Ok, the mistake was in the pca(x)<-princomp(SampleD[i,j]), should've used
pca(x)<-princomp(SampleD) instead.
Now, is there anyway to keep track of the matrix index, so in the end of all
PCAs, I can tell which score/loading belongs to which sample?
Thanks everyone!
On Mon, Jun 30, 2008 at 9:08 PM, Tanya Yatsunenko <[EMAIL PROTECTED]> wrote:
> Hi all,
>
> I am doing bootstrap on a distance matrix, in which samples have been drawn
> with replacement. After that I do PCA on a resulted matrix, and these 2
> steps are repeated 1000 times.
>
> pca(x) is a vector where I wanted to store all 1000 PCAs; and x is from 1
> to 1000
> SampleD is a new matrix after resampling;
>
> I am getting the following error message, which I don't understand:
> ....
> +pca(x)<-princomp(SampleD[i,j])
> + }
> Error in eigen(cv, symmetric = TRUE) : infinite or missing values in 'x'
>
> Should I maybe not use a vector, but matrix instead?
> Thanks!
>
> --
> Tanya.
>
>
--
Tanya
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