Journal article
The use of mixture density networks in the emulation of complex epidemiological individual-based models
- Abstract:
-
Complex, highly-computational, individual-based models are abundant in epidemiology. For epidemics such as macro-parasitic diseases, detailed modelling of human behaviour and pathogen life-cycle are required in order to produce accurate results. This can often lead to models that are computationally-expensive to analyse and perform model fitting, and often require many simulation runs in order to build up sufficient statistics. Emulation can provide a more computationally-efficient output of ...
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- Publication status:
- Published
- Peer review status:
- Peer reviewed
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Authors
Bibliographic Details
- Publisher:
- Public Library of Science (PLoS) Publisher's website
- Journal:
- PLoS Computational Biology Journal website
- Volume:
- 16
- Issue:
- 3
- Article number:
- e1006869
- Place of publication:
- United States
- Publication date:
- 2020-03-16
- Acceptance date:
- 2020-02-20
- DOI:
- EISSN:
-
1553-7358
- ISSN:
-
1553-734X
- Pmid:
-
32176687
Item Description
- Language:
- English
- Keywords:
- Pubs id:
-
1094582
- Local pid:
- pubs:1094582
- Deposit date:
- 2020-04-28
Terms of use
- Copyright holder:
- Davis et al.
- Copyright date:
- 2020
- Rights statement:
- © 2020 Davis et al. This is an open access article distributed under the terms of the Creative Commons Attribution License
- Licence:
- CC Attribution (CC BY)
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