This paper extends the Markov uni-chain series expansion theory to Markov multi-chains, i.e., to Markov chains having multiple ergodic classes and possible transient states. The introduced series expansion approximation (SEA) provides a controllable approximation for Markov multichain ergodic projectors which may be a useful tool in large-scale network analysis. As we will illustrate by means of numerical examples, the new algorithm is faster than the power algorithm for large networks.
Bibliographical noteProceedings title: International Conference On Computational Science, ICCS 2015 — Computational Science at the Gates of Nature
Place of publication: New York