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Representations for the Decay Parameter of a Birth-Death Process Based on the Courant-Fischer Theorem

Published online by Cambridge University Press:  30 January 2018

Erik A. van Doorn*
Affiliation:
University of Twente
*
Postal address: Department of Applied Mathematics, University of Twente, PO Box 217, 7500 AE Enschede, The Netherlands. Email address: e.a.vandoorn@utwente.nl
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Abstract

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We study the decay parameter (the rate of convergence of the transition probabilities) of a birth-death process on {0, 1, …}, which we allow to evanesce by escape, via state 0, to an absorbing state -1. Our main results are representations for the decay parameter under four different scenarios, derived from a unified perspective involving the orthogonal polynomials appearing in Karlin and McGregor's representation for the transition probabilities of a birth-death process, and the Courant-Fischer theorem on eigenvalues of a symmetric matrix. We also show how the representations readily yield some upper and lower bounds that have appeared in the literature.

Type
Research Article
Copyright
© Applied Probability Trust 

References

Callaert, H. (1974). On the rate of convergence in birth-and-death processes. Bull. Soc. Math. Belg. 26, 173184.Google Scholar
Chen, M.-F. (1991). Exponential L2-convergence and L2-spectral gap for Markov processes. Acta Math. Sinica (N.S.) 7, 1937.Google Scholar
Chen, M.-F. (2000). Explicit bounds of the first eigenvalue. Sci. China Ser. A 43, 10511059.CrossRefGoogle Scholar
Chen, M.-F. (2005). Eigenvalues, Inequalities, and Ergodic Theory. Springer, London.Google Scholar
Chen, M.-F. (2010). Speed of stability for birth–death processes. Front. Math. China 5, 379515.CrossRefGoogle Scholar
Chihara, T. S. (1968). On indeterminate Hamburger moment problems. Pacific J. Math. 27, 475484.CrossRefGoogle Scholar
Chihara, T. S. (1978). An Introduction to Orthogonal Polynomials. Gordon and Breach, New York.Google Scholar
Chihara, T. S. (1982). Indeterminate symmetric moment problems. J. Math. Anal. Appl. 85, 331346.CrossRefGoogle Scholar
Karlin, S. and McGregor, J. L. (1957). The differential equations of birth-and-death processes, and the Stieltjes moment problem. Trans. Amer. Math. Soc. 85, 489546.CrossRefGoogle Scholar
Karlin, S. and McGregor, J. L. (1957). The classification of birth and death processes. Trans. Amer. Math. Soc. 86, 366400.CrossRefGoogle Scholar
Meyer, C. (2000). Matrix Analysis and Applied Linear Algebra. SIAM, Philadelphia, PA. Updates available at http://www.matrixanalysis.com.CrossRefGoogle Scholar
Miclo, L. (1999). An example of application of discrete Hardy's inequalities. Markov Process. Relat. Fields 5, 319330.Google Scholar
Sirl, D., Zhang, H. and Pollett, P. (2007). Computable bounds for the decay parameter of a birth–death process. J. Appl. Prob. 44, 476491.CrossRefGoogle Scholar
van Doorn, E. A. (1985). Conditions for exponential ergodicity and bounds for the decay parameter of a birth–death process. Adv. Appl. Prob. 17, 514530.CrossRefGoogle Scholar
van Doorn, E. A. (1987). The indeterminate rate problem for birth–death processes. Pacific J. Math. 130, 379393.CrossRefGoogle Scholar
van Doorn, E. A. and Pollett, P. K. (2013). Quasi-stationary distributions for discrete-state models. Europ. J. Operat. Res. 230, 114.CrossRefGoogle Scholar
van Doorn, E. A. and Zeifman, A. I. (2009). On the speed of convergence to stationarity of the Erlang loss system. Queueing Systems 63, 241252.CrossRefGoogle Scholar