Last data update: 2014.03.03
|
R: R code for FastICA using a parallel scheme
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
Results
|