runICA {MineICA} | R Documentation |
This function performs ICA decomposition of a matrix
using functions fastICA
and
JADE
.
runICA(method = c("fastICA", "JADE"), X, nbComp, alg.type = c("deflation", "parallel"), fun = c("logcosh", "exp"), maxit = 500, tol = 10^-6, ...)
method |
The ICA method to use, either "JADE" (the default) or "fastICA". |
X |
A data matrix with n rows representing observations (e.g genes) and p columns representing variables (e.g samples). |
nbComp |
The number of components to be extracted. |
alg.type |
If |
fun |
The functional form of the G function used in
the approximation to neg-entropy (see 'details' of the
help of function |
maxit |
The maximum number of iterations to perform. |
tol |
A positive scalar giving the tolerance at which the un-mixing matrix is considered to have converged. |
... |
Additional parameters for |
See details of the functions
fastICA
and
JADE
.
A list, see outputs of fastICA
and
JADE
. This list includes at least
three elements:
the estimated mixing matrix
the estimated source matrix
, itemWthe estimated unmixing matrix
Anne Biton
set.seed(2004); M <- matrix(rnorm(5000*6,sd=0.3),ncol=10) M[1:10,1:3] <- M[1:10,1:3] + 2 M[1:100,1:3] <- M[1:100,1:3] +1 resJade <- runICA(X=M, nbComp=2, method = "JADE", maxit=10000)