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Poisson Process Partition Calculus with applications to Exchangeable models and Bayesian Nonparametrics

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arxiv math/0205093 v1 pith:H3ECXFPP submitted 2002-05-09 math.PR

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This article discusses the usage of a partiton based Fubini calculus for Poisson processes. The approach is an amplification of Bayesian techniques developed in Lo and Weng for gamma/Dirichlet processes. Applications to models are considered which all fall within an inhomogeneous spatial extension of the size biased framework used in Perman, Pitman and Yor. Among some of the results; an explicit partition based calculus is then developed for such models, which also includes a series of important exponential change of measure formula. These results are applied to obtain results for Levy-Cox models, identities related to the two-parameter Poisson-Dirichlet process and other processes, generalisations of the Markov-Krein correspondence, calculus for extended Neutral to the Right processes, among other things.

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    math.ST 2025-02 conditional novelty 7.0 of 10

    A Bayesian point-process framework for feature allocations with dependent labels, with sufficientness postulates characterizing Poisson, mixed Poisson, and mixed binomial priors.

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