NIST's Uncertainty Machine is a software application to evaluate the measurement uncertainty associated with an output quantity defined by a measurement model of the form y = f(x,...,x[n]), where the real-valued function f is specified fully and explicitly, and the input quantities are modeled as random variables whose joint probability distribution also is specified fully. The measurement uncertainty is evaluated by application of two different methods: (i) The method introduced by Gauss (1823) and described in the GUM and also by Taylor & Kuyatt (1994); (ii) the Monte Carlo method described by Morgan & Henrion (1992} and specified in the Supplement 1 to the "Guide to the expression of uncertainty in measurement" (GUM-S1). Measurement Uncertainty, Monte Carlo, Measurement Equation, Uncertainty Evaluation, Probability Distribution, Random Variable, Copula, Coverage Interval, Bootstrap
Citation: This is the user manual for a software application -- they are being WERBed together, as a single entity
Pub Type: Others
Measurement Uncertainty, Monte Carlo, Measurement Equation, Uncertainty Evaluation, Probability Distribution, Random Variable, Copula, Coverage Interval, Bootstrap.