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. [[alternative HTML version deleted]]
______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.