R: R code for FastICA using a parallel scheme

ica.R.par {fastICA} | R Documentation

## R code for FastICA using a parallel scheme

### Description

R code for FastICA using a parallel scheme in which the components are estimated simultaneously. This function is called by the fastICA function.

### Usage

    ica.R.par(X, n.comp, tol, fun, alpha, maxit, verbose, w.init)

### Arguments

`X` | data matrix.
`n.comp` | number of components to be extracted.
`tol` | a positive scalar giving the tolerance at which the un-mixing matrix is considered to have converged.
`fun` | the functional form of the G function used in the approximation to negentropy.
`alpha` | constant in range [1,2] used in approximation to negentropy when `fun == "logcosh"`.
`maxit` | maximum number of iterations to perform.
`verbose` | a logical value indicating the level of output as the algorithm runs.
`w.init` | Initial value of un-mixing matrix.

### Details

See the help on `fastICA` for details.

### Value

The estimated un-mixing matrix W.

### Author(s)

J L Marchini and C Heaton

### See Also

`fastICA`, `ica.R.def`

[Package fastICA version 1.2-2 Index]