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Bayesian Analyses of Time-interval Data for Environmental Radiation Monitoring.
MedLine Citation:
PMID:  23192083     Owner:  NLM     Status:  In-Data-Review    
Abstract/OtherAbstract:
ABSTRACT: Time-interval (time difference between two consecutive pulses) analysis based on the principles of Bayesian inference was investigated for online radiation monitoring. Using experimental and simulated data, Bayesian analysis of time-interval data [Bayesian (ti)] was compared with Bayesian and a conventional frequentist analysis of counts in a fixed count time [Bayesian (cnt) and single interval test (SIT), respectively]. The performances of the three methods were compared in terms of average run length (ARL) and detection probability for several simulated detection scenarios. Experimental data were acquired with a DGF-4C system in list mode. Simulated data were obtained using Monte Carlo techniques to obtain a random sampling of the Poisson distribution. All statistical algorithms were developed using the R Project for statistical computing. Bayesian analysis of time-interval information provided a similar detection probability as Bayesian analysis of count information, but the authors were able to make a decision with fewer pulses at relatively higher radiation levels. In addition, for the cases with very short presence of the source (< count time), time-interval information is more sensitive to detect a change than count information since the source data is averaged by the background data over the entire count time. The relationships of the source time, change points, and modifications to the Bayesian approach for increasing detection probability are presented.
Authors:
Peng Luo; Julia L Sharp; Timothy A Devol
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Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  Health physics     Volume:  104     ISSN:  1538-5159     ISO Abbreviation:  Health Phys     Publication Date:  2013 Jan 
Date Detail:
Created Date:  2012-11-29     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  2985093R     Medline TA:  Health Phys     Country:  United States    
Other Details:
Languages:  eng     Pagination:  15-25     Citation Subset:  IM    
Affiliation:
*Environmental Engineering and Earth Sciences, Clemson University, SC 29634-0919; †Department of Mathematical Sciences, Clemson University, SC 29634-0975.
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