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Maximal branching processes and ‘long-range percolation’

Published online by Cambridge University Press:  14 July 2016

John Lamperti*
Affiliation:
Dartmouth College, Hanover, New Hampshire

Extract

In the first part of this paper, we will consider a class of Markov chains on the non-negative integers which resemble the Galton-Watson branching process, but with one major difference. If there are k individuals in the nth “generation”, and are independent random variables representing their respective numbers of offspring, then the (n + 1)th generation will contain max individuals rather than as in the branching case. Equivalently, the transition matrices Pij of the chains we will study are to be of the form where F(.) is the probability distribution function of a non-negative, integervalued random variable. The right-hand side of (1) is thus the probability that the maximum of i independent random variables distributed by F has the value j. Such a chain will be called a “maximal branching process”.

Type
Research Papers
Copyright
Copyright © Applied Probability Trust 

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References

1] Daley, D. J. (1968) Stochastically monotone Markov chains.. Z. Wahrscheinlichkeitsth 10, 305317.CrossRefGoogle Scholar