Utilizing prior knowledge about the measurement process for uncertainty evaluation through plain Monte Carlo sampling | International Journal of Metrology and Quality Engineering (IJMQE)

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Fig. 2

Results for the example of Section 3.1. We show the resulting state of knowledge distribution for the measurand m_X, denoting the deviation of a weight of mass 10 kg. We show the PDFs resulting using the noninformative prior (NIP) in blue, the mildly informative prior (MIP) in green and the strongly informative prior (SIP) in red. Both, MIP and SIP, are computed once using plain Monte Carlo (MC) and once using a vague prior for the measurand and MCMC.

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