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August 2007 When is Eaton’s Markov chain irreducible?
James P. Hobert, Aixin Tan, Ruitao Liu
Bernoulli 13(3): 641-652 (August 2007). DOI: 10.3150/07-BEJ6191


Consider a parametric statistical model P(dx|θ) and an improper prior distribution ν(dθ) that together yield a (proper) formal posterior distribution Q(dθ|x). The prior is called strongly admissible if the generalized Bayes estimator of every bounded function of θ is admissible under squared error loss. Eaton [Ann. Statist. 20 (1992) 1147–1179] has shown that a sufficient condition for strong admissibility of ν is the local recurrence of the Markov chain whose transition function is R(θ, dη)= Q(dη|x)P(dx|θ). Applications of this result and its extensions are often greatly simplified when the Markov chain associated with R is irreducible. However, establishing irreducibility can be difficult. In this paper, we provide a characterization of irreducibility for general state space Markov chains and use this characterization to develop an easily checked, necessary and sufficient condition for irreducibility of Eaton’s Markov chain. All that is required to check this condition is a simple examination of P and ν. Application of the main result is illustrated using two examples.


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James P. Hobert. Aixin Tan. Ruitao Liu. "When is Eaton’s Markov chain irreducible?." Bernoulli 13 (3) 641 - 652, August 2007.


Published: August 2007
First available in Project Euclid: 7 August 2007

zbMATH: 1131.60066
MathSciNet: MR2348744
Digital Object Identifier: 10.3150/07-BEJ6191

Rights: Copyright © 2007 Bernoulli Society for Mathematical Statistics and Probability


Vol.13 • No. 3 • August 2007
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