Hello everybody,
I'm handling a matrix dataset composed by a number of variables much higher than the objects (900 vs 100) and performing a prcomp (centered and scaled) PCA on it. What I get is a Loadings (rotation) matrix limited by my lower number of objects and thus 900x100 instead of 900x900. If I try to manually calculate the matrix scores multiplying the original variables (centered and scaled) for such a loadings matrix I cannot obtain the same values calculated by R and stored on the prcomp$x matrix (100x100). If I repeat the same with a dataset matrix where the number of variables is lower than the number of objects my manual calculation works perfectly and I get the same results of the prcomp$x scores matrix. Can someone help me to find a way to manual calculate the scores in the first case? Where is the difference in the calculation if in the second case everything works?
Thanks a lot,
Francesco Savorani. 
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