The role of measurement error in modelling and simulation
Modelling, Simulation and computational Optimization (MSO) becomes more and more ubiquitous in science and technology. Supporting the quantification of all branches of science it is mission critical to address an area of unexpressed ignorance: the measurement error and its counterpart in modelling, the prediction error. This paper introduces the most important categories of measurement errors and their influence on the predictability of measurements by modelling and simulation. It explains the concept of model fit parameters and their indirect measurement. It counteracts the unjustified uncertainty specification phobia by falsifying the misleading concept of errorbars for two or more fit-parameters and gives a survey on current and future model uncertainty computations made possible by the ubiquitous computational resources.
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