Journal article
Comparing two sequential Monte Carlo samplers for exact and approximate Bayesian inference on biological models
- Abstract:
-
Bayesian methods are advantageous for biological modeling studies due to their ability to quantify and characterize posterior variability in model parameters. When Bayesian methods cannot be applied, due either to nondeterminism in the model or limitations on system observability, approximate Bayesian computation (ABC) methods can be used to similar effect, despite producing inflated estimates of the true posterior variance. Due to generally differing application domains, there are few studie...
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- Publication status:
- Published
- Peer review status:
- Peer reviewed
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Bibliographic Details
- Publisher:
- Royal Society Publisher's website
- Journal:
- Interface Journal website
- Volume:
- 14
- Issue:
- 134
- Article number:
- 20170340
- Publication date:
- 2017-09-20
- Acceptance date:
- 2017-08-29
- DOI:
- EISSN:
-
1742-5662
- ISSN:
-
1742-5689
Item Description
- Keywords:
- Pubs id:
-
pubs:724880
- UUID:
-
uuid:3820f3c9-fd4f-4df1-bd83-50ae5ef1e91b
- Local pid:
- pubs:724880
- Source identifiers:
-
724880
- Deposit date:
- 2017-09-01
Terms of use
- Copyright holder:
- Daly et al
- Copyright date:
- 2017
- Notes:
-
Copyright © 2017 The Authors.
Published by the Royal Society.This is the accepted manuscript version of the article. The final version is available online from the Royal Society at: https://doi.org/10.1098/rsif.2017.0340
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