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A Markov chain associated with the minimal quasi-stationary distribution of birth–death chains

Published online by Cambridge University Press:  14 July 2016

Servet Martínez*
Affiliation:
Universidad de Chile
Maria Eulália Vares*
Affiliation:
Instituto de Matemática Pura e Aplicada, Rio de Janeiro
*
Postal address: Departamento de Ingeniería Matemática, Universidad de Chile, Casilla 170–3 Correo 3, Santiago, Chile.
∗∗Postal address: Instituto de Matemática Pura e Aplicada, Estrada Dona Castorina 110, Jardîm Botânico, 22460 Rio de Janeiro, Brasil.

Abstract

We show that if the limiting conditional distribution for an absorbed birth–death chain exists, then the chain conditioned to non-absorption converges to a Markov chain with transition probabilities given by the matrix associated with the minimal quasi-stationary distribution.

Type
Research Papers
Copyright
Copyright © Applied Probability Trust 1995 

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References

[1] Ferrari, P., Martínez, S. and Picco, P. (1991) Some properties of quasi-stationary distributions in the birth-death chains: a dynamical approach. In Instabilities and Non-Equilibrium Structures III, pp. 177187. Kluwer, Dordrecht.Google Scholar
[2] Ferrari, P., Martínez, S. and Picco, P. (1992) Existence of quasi-stationary distributions for birth-death chains. Adv. Appl. Prob. 24, 795813.CrossRefGoogle Scholar
[3] Ferrari, P., Kesten, H., Martínez, S. and Picco, P. (1993) Existence of quasi-stationary distributions. A renewal dynamical approach. Ann. Prob. To appear.Google Scholar
[4] Keener, R. W. (1992) Limit theorems for random walks conditioned to stay positive. Ann. Prob. 20, 801824.Google Scholar
[5] Kesten, H. (1995) A ratio limit theorem for (sub)Markov chains on {1, 2, …} with bounded jumps. Adv. Appl. Prob. 27(3).Google Scholar
[6] Martínez, S. (1993) Quasi-stationary distributions for birth-death chains, cellular automata and cooperative systems. NATO ASI Series, pp. 491505. Kluwer, Dordrecht.Google Scholar
[7] Pakes, A. G. (1995) Quasi-stationary laws for Markov processes: examples of an always approximate absorbing state. Adv. Appl. Prob. 27, 120145.Google Scholar
[8] Roberts, G. O. and Jacka, S. D. (1994) Weak convergence of conditioned birth and death processes. J. Appl. Prob. 31, 90100.Google Scholar
[9] Seneta, E. (1973) Non-Negative Matrices and Markov Chains. Springer-Verlag, New York.Google Scholar
[10] Seneta, E. and Vere-Jones, D. (1966) On quasi-stationary distributions in discrete-time Markov chains with a denumerable infinity of states. J. Appl. Prob. 3, 404434.Google Scholar
[11] Van Doorn, E. and Schrijner, P. (1992) Geometric ergodicity, quasi-stationary and ratio limits for random walks. Preprint, University of Twente.Google Scholar
[12] Vere-Jones, D. (1962) Geometric ergodicity in denumerable Markov chains. Quart. J. Math. Oxford (2)13, 728.Google Scholar