Electronic Journal of Statistics

On a Gibbs sampler based random process in Bayesian nonparametrics

Stefano Favaro, Matteo Ruggiero, and Stephen G. Walker

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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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Electron. J. Statist., Volume 3 (2009), 1556-1566.

First available in Project Euclid: 4 January 2010

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Random probability measure Dirichlet process Blackwell-MacQueen Pólya urn scheme Gibbs sampler Bayesian nonparametrics


Favaro, Stefano; Ruggiero, Matteo; Walker, Stephen G. On a Gibbs sampler based random process in Bayesian nonparametrics. Electron. J. Statist. 3 (2009), 1556--1566. doi:10.1214/09-EJS563. https://projecteuclid.org/euclid.ejs/1262617419

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