perl module for principal component analysis (PCA)

 Statistics::PCA provides functions for principal component analysis (PCA).
 PCA transforms higher-dimensional data consisting of a number of possibly
 correlated variables into a smaller number of uncorrelated variables termed
 principal components (PCs). The higher the ranking of the PCs the greater the
 amount of variability that the PC accounts for.
 .
 This PCA procedure involves the calculation of the eigenvalue decomposition
 from a data covariance matrix after mean centering the data.
 .
 See https://en.wikipedia.org/wiki/Principal_component_analysis