R code for FastICA using a parallel scheme
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 |
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. |
See the help on fastICA
for details.
The estimated un-mixing matrix W.
J L Marchini and C Heaton
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