Maximum likelihood estimation with poisson (counting) statistics for waste drum inspection
This note provides a preliminary look at the issues involved in waste drum inspection when emission levels are so low that central limit theorem arguments do not apply and counting statistics, rather than the usual Gaussian assumption, must be considered. At very high count rates the assumption of Gaussian statistics is reasonable, and the maximum likelihood arguments that we discuss below for low count rates would lead to the usual approach of least squares fits. Least squares is not the the best technique for low counts, and we will develop the maximum likelihood estimators for the low count case.
- Research Organization:
- Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
- Sponsoring Organization:
- USDOE, Washington, DC (United States)
- DOE Contract Number:
- W-7405-ENG-48
- OSTI ID:
- 632788
- Report Number(s):
- UCRL-ID-127361; ON: DE98050898; TRN: 98:008843
- Resource Relation:
- Other Information: PBD: 1 May 1997
- Country of Publication:
- United States
- Language:
- English
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