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2009 On a Gibbs sampler based random process in Bayesian nonparametrics
Stefano Favaro, Matteo Ruggiero, Stephen G. Walker
Electron. J. Statist. 3: 1556-1566 (2009). DOI: 10.1214/09-EJS563


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


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Stefano Favaro. Matteo Ruggiero. Stephen G. Walker. "On a Gibbs sampler based random process in Bayesian nonparametrics." Electron. J. Statist. 3 1556 - 1566, 2009.


Published: 2009
First available in Project Euclid: 4 January 2010

zbMATH: 1326.60105
MathSciNet: MR2578838
Digital Object Identifier: 10.1214/09-EJS563

Keywords: Bayesian nonparametrics , Blackwell-MacQueen Pólya urn scheme , Dirichlet process , Gibbs sampler , random probability measure

Rights: Copyright © 2009 The Institute of Mathematical Statistics and the Bernoulli Society


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