For minimization, the inversion of the matrices in these formulas is done so that negative eigenvalues are considered zero, resulting always in a positive semidefinite covariance matrix. In small ...
Solving for the covariance matrix gives a list of eigenvalues and eigenvectors—the leading eigenvectors represent directions of maximum variability, and associated eigenvalues represent the ...
If you do not specify the COVSING= option, the nr smallest eigenvalues are set to zero, where nr is the number of rank deficiencies found in the first step. For optimization techniques that do not use ...