Efficient MCMC Schemes for Computationally Expensive Posterior Distributions

@article{Fielding2011EfficientMS,
  title={Efficient MCMC Schemes for Computationally Expensive Posterior Distributions},
  author={Mark Fielding and David J. Nott and Shie-Yui Liong},
  journal={Technometrics},
  year={2011},
  volume={53},
  pages={16-28}
}
We consider Markov chain Monte Carlo (MCMC) computational schemes intended to minimize the number of evaluations of the posterior distribution in Bayesian inference when the posterior is computationally expensive to evaluate. Our motivation is Bayesian calibration of computationally expensive computer models. An algorithm suggested previously in the literature based on hybrid Monte Carlo and a Gaussian process approximation to the target distribution is extended in three ways. First, we… CONTINUE READING
8 Citations
17 References
Similar Papers

References

Publications referenced by this paper.
Showing 1-10 of 17 references

Hybrid Monte Carlo,

  • S. Duane, A. D. Kennedy, B. J. Pendelton, D. Roweth
  • Physics Letters B,
  • 1987
Highly Influential
3 Excerpts

Implementing a Rainfall-Runoff Concept in SOBEK for an Urbanised Catchment in Singapore,” in Water Down Under 2008, 31st Hydrology and Water Resources Symposium, Institution of Engineers, Australia

  • A. Verwey, N. Muttil, S. Y. Liong, S. He
  • TECHNOMETRICS,
  • 2008
1 Excerpt

Implementing a RainfallRunoff Concept in SOBEK for an Urbanised Catchment in Singapore

  • A. Verwey, N. Muttil, S. Y. Liong, S. He
  • Water Down Under
  • 2008
1 Excerpt

Similar Papers

Loading similar papers…