F.Tusell wrote:
In comparing the results of princomp and prcomp I find:
1. The reported standard deviations are similar but about 1% from
each other, which seems well above round-off error.
2. princomp returns what I understand are variances and cumulative
variances accounted for by each principal component which are
all equal. "SS loadings" is always 1.
3. Same happens after the loadings are varimax-rotated, which in
general should alter the proportions of variance accounted by
each component.
It looks as if the loadings() function were expecting the eigenvectors
to be normalized to the corresponding eigenvalue.
Transcript and version information follow signature. Thank you for any
clues.
Did you read the corresponding help files?
from ?prcomp:
<quote>
Details:
The calculation is done by a singular value decomposition of the
(centered and possibly scaled) data matrix, not by using 'eigen'
on the covariance matrix. This is generally the preferred method
for numerical accuracy.
</quote>
from ?princomp:
<quote>
Details:
The calculation is done using 'eigen' on the correlation or
covariance matrix, as determined by 'cor'. This is done for
compatibility with the S-PLUS result. A preferred method of
calculation is to use 'svd' on 'x', as is done in 'prcomp'.
</quote>
HTH,
--sundar
______________________________________________
[EMAIL PROTECTED] mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
