Abstract
Abstract 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 multi-chain 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.
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