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Uncertainty Analysis for Vector Measurands Using Fiducial Inference



Chih-Ming Wang, Hariharan K. Iyer


This paper presents a method for constructing uncertainty regions for a vector measurand in the presence of both type-A and type-B errors. The method is based on the principle of fiducial inference and generally requires a Monte Carlo approach for computing uncertainty regions. A small simulation study is carried out to evaluate the performance of the method. Computer programs, written in public-domain software, for computing uncertainty regions are listed. An example, involving complex S-parameter measurements, is used to illustrate the proposed method.


generalized pivotal quantities, ISO GUM, key comparisons.


Wang, C. and Iyer, H. (2006), Uncertainty Analysis for Vector Measurands Using Fiducial Inference, Metrologia (Accessed April 15, 2024)
Created January 1, 2006, Updated January 27, 2020