the eigenvalues equal the variances of the covariance matrix and the eigenvectors are equal to the definition of the x-axis and y-axis. In the case of arbitrary correlated data, the eigenvectors represent the direction of the largest spread of the data, whereas the eigenvalues define how large...
We let E be the q × q matrix whose columns are the eigenvectors corresponding to the eigenvalues. (iii) Then E T X r s : t T X r s : t E = D λ , where D λ is the diagonal matrix of the eigenvalues λ i , stored in vector λ , and E T E = E E T = I , where...