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

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

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.

The estimated un-mixing matrix W.

See the help on `fastICA`

for details.