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Iterative bounds on the equilibrium distribution of a finite Markov chain. (English) Zbl 1133.60330

Summary: This article presents a new iterative method for computing the equilibrium distribution of a finite Markov chain, which has the significant advantage of providing good upper and lower bounds for the equilibrium probabilities. The method approximates the expected number of visits to each state between two successive visits to a given reference state. Numerical examples indicate that the performance of this method is quite good.

MSC:

60G99 Stochastic processes
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