Hostname: page-component-586b7cd67f-r5fsc Total loading time: 0 Render date: 2024-11-22T23:43:49.308Z Has data issue: false hasContentIssue false

Limiting Conditional Distributions for Birthdeath Processes

Published online by Cambridge University Press:  01 July 2016

M. Kijima*
Affiliation:
University of Tsukuba
M. G. Nair*
Affiliation:
Curtin University of Technology
P. K. Pollett*
Affiliation:
University of Queensland
E. A. Van Doorn*
Affiliation:
University of Twente
*
Postal address: Graduate School of Systems Management, University of Tsukuba, Tokyo 112, Japan.
∗∗ Postal address: School of Mathematics and Statistics, Curtin University of Technology, Perth, WA 6001, Australia.
∗∗∗ Postal address: Department of Mathematics, University of Queensland, QLD 4072, Australia.
∗∗∗∗ Postal address: Faculty of Applied Mathematics, University of Twente, PO Box 217, 7500 AE Enschede, The Netherlands.

Abstract

In a recent paper [16], one of us identified all of the quasi-stationary distributions for a non-explosive, evanescent birth-death process for which absorption is certain, and established conditions for the existence of the corresponding limiting conditional distributions. Our purpose is to extend these results in a number of directions. We shall consider separately two cases depending on whether or not the process is evanescent. In the former case we shall relax the condition that absorption is certain. Furthermore, we shall allow for the possibility that the minimal process might be explosive, so that the transition rates alone will not necessarily determine the birth-death process uniquely. Although we shall be concerned mainly with the minimal process, our most general results hold for any birth-death process whose transition probabilities satisfy both the backward and the forward Kolmogorov differential equations.

Type
General Applied Probability
Copyright
Copyright © Applied Probability Trust 1997 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

[1] Anderson, W. J. (1991) Continuous-Time Markov Chains-An Applications-Oriented Approach. Springer, New York.Google Scholar
[2] Chihara, T. S. (1978) An Introduction to Orthogonal Polynomials. Gordon and Breach, New York.Google Scholar
[3] Elmes, S., Pollett, P. K. and Walker, D. M. (1994) Further results on the relationship between µ-invariant measures and quasistationary distributions for continuous-time Markov chains. Statistics Research Report. University of Queensland.Google Scholar
[4] Ferrari, P. A., Kesten, H., Martínez, S. and Picco, P. (1995) Existence of quasi-stationary distributions. A renewal dynamical approach. Ann. Prob. 23, 501521.Google Scholar
[5] Flaspohler, D. C. (1974) Quasi-stationary distributions for absorbing continuous-time denumerable Markov chains. Ann. Inst. Statist. Math. 26, 351356.Google Scholar
[6] 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.Google Scholar
[7] Karlin, S. and Mcgregor, J. L. (1957) The classification of birth and death processes. Trans. Amer. Math. Soc. 86, 366400.Google Scholar
[8] Kijima, M. and Seneta, E. (1991) Some results for quasi-stationary distributions of birth-death processes. J. Appl. Prob. 28, 503511.Google Scholar
[9] Kijima, M. and Van Doorn, E. A. (1995) Weighted sums of orthogonal polynomials with positive zeros. J. Comput. Appl. Math. 65, 195206.Google Scholar
[10] Nair, M. G. and Pollett, P. K. (1993) On the relationship between µ-invariant measures and quasistationary distributions for continuous-time Markov chains. Adv. Appl. Prob. 25, 82102.Google Scholar
[11] Pakes, A. G. (1995) Quasi-stationary laws for Markov processes: examples of an always proximate absorbing state. Adv. Appl. Prob. 27, 120145.Google Scholar
[12] Pollett, P. K. (1988) Reversibility, invariance and µ-invariance. Adv. Appl. Prob. 20, 600621.Google Scholar
[13] 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.Google Scholar
[14] Van Doorn, E. A. (1986) On orthogonal polynomials with positive zeros and the associated kernel polynomials. J. Math. Anal. Appl. 113, 441450.Google Scholar
[15] Van Doorn, E. A. (1987) The indeterminate rate problem for birth-death processes. Pacific J. Math. 130, 379393.Google Scholar
[16] Van Doorn, E. A. (1991) Quasi-stationary distributions and convergence to quasi-stationarity of birth-death processes. Adv. Appl. Prob. 23, 683700.Google Scholar
[17] Vere-Jones, D. (1969) Some limit theorems for evanescent processes. Austral. J. Statist. 11, 6778.Google Scholar