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Title: Statistical Methods for Improved Evaluation of Environmental Sample Data quarterly FY18Q2

Abstract

We will develop an enhanced statistical framework to evaluate environmental swipe samples collected at nuclear facilities with the goal of identifying anomalies associated with potential undeclared activities. Our approach will be based on Bayesian methodology and time series analysis. This overall framework should result in a more cost effective and operationally effective approach to environmental swipe sample analysis and interpretation.

Authors:
 [1]
  1. Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
Publication Date:
Research Org.:
Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1432977
Report Number(s):
LLNL-SR-748821
DOE Contract Number:  
AC52-07NA27344
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English
Subject:
98 NUCLEAR DISARMAMENT, SAFEGUARDS AND PHYSICAL PROTECTION; 97 MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE

Citation Formats

Wurtz, Ron E. Statistical Methods for Improved Evaluation of Environmental Sample Data quarterly FY18Q2. United States: N. p., 2018. Web. doi:10.2172/1432977.
Wurtz, Ron E. Statistical Methods for Improved Evaluation of Environmental Sample Data quarterly FY18Q2. United States. doi:10.2172/1432977.
Wurtz, Ron E. Thu . "Statistical Methods for Improved Evaluation of Environmental Sample Data quarterly FY18Q2". United States. doi:10.2172/1432977. https://www.osti.gov/servlets/purl/1432977.
@article{osti_1432977,
title = {Statistical Methods for Improved Evaluation of Environmental Sample Data quarterly FY18Q2},
author = {Wurtz, Ron E.},
abstractNote = {We will develop an enhanced statistical framework to evaluate environmental swipe samples collected at nuclear facilities with the goal of identifying anomalies associated with potential undeclared activities. Our approach will be based on Bayesian methodology and time series analysis. This overall framework should result in a more cost effective and operationally effective approach to environmental swipe sample analysis and interpretation.},
doi = {10.2172/1432977},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2018},
month = {3}
}

Technical Report:

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