Abstract

This paper presents an approach to the assessment of random uncertainty in transient measurements based on the modeling of a time series that is representative of the variable of interest. The recommended approach employs conventional regression techniques to estimate all parameters that appear in a model for a given time series. Assessments of random uncertainty are based on the residual deviations associated with an adequate model for a given time series. The approach also incorporates a treatment of the dynamic response of a measurement system as it pertains to random uncertainty in transient measurements.

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