In order to determine if a statistically significant difference exists between shipper and receiver measurements, a statistical combination of the shipper's and receiver's limit-of-error (LOE) is calculated to determine the shipper/receiver limit-of-error, LOES/R. The shipper's and receiver's LOE may possess random and systematic components. Depending on the interpretation of the systematic and random components, the determination of the LOES/R can be performed by several different calculational methods. These calculational methods and their associated underlying assumptions are reviewed in the context of the LANL shipper receiver program. This paper, by presenting the assumptions that form the basis of a site-specific shipper/receiver difference calculation, can assist those individuals responsible for calculating LOES/R.
Funding Material, Control and Accountability (MCA however, MC&A upgrade projects in non-traditional environments may be required to take into account situations where the potential payoff vectors among decision-makers may be significantly different. Once a decision-maker is required to take into account the decisions of others, the process can be modeled as a game. Game theory has been previously be used to shed light on many aspects of social and economic behavior where a payoff from a set of strategies is dependent on the strategy of others. In this paper, the application of game theory in the context of MC&A upgrades is discussed. Various MC&A upgrades decision payoff matrices for relevant circumstances are evaluated for static (simultaneous) and dynamic (sequential decisions) games. Optimal strategies and equilibrium conditions for these payoff matrices are analyzed. Additional game factors (bargaining, uncertain outcomes, moralmore » hazards) that may affect the outcome of the game are briefly discussed. By demonstrating the application of game theory to a nontraditional environment that may require MC&A upgrades, this work increases the understanding out how outcomes are logically connected to the respective value decision-makers assign to choices.« less
DOE M 474.1 states that 'For Category I and II items, the acceptance/rejection criteria for verification measurements and, where possible, for confirmation measurements must be based on the standard deviation for the measurement method under operating conditions.' Determination of the acceptance/rejection criteria for confirmation and verification measurements may involve null and alternative hypothesis testing. The specific values used for computing the appropriate test statistics are dependent on the desired type I and II errors. If hypothesis testing is applied to a verification measurement (such as verification measurement signal interpretation equals nuclear material book value), then the successful application of hypothesis testing and accurate determination of type I and type II error is dependent on the existing statistical assumptions. This paper discusses some common statistical assumptions that may be used in support of confirmation and verification measurements. The implications of these assumptions on type I and II error are briefly analyzed. Suggestions for validating the desired type I and II error for confirmation and verification measurements are provided. This paper, by providing an introduction to some common statistical assumptions and the associated implications on error, aids safeguards professionals in their ability to determine the validity on the statistical models that supportmore » their verification and confirmation measurement programs.« less
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