Particle Metropolis Hastings using Langevin Dynamics
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 us...
| Main Authors: | , , |
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| Format: | Others |
| Language: | English |
| Published: |
Linköpings universitet, Reglerteknik
2013
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| Online Access: | http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-93699 |