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On a Gibbs sampler based random process in Bayesian nonparametrics

By Stefano Favaro, Matteo Ruggiero and Stephen G. Walker

Abstract

We define and investigate a new class ofmeasure-valuedMarkov\ud chains by resorting to ideas formulated in Bayesian nonparametrics related\ud to the Dirichlet process and the Gibbs sampler. Dependent random prob-\ud ability measures in this class are shown to be stationary and ergodic with\ud respect to the law of a Dirichlet process and to converge in distribution to\ud the neutral diffusion model

Topics: QA276
Year: 2009
OAI identifier: oai:kar.kent.ac.uk:23914
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