Annals of Probability

Asymptotic Growth of Controlled Galton-Watson Processes

Petra Kuster

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The almost sure growth behavior of some time-homogeneous Markov chains is studied. They generalize the ordinary Galton-Watson processes with regard to allowing state-dependent offspring distributions and also to controlling the number of reproducing individuals by a random variable that depends on the state of the process. The main assumption is that the mean offspring per individual is nonincreasing while the state increases. These controlled Galton-Watson processes can be included in a general growth model whose divergence rate is determined. In case of processes that differ from the Galton-Watson process only by the state dependence of the offspring distributions, a necessary and sufficient moment condition for divergence with "natural" rate is obtained generalizing the $(x \log x)$ condition of Galton-Watson processes. In addition, some criteria are given when a state-dependent Galton-Watson process behaves like an ordinary supercritical Galton-Watson process.

Article information

Ann. Probab., Volume 13, Number 4 (1985), 1157-1178.

First available in Project Euclid: 19 April 2007

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Primary: 60J80: Branching processes (Galton-Watson, birth-and-death, etc.)
Secondary: 60F15: Strong theorems 60J10: Markov chains (discrete-time Markov processes on discrete state spaces)

Galton-Watson process state-dependent offspring distribution $\varphi$-controlled branching process population-size-dependent branching process growth model growth rate


Kuster, Petra. Asymptotic Growth of Controlled Galton-Watson Processes. Ann. Probab. 13 (1985), no. 4, 1157--1178. doi:10.1214/aop/1176992802.

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