Hi I need to rotate a PCs coming from a Principal Component Analysis. I know I shouldn't but the analysis I'm doing requests this step. I used function rotatefactors() but it does not produce the eingenvalues of the rotated PCs. At the same time I can't use factorian() routine because my covariance matrix is not positive definite. Does anyone have an idea? Thanks!
No products are associated with this question.
On reflection, if you are thinking of the eigenvalues as the variances of the scores, perhaps this is what you want after rotation:
% Eigenvalues are the variances of the scores load hald [C,S,latent] = pca(ingredients); V = cov(ingredients); var(S) % variance of scores latent' % latent values Sigma = eig(V)' % eigenvalues
% Rotate away from the principal components [L,T] = rotatefactors(C(:,1:2));
% Variances of the rotated scores, if we have S var1 = diag(cov(S(:,1:2)*T))'
% Variances computed without using the scores var2 = diag(L'*V*L)'
Play games and win prizes!Learn more