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Iterative Bounds on the Equilibrium Distribution of a Finite Markov Chain

Published online by Cambridge University Press:  27 July 2009

Jan Van Der Wal
Affiliation:
Department of Mathematics and Computing ScienceUniversity of Technology Eindhoven, The Netherlands
Paul J. Schweitzer
Affiliation:
William E. Simon Graduate School of Business Administration University of Rochester Rochester, New York

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.

Type
Articles
Copyright
Copyright © Cambridge University Press 1987

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