Bayesian theory of systematic measurement deviations
Abstract
Concerning systematic effects, the recommendation given in the GUM is to correct for them, but unfortunately no detailed information is available, how to do this. This publication will show, how systematic measurement deviations can be handled correctly based on the Bayesian probability theory. After a short overview about useful methods and tools, like the product rule of probability theory, Bayes' theorem, the principle of maximum entropy, and the marginalisation equation, an outline of a method to handle systematic measurement deviations is introduced. Finally some simple examples of practical interest are given, in order to demonstrate the applicability of the suggested method.
Cite
@article{arxiv.1009.0942,
title = {Bayesian theory of systematic measurement deviations},
author = {Michael Krystek},
journal= {arXiv preprint arXiv:1009.0942},
year = {2011}
}
Comments
This paper has been withdrawn by the author. The paper has been rejected by the referees of MST. If someone is still interested in the content, please contact me by e-mail (Michael.Krystek@ptb.de)