PCA1.1PCA performs a principal component analysis on a given data matrix based on eigen values.Minna MiettinenVille RantanenMultivariate StatisticsThe data matrix on which PCA is applied.A logical value indicating whether the variables should be shifted to be zero centered. Centering is recommended; Mean subtraction (a.k.a. "mean centering") is necessary for performing PCA to ensure that the first principal component describes the direction of maximum variance. If mean subtraction is not performed, the first principal component will instead correspond to the mean of the data.
A logical value indicating whether the variables should be scaled to have unit variance before the analysis takes place. In general, scaling is advisable.
Direction of the summarization i.e. should PCA be applied row- or column-wise. The possible values are "column" and "row".Seed number for the pseudo random number generator