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Optimal point process filtering and estimation of the coalescent process

Abstract:

The coalescent process is a widely used approach for inferring the demographic history of a population, from samples of its genetic diversity. Several parametric and non-parametric coalescent inference methods, involving Markov chain Monte Carlo, Gaussian processes, and other algorithms, already exist. However, these techniques are not always easy to adapt and apply, thus creating a need for alternative methodologies. We introduce the Bayesian Snyder filter as an easily implementable and flex...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1016/j.jtbi.2017.04.001

Authors


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Institution:
University of Oxford
Division:
MPLS
Department:
Zoology
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Zoology
Role:
Author
Publisher:
Elsevier
Journal:
Journal of Theoretical Biology More from this journal
Volume:
421
Pages:
153-167
Publication date:
2017-05-21
Acceptance date:
2017-04-02
DOI:
EISSN:
1095-8541
ISSN:
0022-5193
Language:
English
Keywords:
Pubs id:
pubs:689323
UUID:
uuid:ce1edc1f-f8b2-4580-ad52-bac369bf24f1
Local pid:
pubs:689323
Source identifiers:
689323
Deposit date:
2017-06-21

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