The second principal component is
with variance
We need to maximize this variance subject to the normalizing constraint a’2a2= 1 and the orthogonality constraint w’1w2= 0. Show that the orthogonality constraint is equivalent to a’1a2= 0. Then, using two Lagrange multipliers, one for the normalizing constraint and the other for the orthogonality constraint, show that a2is an eigenvector corresponding to the second-largest eigenvalue of RXX. Explain how this procedure can be extended to derive the remaining k ' 2 principal components.
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