Combining upper limits with a Bayesian approach

YANG Liu; ZHU Kai; ZHU Yong-Sheng; CAI Hao

doi:10.1088/1674-1137/39/12/123001

Chinese Physics C> 2015, Vol. 39> Issue(12) : 123001 DOI: 10.1088/1674-1137/39/12/123001

Combining upper limits with a Bayesian approach

YANG Liu ^1,2 ,
ZHU Kai ^2,, ,
ZHU Yong-Sheng ² ,
CAI Hao ^1,,

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Abstract：
We discuss how to determine and combine upper limits based on observed events and estimated backgrounds with a Bayesian method, when insignificant signals are observed in independent measurements. In addition to some general features deduced from the analytical formulae, systematic numerical results are obtained by a C++ program (CULBA) for low-count experiments, which can be used as a reference to combine two upper limits.
- upper limit ,
- Bayesian method ,
- combine results

References

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YANG Liu, ZHU Kai, ZHU Yong-Sheng and CAI Hao. Combining upper limits with a Bayesian approach[J]. Chinese Physics C, 2015, 39(12): 123001. doi: 10.1088/1674-1137/39/12/123001

YANG Liu, ZHU Kai, ZHU Yong-Sheng and CAI Hao. Combining upper limits with a Bayesian approach[J]. Chinese Physics C, 2015, 39(12): 123001. doi: 10.1088/1674-1137/39/12/123001 shu

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Received: 2015-01-30
Revised: 2015-07-21

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Supported by National Natural Science Foundation of China (NSFC) (11005115), Joint Funds of the NSFC and Chinese Academia Sinica's Big Scientific Apparatus (U1232109)

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通讯作者: 陈斌, bchen63@163.com

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沈阳化工大学材料科学与工程学院沈阳 110142

Combining upper limits with a Bayesian approach

Corresponding author: ZHU Kai,

Corresponding author: CAI Hao,

Received Date: 2015-01-30

Accepted Date: 2015-07-21

Available Online: 2015-12-20

Fund Project: Supported by National Natural Science Foundation of China (NSFC) (11005115), Joint Funds of the NSFC and Chinese Academia Sinica's Big Scientific Apparatus (U1232109)

Abstract: We discuss how to determine and combine upper limits based on observed events and estimated backgrounds with a Bayesian method, when insignificant signals are observed in independent measurements. In addition to some general features deduced from the analytical formulae, systematic numerical results are obtained by a C++ program (CULBA) for low-count experiments, which can be used as a reference to combine two upper limits.

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Combining upper limits with a Bayesian approach

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