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  Coupled MCMC in BEAST 2

Müller, N. F., & Bouckaert, R. (2019). Coupled MCMC in BEAST 2. bioRxiv, 603514. doi:10.1101/603514.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0004-98C8-F Version Permalink: http://hdl.handle.net/21.11116/0000-0004-98C9-E
Genre: Journal Article

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 Creators:
Müller, Nicola F., Author
Bouckaert, Remco1, Author              
Affiliations:
1Linguistic and Cultural Evolution, Max Planck Institute for the Science of Human History, Max Planck Society, ou_2074311              

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 Abstract: Coupled MCMC has long been used to speed up phylogenetic analyses and to make use of multi-core CPUs. Coupled MCMC uses a number of heated chains with increased acceptance probabilities that are able to traverse unfavourable intermediate states more easily than non heated chains and can be used to propose new states. While more and more complex models are used to study evolution, one of the main software platforms to do so, BEAST 2, was lacking this functionality. Here, we describe an implementation of the coupled MCMC algorithm for the Bayesian phylogenetics platform BEAST 2. This implementation is able to exploit multiple-core CPUs while working with all models and packages in BEAST 2 that affect the likelihood or the priors and not directly the MCMC machinery. We show that the implemented coupled MCMC approach is exploring the same posterior probability space as regular MCMC when MCMC behaves well. We also show our implementation is able to retrieve more consistent estimates of tree distributions on a dataset where convergence with MCMC is problematic.

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Language(s): eng - English
 Dates: 2019-04-09
 Publication Status: Published online
 Pages: 9
 Publishing info: -
 Table of Contents: -
 Rev. Method: No review
 Identifiers: DOI: 10.1101/603514
Other: shh2386
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Title: bioRxiv
Source Genre: Journal
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Publ. Info: Cold Spring Harbor : Cold Spring Harbor Laboratory
Pages: - Volume / Issue: - Sequence Number: 603514 Start / End Page: - Identifier: -