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Probabilistic integration: A role in statistical computation?

Abstract:

A research frontier has emerged in scientific computation, wherein discretisation error is regarded as a source of epistemic uncertainty that can be modelled. This raises several statistical challenges, including the design of statistical methods that enable the coherent propagation of probabilities through a (possibly deterministic) computational work-flow, in order to assess the impact of discretisation error on the computer output. This paper examines the case for probabilistic numerical m...

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Publication status:
Published
Peer review status:
Peer reviewed
Version:
Accepted Manuscript

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Publisher copy:
10.1214/18-STS660

Authors


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Institution:
University of Oxford
Division:
MPLS Division
Department:
Engineering Science
Role:
Author
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Institution:
University of Oxford
Division:
MPLS Division
Department:
Statistics
Role:
Author
ORCID:
0000-0001-5547-9213
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Funding agency for:
Girolami, M
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Funding agency for:
Girolami, M
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Publisher:
Institute of Mathematical Statistics Publisher's website
Journal:
Statistical Science Journal website
Volume:
34
Issue:
1
Pages:
1-22
Publication date:
2019-04-12
Acceptance date:
2018-05-25
DOI:
EISSN:
2168-8745
ISSN:
0883-4237
Pubs id:
pubs:854172
URN:
uri:b9074917-fecb-41a6-a2eb-62fe47ae715f
UUID:
uuid:b9074917-fecb-41a6-a2eb-62fe47ae715f
Local pid:
pubs:854172

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