Journal article
When is Eaton's Markov chain irreducible?
Bernoulli : official journal of the Bernoulli Society for Mathematical Statistics and Probability, Vol.13(3), pp.641-652
08/01/2007
DOI: 10.3150/07-BEJ6191
Abstract
Consider a parametric statistical model P(dx vertical bar theta) and an improper prior distribution v(d theta) that together yield a (proper) formal posterior distribution Q(d theta vertical bar x). The prior is called strongly admissible if the generalized Bayes estimator of every bounded function of 0 is admissible under squared error loss. Eaton [Ann. Statist. 20 (1992) 1147-1179] has shown that a sufficient condition for strong admissibility of v is the local recurrence of the Markov chain whose transition function is R(theta, d eta) = integral Q(d eta vertical bar x) P(dx vertical bar theta). 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 v. Application of the main result is illustrated using two examples.
Details
- Title: Subtitle
- When is Eaton's Markov chain irreducible?
- Creators
- James P Hobert - University of FloridaAixin TanRuitao Liu
- Resource Type
- Journal article
- Publication Details
- Bernoulli : official journal of the Bernoulli Society for Mathematical Statistics and Probability, Vol.13(3), pp.641-652
- Publisher
- INT STATISTICAL INST
- DOI
- 10.3150/07-BEJ6191
- ISSN
- 1350-7265
- Number of pages
- 12
- Language
- English
- Date published
- 08/01/2007
- Academic Unit
- Statistics and Actuarial Science
- Record Identifier
- 9984257629502771
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