networkOptions: Setup network options

In glmSparseNet: Network Centrality Metrics for Elastic-Net Regularized Models

Description

Setup network options, such as using weighted or unweighted degree, which centrality measure to use

Usage

networkOptions(
  method = "pearson",
  unweighted = TRUE,
  cutoff = 0,
  centrality = "degree",
  min.degree = 0,
  n.cores = 1,
  trans.fun = function(x) {     x }
)

Arguments

method	in case of correlation and covariance, which method to use
unweighted	calculate degree using unweighted network
cutoff	cuttoff value in network edges to trim the network
centrality	centrality measure to use, currently only supports degree
min.degree	minimum value that individual penalty weight can take
n.cores	number of cores to use, default to 1 The trans.fun argument takes a function definition that will apply a transformation to the penalty vector calculated from the degree. This transformation allows to change how the penalty is applied.
trans.fun	see below

Value

a list of options

See Also

glmOrphan glmDegree

Examples

networkOptions(unweighted = FALSE)

glmSparseNet documentation built on April 14, 2021, 6 p.m.