[R] prcomp

[carol white]

Hi,
If center=T (by default) in invoking prcomp, that is, prcomp (x) where x is a matrix with the observations are in rows and the variables are in column, is this equivalent to scale(t(x),center=T,scale=F) where x is a matrix with the observations are in rows and the variables are in columns?

Additionally, could you advise when the variables should mean centered (center = T in prcomp) before the application of PCA? According to the documentation of prcomp, the variables and I assume not the observations are mean-centered if center = T. 

I have a discrete data containing 0, 1 and 2. Should I mean center the variables (center = T in prcomp)? See the histogram in attachment. When I don't mean center, the first PC captures 91% of variability. and when I mean center, the first PC captures 1% of variability, see the proportion of variation:

non-mean centered variables:
                             PC1      PC2      PC3
Standard deviation     259.42437 11.12854 6.865225
Proportion of Variance   0.91282  0.00168 0.000640
Cumulative Proportion    0.91282  0.91450 0.915140

mean-centered variables:
                            PC1      PC2     PC3
Standard deviation     11.30053 6.870346 5.64987
Proportion of Variance  0.01985 0.007340 0.00496
Cumulative Proportion   0.01985 0.027190 0.03215


Thanks in advance,

Carol