cv.glmHub: GLMNET cross-validation model penalizing nodes with small...

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

Description

This function overrides the 'trans.fun' options in 'network.options' with an heuristic described in Veríssimo et al. that penalizes nodes with small degree.

Usage

cv.glmHub(xdata, ydata, network, network.options = networkOptions(), ...)

Arguments

xdata	input data, can be a matrix or MultiAssayExperiment
ydata	response data compatible with glmnet
network	type of network, see below
network.options	options to calculate network
...	parameters that glmnet accepts

Value

see cv.glmSparseNet

See Also

glmNetSparse

Examples

xdata <- matrix(rnorm(100), ncol = 5)
cv.glmHub(xdata, rnorm(nrow(xdata)), 'correlation',
          family = 'gaussian',
          nfolds = 5,
          network.options = networkOptions(min.degree = .2))

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