Using exact Poisson likelihood functions in Bayesian interpretation of counting measurements
| Autor: | T. Little, Ray Guilmette, Guthrie Miller, Harry F. Martz |
|---|---|
| Rok vydání: | 2002 |
| Předmět: |
Background subtraction
Likelihood Functions Epidemiology Health Toxicology and Mutagenesis Bayesian probability Statistics as Topic Bayes Theorem Poisson distribution Marginal likelihood symbols.namesake Statistics Prior probability Calibration symbols Applied mathematics Radiology Nuclear Medicine and imaging Poisson regression Poisson Distribution Likelihood function Radiometry Mathematics Interpolation |
| Zdroj: | Health physics. 83(4) |
| ISSN: | 0017-9078 |
| Popis: | — A technique for computing the exact marginalized (integrated) Poisson likelihood function for counting measurement processes involving a background subtraction is described. An empirical Bayesian method for determining the prior probability distribution of background count rates from population data is recommended and would seem to have important practical advantages. The exact marginalized Poisson likelihood function may be used instead of the commonly used Gaussian approximation. Differences occur in some cases of small numbers of measured counts, which are discussed. Optional use of exact likelihood functions in our Bayesian internal dosimetry codes has been implemented using an interpolation-table approach, which means that there is no computation time penalty except for the initial setup of the interpolation tables. |
| Databáze: | OpenAIRE |
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