B.1 Power method with deflation

The power method is a common method to extract the eigenvector with the largest eigenvalue (Diamantaras and Kung, 1996). Starting with a random vector $\bf a$, the principal eigenvector of a matrix $\bf K$ is computed by iterating:

$${\frac{{{\bf K}{\bf a}}}{{\Vert\mbox{max}({\bf K}{\bf a})\Vert}}} \rightarrow \bf a$$ (B.1)

max($\bf K$$\bf a$) is the component of the vector $\bf K$$\bf a$ with the largest absolute value (some variants of the power method use |$\bf a$| instead). This iteration converges to the largest eigenvector with the eigenvalue $\lambda{^\prime}$ = |max($\bf K$$\bf a$)|. Further eigenvectors are obtained using deflation. After the eigenvector $\bf a_{i}^{}$ (number i, ordered by the size of the corresponding eigenvalue) is computed, a new matrix $\bf K_{{i+1}}^{}$ is obtained from the previous one $\bf K_{i}^{}$ by iterating

$$\bf K_{{i+1}}^{} \bf K_{i}^{} \lambda_{i}{^\prime} {\frac{{{\bf a}_i {\bf a}_i^T}}{{{\bf a}_i^T {\bf a}_i}}}$$ (B.2)

where $\lambda_{i}{^\prime}$ is the eigenvalue corresponding to $\bf a_{i}^{}$.