weird results w/ prcomp-princomp

R2.0.1
x<-matrix(rnorm(44*19),nrow=44)
princomp(x,cor=TRUE,scores=TRUE)
Call:
princomp(x = x, cor = TRUE, scores = TRUE)

Standard deviations:
   Comp.1    Comp.2    Comp.3    Comp.4    Comp.5    Comp.6    Comp.7    Comp.8
1.5874672 1.4652217 1.3088833 1.2339949 1.1697727 1.1402570 1.0774402 1.0458567
   Comp.9   Comp.10   Comp.11   Comp.12   Comp.13   Comp.14   Comp.15   Comp.16
1.0152164 0.9403912 0.8854087 0.8433314 0.7918201 0.7454395 0.6680463 0.6240805
  Comp.17   Comp.18   Comp.19
0.5752994 0.4873633 0.4205193

 19  variables and  44 observations.
sum(princomp(x,cor=TRUE,scores=TRUE)$sdev^2)
[1] 19

it seems ok. 
On Fri, 08 Apr 2005 11:12:26 +0200

I am doing a Principal Component Analaysis (PCA) on a 44x19 matrix.
with
 > princomp(x,cor=TRUE,scores=TRUE)
and
 > prcomp(x,scale=TRUE,center=TRUE)
The resulted eigenv. and rotated matrix are the same (as expected), however 
the sum of eigenvalues is lower than 19 (number of variables).

With a commercial stat software it worked correctly, with the same dataset.
Am I doing something wrong?
Thanks
Alex

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weird results w/ prcomp-princomp

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