.degreeGeneric {glmSparseNet} | R Documentation |
The assumption to use this function is that the network represented by a matrix is symetric and without any connection the node and itself.
.degreeGeneric( fun = stats::cor, fun.prefix = "operator", xdata, cutoff = 0, consider.unweighted = FALSE, chunks = 1000, force.recalc.degree = FALSE, force.recalc.network = FALSE, n.cores = 1, ... )
fun |
function that will calculate the edge weight between 2 nodes |
fun.prefix |
used to store low-level information on network as it can become to large to be stored in memory |
xdata |
calculate correlation matrix on each column |
cutoff |
positive value that determines a cutoff value |
consider.unweighted |
consider all edges as 1 if they are greater than 0 |
chunks |
calculate function at batches of this value (default is 1000) |
force.recalc.degree |
force recalculation of penalty weights (but not the network), instead of going to cache |
force.recalc.network |
force recalculation of network and penalty weights, instead of going to cache |
n.cores |
number of cores to be used |
... |
extra parameters for fun |
a vector of the degrees