[R] fastICA package: C, R codes provide vastly different results

[Ranjan Maitra]

Dear friends,

I have been trying out the C and the R codes in the fastICA package.
However, it turns out that these often give vastly different results,
especially when row.norm is set to T. This happens even though I have
initialized the input matrix to be exactly the same for both of them.

Here is an example:

### cut code here

xx <- read.table(file =
"http://maitra.public.iastate.edu/SharadUtshob05.dat")


win <- matrix(c(-0.434590,  1.288207, -0.597128, -0.501621,  1.434678,
0.812076, -1.281559, -1.798178,  0.409151), ncol = 3)

library(fastICA)

adeflate.C <- fastICA(X = xx, alg.typ="deflation", row.norm=T,
w.init=win, n.comp=3, fun = "logcosh", method = "C")

adeflate.R <- fastICA(X = xx, alg.typ="deflation", row.norm=T,
w.init=win, n.comp=3, fun = "logcosh", method = "R")


### end code here.

The answers follow: note that the final un-mixing matrix estimate W is
not even close to each other. 

adeflate.R$W
            [,1]       [,2]       [,3]
[1,] -0.85074291 -0.2385149  0.4683451
[2,]  0.02907471 -0.9110909 -0.4111789
[3,] -0.52477726  0.3361905 -0.7820388


adeflate.C$W
             [,1]          [,2]         [,3]
[1,] -0.001317682 -0.9904552102 -0.137828767
[2,] -0.006132130  0.1378342956 -0.990436316
[3,]  0.999980330 -0.0004598964 -0.006255222

Can anyone throw light on this matter?

On the other hand, using row.norm = F provides the following results:

adeflate.R$W
            [,1]       [,2]       [,3]
[1,] -0.86309623 -0.2103872  0.4591319
[2,] -0.01433631 -0.8985285 -0.4386811
[3,] -0.50483598  0.3852062 -0.7725003

which is not as much different (but still quite different) from 

adeflate.C$W
            [,1]       [,2]       [,3]
[1,] -0.83111268  0.2247869  0.5086478
[2,] -0.01217191  0.9070906 -0.4207594
[3,] -0.55597085 -0.3558897 -0.7511584

What is the problem? Am I assuming something here that i should not in
my inputs?

Many thanks again for any help!

Best wishes,
Ranjan






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