runICA: Run of fastICA and JADE algorithms

Description Usage Arguments Details Value Author(s) Examples

View source: R/runAn.R

Description

This function performs ICA decomposition of a matrix using functions fastICA and JADE.

Usage

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  runICA(method = c("fastICA", "JADE"), X, nbComp,
    alg.type = c("deflation", "parallel"),
    fun = c("logcosh", "exp"), maxit = 500, tol = 10^-6,
    ...)

Arguments

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 alg.type="parallel" the components are extracted simultaneously (the default), if alg.type="deflation" the components are extracted one at a time, see fastICA.

fun

The functional form of the G function used in the approximation to neg-entropy (see 'details' of the help of function fastICA).

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 fastICA and JADE

Details

See details of the functions fastICA and JADE.

Value

A list, see outputs of fastICA and JADE. This list includes at least three elements:

A

the estimated mixing matrix

S

the estimated source matrix

, itemWthe estimated unmixing matrix

Author(s)

Anne Biton

Examples

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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)

Bioconductor-mirror/MineICA documentation built on May 29, 2017, 8:30 a.m.