.glmSparseNetPrivate {glmSparseNet}R Documentation

Calculate GLM model with network-based regularization

Description

Calculate GLM model with network-based regularization

Usage

.glmSparseNetPrivate(fun, xdata, ydata, network, experiment.name = NULL,
  network.options = networkOptions(), ...)

Arguments

fun

function to be called (glmnet or cv.glmnet)

xdata

input data, can be a matrix or MultiAssayExperiment

ydata

response data compatible with glmnet

network

type of network, see below

experiment.name

when xdata is a MultiAssayExperiment object this parameter is required

network.options

options to calculate network

...

parameters that glmnet accepts

Value

an object just as glmnet network parameter accepts:

* string to calculate network based on data (correlation, covariance) * matrix representing the network * vector with already calculated penalty weights (can also be used directly with glmnet)


[Package glmSparseNet version 1.2.0 Index]