.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 1.8.1 Index]