Iterative bounds on the equilibrium distribution of a finite Markov chain

J. Wal, van der; P.J. Schweitzer

doi:10.1017/S0269964800000334

Iterative bounds on the equilibrium distribution of a finite Markov chain

J. Wal, van der, P.J. Schweitzer

Stochastic Operations Research

Research output: Contribution to journal › Article › Academic › peer-review

7 Citations (Scopus)

Abstract

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.

Original language	English
Pages (from-to)	117-131
Journal	Probability in the Engineering and Informational Sciences
Volume	1
Issue number	1
DOIs	https://doi.org/10.1017/S0269964800000334
Publication status	Published - 1987

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AB - 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.

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Iterative bounds on the equilibrium distribution of a finite Markov chain

Abstract

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