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Weak convergence of conditioned birth and death processes

Published online by Cambridge University Press:  14 July 2016

G. O. Roberts*
Affiliation:
University of Cambridge
S. D. Jacka*
Affiliation:
University of Warwick
*
Postal address: Statistical Laboratory, 16 Mill Lane, Cambridge CB2 1SB, UK.
∗∗ Postal address: Department of Statistics, University of Warwick, Coventry CV4 7AL, UK.

Abstract

We consider the problem of conditioning a non-explosive birth and death process to remain positive until time T, and consider weak convergence of this conditional process as T → ∞. By a suitable almost sure construction we prove weak convergence. The almost sure construction used is of independent interest but relies heavily on the strong monotonic properties of birth and death processes.

Type
Research Papers
Copyright
Copyright © Applied Probability Trust 1994 

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References

Darroch, J. N. and Seneta, E. (1967) On quasi-stationary distributions in absorbing continuous-time finite Markov chains. J. Appl. Prob. 4, 192196.Google Scholar
Gibson, D. and Seneta, E. (1989) Monotone infinite stochastic matrices and their augmented truncations. Stoch. Proc. Appl. 24, 287292.Google Scholar
Jacka, S. D. and Roberts, G. O. (1987) Conditional diffusions: their infinitesimal generators and limit laws. Warwick University, Department of Statistics, Research Report No. 127.Google Scholar
Jacka, S. D. and Roberts, G. O. (1992a) Strong forms of weak convergence. Warwick University, Department of Statistics, Research Report No. 243.Google Scholar
Jacka, S. D. and Roberts, G. O. (1992b) Weak convergence of conditioned processes on a countable state space. Research Report 255, Department of Statistics, University of Warwick.Google Scholar
Karlin, S. (1968) Total Positivity, Vol. 1. Stanford University Press.Google Scholar
Karlin, S. and Mcgregor, J. (1959) Coincident probabilities. Proc. J. Maths. 9, 11411164.Google Scholar
Pinsky, R. G. (1985) On the convergence of diffusion processes conditioned to remain in a bounded region for a large time to limiting positive recurrent diffusion processes. Ann. Prob. 13, 363378.Google Scholar
Pollak, ?. and Siegmund, D. (1986) Convergence of quasi-stationary distributions for stochastically monotone Markov processes. J. Appl. Prob. 23, 215220.Google Scholar
Roberts, G. O. (1991a) A comparison theorem for conditioned Markov processes. J. Appl. Prob. 28, 7483.Google Scholar
Roberts, G. O. (1991b) Asymptotic approximations for Brownian motion boundary hitting times. Ann. Prob. 19, 16891731.Google Scholar
Seneta, E. (1981) Non-negative Matrices and Markov Chains, 2nd edn. Springer-Verlag, New York.Google Scholar
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, 403434.Google Scholar
Shortland, C. F. and Roberts, G. O. (1993) Strong stochastic ordering of Markov processes. In preparation.Google Scholar