Journal of Applied Probability
- J. Appl. Probab.
- Volume 52, Number 3 (2015), 609-621.
Bounded truncation error for long-run averages in infinite Markov chains
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.
J. Appl. Probab., Volume 52, Number 3 (2015), 609-621.
First available in Project Euclid: 22 October 2015
Permanent link to this document
Digital Object Identifier
Mathematical Reviews number (MathSciNet)
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
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. https://projecteuclid.org/euclid.jap/1445543835