¥The optimisation problem which defines PCs turns out, like many in
multivariate analysis, to be an eigenvalue problem
¥The variances of the PCs are eigenvalues of the covariance (or correlation)
matrix of x, in descending order, and the
vectors of coefficients ak are the
corresponding eigenvectors
¥This is the usual way of finding PCs, though other algorithms exist e.g using
the singular value decomposition of the
column-centred data matrix
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