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The Poisson-Dirichlet Law Is the Unique Invariant Distribution for Uniform Split-Merge Transformations
We consider a Markow chain on the space of (countable) partitions of the interval [0, 1], obtained first by size-biased sampling twice (allowing repetitions) and then merging the parts (if the sampled parts are distinct) or splitting the part uniformly (if the same part was sampled twice). We prove...
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Published in: | The Annals of probability 2004-01, Vol.32 (1), p.915-938 |
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container_title | The Annals of probability |
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creator | Diaconis, Persi Mayer-Wolf, Eddy Zeitouni, Ofer Martin P. W. Zerner |
description | We consider a Markow chain on the space of (countable) partitions of the interval [0, 1], obtained first by size-biased sampling twice (allowing repetitions) and then merging the parts (if the sampled parts are distinct) or splitting the part uniformly (if the same part was sampled twice). We prove a conjecture of Vershik stating that the Poisson-Dirichlet law with parameter θ = 1 is the unique invariant distribution for this Markov chain. Our proof uses a combination of probabilistic, combinatoric and representation-theoretic arguments. |
doi_str_mv | 10.1214/aop/1079021468 |
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subjects | 60G55 60J27 60K35 Atoms coagulation Distribution theory Exact sciences and technology fragmentation General topics Integers invariant measures Markov chains Markov processes Mathematics Partitions Poisson--Dirichlet Probabilities Probability and statistics Probability theory and stochastic processes Property partitioning Riemann surfaces Sampling distributions Sciences and techniques of general use Statistics Uniform laws |
title | The Poisson-Dirichlet Law Is the Unique Invariant Distribution for Uniform Split-Merge Transformations |
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