A Dirichlet Form approach to MCMC Optimal Scaling

@article{Zanella2016ADF,
  title={A Dirichlet Form approach to MCMC Optimal Scaling},
  author={Giacomo Zanella and Wilfrid S. Kendall and Mylene B'edard},
  journal={arXiv: Probability},
  year={2016},
  pages={4053-4082}
}
This paper develops the use of Dirichlet forms to deliver proofs of optimal scaling results for Markov chain Monte Carlo algorithms (specifically, Metropolis-Hastings random walk samplers) under regularity conditions which are substantially weaker than those required by the original approach (based on the use of infinitesimal generators). The Dirichlet form methods have the added advantage of providing an explicit construction of the underlying infinite-dimensional context. In particular, this… Expand
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