algorithm for several regularization parameters and selects a network based on the BIC of the model.

Usage

networkInferenceGlassoBIC(dataNet, nb.rho = 100)

Arguments

dataNet

matrix of data

nb.rho

number of regularization parameters to test in the glasso algorithm

Value

A

selected adjacency matrix based on BIC

Theta

selected precision matrix based on BIC

Sigma

selected covariance matrix based on BIC

penaltieslist

list of regularization parameters

pathA

list of adjacency matrices for each regularization parameter

pathTheta

list of precision matrices for each regularization parameter

pathSigma

list of covariance matrices for each regularization parameter

pathBIC

list of BIC values for each regularization parameter

References

https://cran.r-project.org/web/packages/glasso/glasso.pdf

Examples

## load data to test 
data(dataTest)

## perform network inference 
resNet <- networkInferenceGlassoBIC(dataTest)