https://doi.org/10.1140/epjst/e2009-01048-0
Propagation of distributions by a Monte Carlo method, with an application to ratio models
National Physical Laboratory, Teddington, Middlesex, TW11 0LW, UK
Corresponding author: maurice.cox@npl.co.uk
The GUM uncertainty framework, namely the law of propagation of uncertainty and the characterization of the measurand Y by a Gaussian distribution (or a scaled and shifted t-distribution), is seen as an approximate implementation of a fundamental concept, the propagation of distributions. This concept and a Monte Carlo method that implements it in a numerically controlled way are outlined. A family of models, relating to comparison measurement, and solvable analytically in algebraic form, is treated by both approaches to assess the degrees of approximation involved.
© EDP Sciences, Springer-Verlag, 2009
