Hello,

I would like to do a pca with princomp.

I have a dataset with different observations for each row and for different
variables for each column (test.z). If I understood it correctly this is
the way the data should be structured for princomp.  But it does not work.
But if I transpose the matrix (test.t - see below) it works.


test.z[1:3,1:6]
  rs1291584 rs3737728 rs6687776 rs9651273 rs4970405 rs12726255
1  1.058438  3.175315 -3.704534 -3.439924 -2.116876  -2.381486
2 -6.879848 -4.762972  4.233753 -3.439924 -2.116876  -2.381486
3 -6.879848 -4.762972  4.233753 -3.439924 -2.116876  -2.381486
> prc <- princomp (test.z)
Fehler in princomp.default(test.z) :
  'princomp' kann nur mit mehr Einheiten als Variablen genutzt werden

After tranposing the matrix - it works.
Transposed matrix:
> test.t <- t (test.z)
> prc <- princomp (test.t)
> prc
Call:
princomp(x = test.t) etc

The error message might give the answer: I understand it like this: You
need more obsvervations than variables. Does this make sense?

Thanks for some hints
hermann


dput (test.z)
structure(c(1.05843820744527, -6.87984834839428, -6.87984834839428,
-6.87984834839428, 8.99672476328483, 8.99672476328483, -6.87984834839428,
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