Journal of Applied Probability

Bounded truncation error for long-run averages in infinite Markov chains

Hendrik Baumann and Werner Sandmann

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We consider long-run averages of additive functionals on infinite discrete-state Markov chains, either continuous or discrete in time. Special cases include long-run average costs or rewards, stationary moments of the components of ergodic multi-dimensional Markov chains, queueing network performance measures, and many others. By exploiting Foster-Lyapunov-type criteria involving drift conditions for the finiteness of long-run averages we determine suitable finite subsets of the state space such that the truncation error is bounded. Illustrative examples demonstrate the application of this method.

Article information

J. Appl. Probab., Volume 52, Number 3 (2015), 609-621.

First available in Project Euclid: 22 October 2015

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Zentralblatt MATH identifier

Primary: 60J22: Computational methods in Markov chains [See also 65C40]
Secondary: 60J10: Markov chains (discrete-time Markov processes on discrete state spaces) 60J27: Continuous-time Markov processes on discrete state spaces 60J28: Applications of continuous-time Markov processes on discrete state spaces

Infinite Markov chain additive functional long-run average state space truncation bounded truncation error Foster-Lyapunov-type criterion drift condition


Baumann, Hendrik; Sandmann, Werner. Bounded truncation error for long-run averages in infinite Markov chains. J. Appl. Probab. 52 (2015), no. 3, 609--621. doi:10.1239/jap/1445543835.

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