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Gibbs Distributions for Random Partitions Generated by a Fragmentation Process
Authors:Nathanaël Berestycki  Jim Pitman
Institution:(1) University of British Columbia, Vancouver, B.C., Canada, V6T 1Z2;(2) Department of Statistics, University of California, Berkeley, CA, USA
Abstract:In this paper we study random partitions of {1,…,n} where every cluster of size j can be in any of w j possible internal states. The Gibbs (n,k,w) distribution is obtained by sampling uniformly among such partitions with k clusters. We provide conditions on the weight sequence w allowing construction of a partition valued random process where at step k the state has the Gibbs (n,k,w) distribution, so the partition is subject to irreversible fragmentation as time evolves. For a particular one-parameter family of weight sequences w j , the time-reversed process is the discrete Marcus–Lushnikov coalescent process with affine collision rate K i,j = a+b(i+j) for some real numbers a and b. Under further restrictions on a and b, the fragmentation process can be realized by conditioning a Galton–Watson tree with suitable offspring distribution to have n nodes, and cutting the edges of this tree by random sampling of edges without replacement, to partition the tree into a collection of subtrees. Suitable offspring distributions include the binomial, negative binomial and Poisson distributions. Research supported in part by N.S.F. Grant DMS-0405779.
Keywords:Fragmentation processes  Gibbs distributions  Marcus–  Lushnikov processes  Gould convolution identities
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