cv.glmDegree {glmSparseNet}R Documentation

GLMNET cross-validation model penalizing nodes with small degree

Description

This function overrides the 'trans.fun' options in 'network.options' with the inverse of a degree described in VerĂ­ssimo et al. (2015) that penalizes nodes with small degree.

Usage

cv.glmDegree(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.glmDegree(xdata, rnorm(nrow(xdata)), 'correlation',
            family = 'gaussian',
            nfolds = 5,
            network.options = networkOptions(min.degree = .2))

[Package glmSparseNet version 1.0.0 Index]