.degreeGeneric {glmSparseNet} | R Documentation

## Generic function to calculate degree based on data

### Description

The assumption to use this function is that the network represented by a matrix is symetric and without any connection the node and itself.

### Usage

    .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, ...)

### Arguments

`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

### Value

a vector of the degrees

[Package glmSparseNet version 1.4.0 Index]