The help for fastICA says:
The data matrix X is considered to be a linear combination of
non-Gaussian (independent) components i.e. X = SA where columns of
S contain the independent components and A is a linear mixing
matrix.
The value of fastICA is a list with components "S" (the estimated
source matrix) and "A" (the estimated mixing matrix). Are these what
you want?
-- Tony Plate
Joel F?rstenberg-H?gg wrote:> Hi all,
>
>
>
> Does anyone know how to get the independent components and loadings from an
Independent Component Analysis (ICA), as well as principal components and
loadings from a Pricipal Component analysis (PCA) using the fastICA package? Or
perhaps if there's another way to do ICAs in R?
>
>
> Below is an example from the fastICA manual
(http://cran.r-project.org/web/packages/fastICA/fastICA.pdf)
>
>
>
> if(require(MASS))
> {
> x <- mvrnorm(n = 1000, mu = c(0, 0), Sigma = matrix(c(10, 3, 3, 1),
2, 2))
> x1 <- mvrnorm(n = 1000, mu = c(-1, 2), Sigma = matrix(c(10, 3, 3,
1), 2, 2))
> X <- rbind(x, x1)
> a <- fastICA(X, 2, alg.typ = "deflation", fun =
"logcosh", alpha = 1, method = "R", row.norm = FALSE, maxit
= 200, tol = 0.0001, verbose = TRUE)
> par(mfrow = c(1, 3))
> plot(a$X, main = "Pre-processed data")
> plot(a$X%*%a$K, main = "PCA components")
> plot(a$S, main = "ICA components")
> }
>
>
>
> Best regards,
>
>
>
> Joel
>
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