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A Galton–Watson process with a threshold

Published online by Cambridge University Press:  21 June 2016

K. B. Athreya*
Affiliation:
Iowa State University
H.-J. Schuh*
Affiliation:
Johannes Gutenberg-Universität
*
* Postal address: Departments of Mathematics and Statistics, Iowa State University, Ames, IA 50010, USA. Email address: [email protected]
** Postal address: Fachbereich 8, Physik, Mathematik und Informatik, Johannes Gutenberg-Universität, D-55099 Mainz, Germany. Email address: [email protected]

Abstract

In this paper we study a special class of size dependent branching processes. We assume that for some positive integer K as long as the population size does not exceed level K, the process evolves as a discrete-time supercritical branching process, and when the population size exceeds level K, it evolves as a subcritical or critical branching process. It is shown that this process does die out in finite time T. The question of when the mean value E(T) is finite or infinite is also addressed.

Type
Short Communications
Copyright
Copyright © Applied Probability Trust 2016 

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References

[1]Athreya, K. B. and Ney, P. E. (1972).Branching Processes.Springer, New York.Google Scholar
[2]Eisenberg, B. (2008).On the expectation of the maximum of IID geometric random variables.Statist. Prob. Lett. 78, 135143.Google Scholar
[3]Jagers, P. (1996).Population-size-dependent branching processes.J. Appl. Math. Stoch. Anal. 9, 449457.Google Scholar
[4]Klebaner, F. C. (1984).Geometric rate of growth in population size dependent branching processes.J. Appl. Prob. 21, 4049.CrossRefGoogle Scholar
[5]Klebaner, F. C. (2010).Approximation in population-size-dependent branching processes. In Workshop on branching processes and their applications (Lecture Notes Statist. Proc.197), pp.7178.Google Scholar
[6]Seneta, E. (1967).The Galton–Watson process with mean one.J. Appl. Prob. 4, 489495.Google Scholar
[7]Slack, E. (1968).A branching process with mean one and possibly infinite variance.Z. Wahrscheinlichkeitsth. 9, 139145.CrossRefGoogle Scholar