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Reliable and efficient parameter estimation using approximate continuum limit descriptions of stochastic models

Abstract:

Stochastic individual-based mathematical models are attractive for modelling biological phenomena because they naturally capture the stochasticity and variability that is often evident in biological data. Such models also allow us to track the motion of individuals within the population of interest. Unfortunately, capturing this microscopic detail means that simulation and parameter inference can become computationally expensive. One approach for overcoming this computational limitation is to...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1016/j.jtbi.2022.111201

Authors


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Institution:
University of Oxford
Division:
MPLS
Department:
Mathematical Institute
Oxford college:
St Hugh's College
Role:
Author
ORCID:
0000-0002-6304-9333


Publisher:
Elsevier
Journal:
Journal of Theoretical Biology More from this journal
Volume:
549
Article number:
111201
Publication date:
2022-06-22
Acceptance date:
2022-06-10
DOI:
EISSN:
1095-8541
ISSN:
0022-5193
Pmid:
35752285


Language:
English
Keywords:
Pubs id:
1265740
Local pid:
pubs:1265740
Deposit date:
2022-08-08

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