Calculation of measurement uncertainty using prior information | Zendy

Steven Phillips | Zendy; William T. Estler | Zendy; Mark Levenson | Zendy; Keith R. Eberhardt | Zendy

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Calculation of measurement uncertainty using prior information

Author(s) -

Steven Phillips,

William T. Estler,

Mark Levenson,

Keith R. Eberhardt

Publication year - 1998

Publication title -

journal of research of the national institute of standards and technology

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.202

H-Index - 59

eISSN - 2165-7254

pISSN - 1044-677X

DOI - 10.6028/jres.103.042

Subject(s) - measurement uncertainty , guard (computer science) , bayesian probability , uncertainty quantification , computer science , uncertainty analysis , bayesian inference , inference , standard uncertainty , propagation of uncertainty , prior information , data mining , algorithm , statistics , mathematics , artificial intelligence , machine learning , simulation , programming language

We describe the use of Bayesian inference to include prior information about the value of the measurand in the calculation of measurement uncertainty. Typical examples show this can, in effect, reduce the expanded uncertainty by up to 85 %. The application of the Bayesian approach to proving workpiece conformance to specification (as given by international standard ISO 14253-1) is presented and a procedure for increasing the conformance zone by modifying the expanded uncertainty guard bands is discussed.

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