.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 1.12.0 Index]