R help - Jul 2008 - fastICA

Hi everyone

It looks like repeated runs of fastICA produce quite significantly different
mixing matrices (not only in terms of sign and row order). I'm not a
specialist, so would appreciate any advice on whether this should really be
the case:
> res3 >
fastICA(af[,2:20],4,alg.typ="parallel",fun="logcosh",alpha=1,method="C",row.norm=TRUE)
colstandard
> res4 >
fastICA(af[,2:20],4,alg.typ="parallel",fun="logcosh",alpha=1,method="C",row.norm=TRUE)
colstandard
> res3$A
          [,1]       [,2]       [,3]       [,4]       [,5]       [,6]      
[,7]       [,8]       [,9]        [,10]       [,11]      [,12]
[1,] 0.3492656 0.47129703 0.11709867 -0.3866225 -0.3180731 -0.4991164 
0.6215495  0.8923775  0.5595437 -0.074976310 -0.02226736  0.2540303
[2,] 0.3374660 0.39962068 0.24130395 -0.4555433 -0.2731303 -0.4717878
-0.1361462 -0.1812964 -0.4349231  0.001598010  0.05622615  0.3771093
[3,] 0.1577214 0.06431248 0.04530352  0.2426606  0.2546012  0.3607750 
0.3066278  0.2459179 -0.1632415  0.079017073 -0.01756727 -0.6831387
[4,] 0.3024079 0.42547482 0.42272925  0.4219971  0.1849393  0.3102353
-0.2709699 -0.2480479 -0.2029552  0.186288059 -0.03772351  0.2284498
          [,13]      [,14]      [,15]       [,16]        [,17]       [,18]      
[,19]
[1,] -0.3560465 -0.8023760 -0.6901401 -0.09377930  0.039225519  0.01019511
-0.07118729
[2,] -0.1333961  0.3828090  0.4846588 -0.03412919 -0.009067316 -0.13459846
-0.01677050
[3,] -1.0164242 -0.2774528  0.2472543  0.05641915  0.112881877 -0.10800022 
0.09233623
[4,] -0.1606417 -0.6265621 -0.6120113 -0.08991269 -0.052944720 -0.11545406
-0.06530203
> res4$A
            [,1]        [,2]        [,3]        [,4]        [,5]        [,6]
[,7]        [,8]       [,9]       [,10]       [,11]      [,12]
[1,]  0.37425998  0.47693372  0.43825728  0.06634739  0.01113021  0.00141282
-0.4044253 -0.47496861 -0.5553201  0.14804389  0.01623842  0.3564346
[2,] -0.14173880 -0.04252148 -0.03162973 -0.24141814 -0.25736466 -0.36473238
-0.3000759 -0.23306483  0.1691999 -0.07594278  0.01626331  0.6948413
[3,] -0.05005946 -0.01742712  0.11216921  0.64260942  0.34415960  0.58450365
-0.1146743 -0.08045181  0.1442732  0.13216174 -0.06578838 -0.1372067
[4,] -0.43535000 -0.58086526 -0.21688752  0.34399283  0.29998124  0.47268328
-0.5527654 -0.81536674 -0.4607192  0.03768184  0.02307793 -0.3113437
           [,13]       [,14]       [,15]       [,16]       [,17]       [,18]
[,19]
[1,] -0.14663100 -0.01915221  0.04564954 -0.06653969 -0.04960206 -0.17660055
-0.04146818
[2,]  1.00383413  0.24516021 -0.27622870 -0.06074335 -0.11331305  0.10496803
-0.09549671
[3,] -0.01167087 -0.67320085 -0.73464239 -0.03193329 -0.03025987  0.01552101
-0.02808728
[4,]  0.41733259  0.86385119  0.72718191  0.10995336 -0.03082935  0.02770219 
0.08069126

Many thanks
Mikhail

--
Mikhail Spivakov PhD
Postdoctoral Fellow
European Bioinformatics Institute
European Molecular Biology Laboratory
Hinxton Cambridgeshire CB10 1SD
UK

tel +44 1223 492 260
fax +44 1223 494 468
spivakov ebi ac uk
-- 
View this message in context:
http://www.nabble.com/fastICA-tp18506527p18506527.html
Sent from the R help mailing list archive at Nabble.com.

Is the FastICA R implementation as good as the MatLab Implementation ?
I would appreciate talking to someone who has used FastICA for R.

Thank you very much.

-- 
Maura E.M

	[[alternative HTML version deleted]]

Maura E Monville <maura.monville <at> gmail.com> writes:
> 
> Is the FastICA R implementation as good as the MatLab Implementation ?
> I would appreciate talking to someone who has used FastICA for R.
The fastICA packages for Matlab and R (and there is even a version for Python)
have a common origin at the Helsinki University of Technology. I regularly use
Matlab and R, not seeing much of a difference in packages like these.

//  Hans Werner Borchers
> 
> Thank you very much.
>