.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 1.1.2 Index]