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Block updating in constrained Markov chain Monte Carlo sampling

Author

Listed:
  • Hum, Merrilee A.
  • Rue, Håvard
  • Sheehan, Nuala A.

Abstract

Markov chain Monte Carlo methods are widely used to study highly structured stochastic systems. However, when the system is subject to constraints, it is difficult to find irreducible proposal distributions. We suggest a "block-wise" approach for constrained sampling and optimisation.

Suggested Citation

  • Hum, Merrilee A. & Rue, Håvard & Sheehan, Nuala A., 1999. "Block updating in constrained Markov chain Monte Carlo sampling," Statistics & Probability Letters, Elsevier, vol. 41(4), pages 353-361, February.
  • Handle: RePEc:eee:stapro:v:41:y:1999:i:4:p:353-361
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    Cited by:

    1. Al-Awadhi, Fahimah & Hurn, Merrilee & Jennison, Christopher, 2004. "Improving the acceptance rate of reversible jump MCMC proposals," Statistics & Probability Letters, Elsevier, vol. 69(2), pages 189-198, August.

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