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Robust test statistics for data sets with missing correlation information

Abstract:
Not all experiments publish their results with a description of the correlations between the data points. This makes it difficult to do hypothesis tests or model fits with that data, since just assuming no correlation can lead to an overestimation or underestimation of the resulting uncertainties. This work presents robust test statistics that can be used with datasets with missing correlation information. They are exact in the case of no correlation and either guaranteed to be conservative—i.e., the uncertainty is never underestimated—in the presence of correlations, or they are also exact in the degenerate case of perfect correlation between the data points.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1103/PhysRevD.103.113008

Authors


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Institution:
University of Oxford
Division:
MPLS
Department:
Physics
Sub department:
Particle Physics
Role:
Author
ORCID:
0000-0002-2966-7461


Publisher:
American Physical Society
Journal:
Physical Review D More from this journal
Volume:
103
Issue:
11
Article number:
113008
Publication date:
2021-06-21
Acceptance date:
2021-05-25
DOI:
EISSN:
2470-0029
ISSN:
2470-0010


Language:
English
Keywords:
Pubs id:
1161876
Local pid:
pubs:1161876
Deposit date:
2021-05-20

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