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Almost sure convergence in Markov branching processes with infinite mean

Published online by Cambridge University Press:  14 July 2016

D. R. Grey
D. R. Grey*
Affiliation:
University of Sheffield
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Abstract

If {Zn} is a Galton–Watson branching process with infinite mean, it is shown that under certain conditions there exist constants {cn} and a function L, slowly varying at 0, such that converges almost surely to a non-degenerate random variable, whose distribution function satisfies a certain functional equation. The method is then extended to a continuous-time Markov branching process {Zt} with infinite mean, where it is shown that there is always a function φ, slowly varying at 0, such that converges almost surely to a non-degenerate random variable, and a necessary and sufficient condition is given for this convergence to be equivalent to convergence of for some constant α > 0.

Keywords

GALTON-WATSON PROCESSMARKOV BRANCHING PROCESSINFINITE MEANALMOST SURE CONVERGENCEMARTINGALESCONTINUOUS-TIME MARTINGALESSLOWLY VARYING FUNCTIONSFUNCTIONAL EQUATIONS

Information

Type
Research Papers
Information
Journal of Applied Probability , Volume 14 , Issue 4 , December 1977 , pp. 702 - 716
Copyright
Copyright © Applied Probability Trust 1977 

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