R: Calculate penalty based on data

.calcPenalty {glmSparseNet}

R Documentation

Calculate penalty based on data

Description

Internal method to calculate the network using data-dependant methods

Usage

.calcPenalty(xdata, penalty.type, network.options = networkOptions())

Arguments

`xdata`	input data
`penalty.type`	which method to use
`network.options`	options to be used

Value

vector with penalty weights

Examples

xdata <- matrix(rnorm(100), ncol = 20)
glmSparseNet:::.calcPenalty(xdata, 'none')
glmSparseNet:::.calcPenalty(xdata, 'correlation',
                            networkOptions(cutoff = .6))
glmSparseNet:::.calcPenalty(xdata, 'correlation')
glmSparseNet:::.calcPenalty(xdata, 'covariance',
                            networkOptions(cutoff = .6))
glmSparseNet:::.calcPenalty(xdata, 'covariance')
glmSparseNet:::.calcPenalty(xdata, 'sparsebn')

[Package glmSparseNet version 1.4.0 Index]