Abstract
We show that it is possible for every non-diagonalizable stochastic 3 × 3 matrix to
be perturbed into a diagonalizable stochastic matrix with the eigenvalues, arbitrarily close to the eigenvalues of the original matrix, with the same principal eigenspaces. An algorithm is presented to determine a perturbation matrix, which preserves these spectral properties. Additionally, a relation is proved between the eigenvectors and generalized eigenvectors of the original matrix and the perturbed matrix.
be perturbed into a diagonalizable stochastic matrix with the eigenvalues, arbitrarily close to the eigenvalues of the original matrix, with the same principal eigenspaces. An algorithm is presented to determine a perturbation matrix, which preserves these spectral properties. Additionally, a relation is proved between the eigenvectors and generalized eigenvectors of the original matrix and the perturbed matrix.
| Original language | English |
|---|---|
| Article number | 108633 |
| Journal | Statistics and Probability Letters |
| Volume | 157 |
| DOIs | |
| Publication status | Published - Feb 2020 |
Keywords
- Stochastic matrices; Non-diagonalizable matrices; Perturbation theory; Markov chains
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