Analysis of a Nonreversible Markov Chain Sampler

  title={Analysis of a Nonreversible Markov Chain Sampler},
  author={Persi Diaconis and Susan P. Holmes and Radford M. Neal},
We analyze the convergence to stationarity of a simple nonreversible Markov chain that serves as a model for several nonreversible Markov chain sampling methods that are used in practice. Our theoretical and numerical results show that nonreversibility can indeed lead to improvements over the diffusive behavior of simple Markov chain sampling schemes. The analysis uses both probabilistic techniques and an explicit diagonalization. 
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Publications referenced by this paper.
Showing 1-10 of 35 references

Rates of convergence for a non-reversible Markov chain sampler. Preprint. Available from ̃martinhi

  • M. Hildebrand
  • 1997
Highly Influential
5 Excerpts

A generalized guided Monte Carlo algorithm

  • A. M. Horowitz
  • Phys. Lett. B
  • 1991
Highly Influential
6 Excerpts

The theory of hybrid stochastic algorithms. In Probabilistic Methods in Quantum Field Theory and Quantum Gravity (P

  • A. D. Kennedy
  • eds.). Plenum,
  • 1990
Highly Influential
4 Excerpts

A guided walk

  • P. Gustafson
  • Metropolis algorithm. Statist. Comput
  • 1998
3 Excerpts

Suppressing random walks in Markov chain Monte Carlo using ordered overrelaxation

  • R. M. Neal
  • In Learning in Graphical Models (M. I. Jordan,
  • 1998
3 Excerpts

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