The purpose of principal component analysis is to derive a small number of independent linear combinations (principal components) of a set of variables that retain as much of the information in the ...

For a covariance or correlation matrix, the sum of its eigenvalues equals the trace of the matrix, that is, the sum of the variances of the n y variables for a covariance matrix, and n y for a ...