[R] (no subject) (was: Permutations)
Robin Hankin
rksh at soc.soton.ac.uk
Wed Jul 14 10:11:48 CEST 2004
Jordi
try this
R> x <- c(1,2,3, 10,11,12, 41,42,43, 81,82,83)
R> dim(x) <- c(3,4)
R> x
[,1] [,2] [,3] [,4]
[1,] 1 10 41 81
[2,] 2 11 42 82
[3,] 3 12 43 83
R> jj <- t(apply(x,1,sample))
R> jj
[,1] [,2] [,3] [,4]
[1,] 1 41 10 81
[2,] 2 11 82 42
[3,] 12 3 43 83
R> as.vector(jj)
R>
[1] 1 2 12 41 11 3 10 82 43 81 42 83
and I think that does what you want...
We take the vector, rearrange it into a matrix with three rows, then
sample *within* the rows,
then rearrange into a vector again.
There will be one forbidden permutation, namely the identity (which
may or may not be
desirable).
This method doesn't allow "intra block" permutations.
best
rksh
> Dear R users,
> First of all, thanks for the incredibly fast answers and help of
>Rolf, Marc and Robert.
> Yes, I noticed that it was a lot of permutacions, but my intention
>was to make this process automatic and take only 5.000 - 10.000
>permutations. Therefore, I wanted only to take that "interesting
>permutations" with "some information" [inter-block permutations].
> The reason why I'm interested in these permutations is because I'm
>using some packages of Bioconductor to analyse my data from some
>microarrays and I thought that perhaps could be interesting to see
>what happens when I permute my data and I compare it against the not
>permuted data.
> Thanks again for your time and suggestions.
>
>Jordi Altirriba
>Ph. D. Student
>
>Hospital Clinic-Barcelona-Spain
>
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--
Robin Hankin
Uncertainty Analyst
Southampton Oceanography Centre
SO14 3ZH
tel +44(0)23-8059-7743
initialDOTsurname at soc.soton.ac.uk (edit in obvious way; spam precaution)
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