Journal article
Optimal point process filtering and estimation of the coalescent process
- Abstract:
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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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- Files:
-
-
(Accepted manuscript, pdf, 452.9KB)
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- Publisher copy:
- 10.1016/j.jtbi.2017.04.001
Authors
Funding
Bibliographic Details
- Publisher:
- Elsevier Publisher's website
- Journal:
- Journal of Theoretical Biology Journal website
- Volume:
- 421
- Pages:
- 153-167
- Publication date:
- 2017-05-21
- Acceptance date:
- 2017-04-02
- DOI:
- EISSN:
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1095-8541
- ISSN:
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0022-5193
Item Description
- Language:
- English
- Keywords:
- Pubs id:
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pubs:689323
- UUID:
-
uuid:ce1edc1f-f8b2-4580-ad52-bac369bf24f1
- Local pid:
- pubs:689323
- Source identifiers:
-
689323
- Deposit date:
- 2017-06-21
Terms of use
- Copyright holder:
- Elsevier Ltd
- Copyright date:
- 2017
- Notes:
- Copyright © 2017 Elsevier Ltd. This is the accepted manuscript version of the article. The final version is available online from Elsevier at: https://doi.org/10.1016/j.jtbi.2017.04.001
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