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Particle Metropolis Hastings using Langevin Dynamics
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.ORCID iD: 0000-0002-9424-1272
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
2013 (English)In: Proceedings of the 38th International Conference on Acoustics, Speech, and Signal Processing, IEEE conference proceedings, 2013, 6308-6312 p.Conference paper, Published paper (Refereed)
Abstract [en]

Particle Markov Chain Monte Carlo (PMCMC) samplers allow for routine inference of parameters and states in challenging nonlinear problems. A common choice for the parameter proposal is a simple random walk sampler, which can scale poorly with the number of parameters.

In this paper, we propose to use log-likelihood gradients, i.e. the score, in the construction of the proposal, akin to the Langevin Monte Carlo method, but adapted to the PMCMC framework. This can be thought of as a way to guide a random walk proposal by using drift terms that are proportional to the score function. The method is successfully applied to a stochastic volatility model and the drift term exhibits intuitive behaviour.

Place, publisher, year, edition, pages
IEEE conference proceedings, 2013. 6308-6312 p.
Keyword [en]
Bayesian inference, Sequential Monte Carlo, Particle Markov Chain Monte Carlo, Langevin Monte Carlo
National Category
Control Engineering Signal Processing Probability Theory and Statistics
Identifiers
URN: urn:nbn:se:liu:diva-93699DOI: 10.1109/ICASSP.2013.6638879ISI: 000329611506094OAI: oai:DiVA.org:liu-93699DiVA: diva2:626579
Conference
38th International Conference on Acoustics, Speech, and Signal Processing, Vancouver, Canada, 28-31 May, 2013
Projects
CADICS, CNDS
Funder
Swedish Research Council
Available from: 2013-06-10 Created: 2013-06-10 Last updated: 2016-05-04Bibliographically approved

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Dahlin, JohanLindsten, FredrikSchön, Thomas

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