dot-calcPenalty: Calculate penalty based on data

In glmSparseNet: Network Centrality Metrics for Elastic-Net Regularized Models

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')

glmSparseNet documentation built on April 14, 2021, 6 p.m.