runICA {MineICA} | R Documentation

## Run of fastICA and JADE algorithms

### Description

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

### Usage

      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

    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)

[Package MineICA version 1.26.0 Index]