The Annals of Applied Probability

A mixture representation of π with applications in Markov chain Monte Carlo and perfect sampling

James P. Hobert and Christian P. Robert

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Abstract

Let X={Xn:n=0,1,2,} be an irreducible, positive recurrent Markov chain with invariant probability measure π. We show that if X satisfies a one-step minorization condition, then π can be represented as an infinite mixture. The distributions in the mixture are associated with the hitting times on an accessible atom introduced via the splitting construction of Athreya and Ney [Trans. Amer. Math. Soc. 245 (1978) 493–501] and Nummelin [Z. Wahrsch. Verw. Gebiete 43 (1978) 309–318]. When the small set in the minorization condition is the entire state space, our mixture representation of π reduces to a simple formula, first derived by Breyer and Roberts [Methodol. Comput. Appl. Probab. 3 (2001) 161–177] from which samples can be easily drawn. Despite the fact that the derivation of this formula involves no coupling or backward simulation arguments, the formula can be used to reconstruct perfect sampling algorithms based on coupling from the past (CFTP) such as Murdoch and Green’s [Scand. J. Statist. 25 (1998) 483–502] Multigamma Coupler and Wilson’s [Random Structures Algorithms 16 (2000) 85–113] Read-Once CFTP algorithm. In the general case where the state space is not necessarily 1-small, under the assumption that X satisfies a geometric drift condition, our mixture representation can be used to construct an arbitrarily accurate approximation to π from which it is straightforward to sample. One potential application of this approximation is as a starting distribution for a Markov chain Monte Carlo algorithm based on X.

Article information

Source
Ann. Appl. Probab., Volume 14, Number 3 (2004), 1295-1305.

Dates
First available in Project Euclid: 13 July 2004

Permanent link to this document
https://projecteuclid.org/euclid.aoap/1089736286

Digital Object Identifier
doi:10.1214/105051604000000305

Mathematical Reviews number (MathSciNet)
MR2071424

Zentralblatt MATH identifier
1046.60062

Subjects
Primary: 62C15: Admissibility
Secondary: 60J05: Discrete-time Markov processes on general state spaces

Keywords
Burn-in drift condition geometric ergodicity Kac’s theorem minorization condition Multigamma Coupler Read-Once CFTP regeneration split chain

Citation

Hobert, James P.; Robert, Christian P. A mixture representation of π with applications in Markov chain Monte Carlo and perfect sampling. Ann. Appl. Probab. 14 (2004), no. 3, 1295--1305. doi:10.1214/105051604000000305. https://projecteuclid.org/euclid.aoap/1089736286


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References

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