Currie detection limits in gamma-ray spectroscopy

Currie Hypothesis testing is applied to gamma-ray spectral data, where an optimum part of the peak is used and the background is considered well known from nearby channels. With this, the risk of making Type I errors is about 100 times lower than commonly assumed. A programme, PeakMaker, produces ra...

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Bibliographic Details
Published in:Applied radiation and isotopes 2004-08, Vol.61 (2), p.151-160
Main Author: De Geer, Lars-Erik
Format: Article
Language:English
Subjects:
CTBTO Preparatory Commission
Currie
Decision limit
Detection limit
Determination limit
Gamma spectrum
Gaussian distribution
Hypothesis testing
Nuclear Test Ban
PeakMaker
Poisson distribution
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Summary:Currie Hypothesis testing is applied to gamma-ray spectral data, where an optimum part of the peak is used and the background is considered well known from nearby channels. With this, the risk of making Type I errors is about 100 times lower than commonly assumed. A programme, PeakMaker, produces random peaks with given characteristics on the screen and calculations are done to facilitate a full use of Poisson statistics in spectrum analyses. Short technical note summary: The Currie decision limit concept applied to spectral data is reinterpreted, which gives better consistency between the selected error risk and the observed error rates. A PeakMaker program is described and the few count problem is analyzed.
ISSN:0969-8043
1872-9800
DOI:10.1016/j.apradiso.2004.03.037