shock (version 1.0)

networkInferenceGlassoBIC: 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)