StochastikKolloquium A Dirichlet Form approach to MCMC Optimal Scaling |  |
Speaker:Prof. Dr. Wilfrid S. Kendall, University of Warwick
Organizer:Institut für Mathematische Stochastik
Details:
In this talk I will discuss 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 method has the added advantage of providing an explicit construction of the underlying infinite-dimensional context. In particular, this enables us directly to establish weak convergence to the relevant infinite-dimensional diffusion.
(Joint with Giacomo Zanella and Mylene Bédard.)
Reference:
Zanella, G., Bédard, M., & Kendall, W. S. (2017). A Dirichlet Form approach to MCMC Optimal Scaling. Stochastic Processes and Their Applications, Volume 127, Issue 12, 4053-4082. See also arXiv, 1606.01528, 22pp. URL: arxiv.org/abs/1606.01528.
The Dirichlet form method has the added advantage of providing an explicit construction of the underlying infinite-dimensional context. In particular, this enables us directly to establish weak convergence to the relevant infinite-dimensional diffusion.
(Joint with Giacomo Zanella and Mylene Bédard.)
Reference:
Zanella, G., Bédard, M., & Kendall, W. S. (2017). A Dirichlet Form approach to MCMC Optimal Scaling. Stochastic Processes and Their Applications, Volume 127, Issue 12, 4053-4082. See also arXiv, 1606.01528, 22pp. URL: arxiv.org/abs/1606.01528.
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Type:Colloquium
Language:English
Category:Research
Host:Dozenten des Instituts für Mathematische Stochastik
External link:http://www.stochastik.math.uni-goettingen.de/
Additional information:Download PDF attachment
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Direct link to event:https://events.goettingen-campus.de/event?eventId=8657
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