networkOptions {glmSparseNet} | R Documentation |
Setup network options, such as using weighted or unweighted degree, which centrality measure to use
networkOptions(method = "pearson", unweighted = TRUE, cutoff = 0, centrality = "degree", min.degree = 0, n.cores = 1, trans.fun = function(x) { x })
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 |
a list of options
glmOrphan glmDegree
networkOptions(unweighted = FALSE)