On Aug 17, 2011, at 5:47 PM, David Winsemius wrote:
On Aug 17, 2011, at 5:19 PM, Rosario Garcia Gil wrote:
Hello
I am trying to run a PCA on the attached file, but I get this error
message:
pc<-prcomp(data[,-(1:2)],scale=T)$x
Error in svd(x, nu = 0) : infinite or missing values in 'x'
What part of "missing values in 'x'" is unclear in that error message?
After looking further at the prcomp defaults I see that na.action
defaults to na.omit so it may not be the missing data, but rather
collinearity. Do these plotting and descriptive steps to see that your
data is extremely clustered:
matplot(dat[,-(1:2)] )
pairs(dat[-(1:2)])
summary(dat[-(1:2)])
So the effort to invert the data matrix is probably failing due to the
application of inappropriate data reduction to variables which, though
nominally numeric, are really categorical, and fairly strangely
distributed ones at that. Also not this advice in ?prcomp:
"Note that scale = TRUE cannot be used if there are zero or constant
(for center = TRUE) variables." I cpunt four variables that violate
that restriction. But removing scale=T still does not fix the problem.
--
David Winsemius, MD
West Hartford, CT
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