"pca"(x, use.svd = TRUE, ...)
dccm or enma2covs. Calculate the principal components of an array of correlation or covariance matrices.
This function performs PCA of symmetric matrices, such as distance matrices from an ensemble of crystallographic structures, residue-residue cross-correlations or covariance matrices derived from ensemble NMA or MD simulation replicates, and so on. The ‘upper triangular’ region of the matrix is regarded as a long vector of random variables. The function returns M eigenvalues and eigenvectors with each eigenvector having the dimension N(N-1)/2, where M is the number of matrices and N the number of rows/columns of matrices.
pca.xyz.
Grant, B.J. et al. (2006) Bioinformatics 22, 2695--2696.