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Monte Carlo cubature construction

Abstract:
Abstract In numerical integration, cubature methods are effective, especially when the integrands can be well-approximated by known test functions, such as polynomials. However, the construction of cubature formulas has not generally been known, and existing examples only represent the particular domains of integrands, such as hypercubes and spheres. In this study, we show that cubature formulas can be constructed for probability measures provided that we have an i.i.d. sampler from the measure and the mean values of given test functions. Moreover, the proposed method also works as a means of data compression, even if sufficient prior information of the measure is not available.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1007/s13160-020-00451-x

Authors

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Institution:
University of Oxford
Division:
MPLS
Department:
Mathematical Institute
Role:
Author
ORCID:
0000-0003-1176-5837


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Funder identifier:
10.13039/501100000769


Publisher:
Springer
Journal:
Japan Journal of Industrial and Applied Mathematics More from this journal
Volume:
38
Issue:
2
Pages:
561-577
Publication date:
2020-12-15
DOI:
EISSN:
1868-937X
ISSN:
0916-7005


Language:
English
Pubs id:
1145106
Local pid:
pubs:1145106
Source identifiers:
W2998641726
Deposit date:
2026-02-12
ARK identifier:
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