.calcPenalty {glmSparseNet} | R Documentation |
Internal method to calculate the network using data-dependant methods
.calcPenalty(xdata, penalty.type, network.options = networkOptions())
xdata |
input data |
penalty.type |
which method to use |
network.options |
options to be used |
vector with penalty weights
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')