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Calibration and uncertainty assessment for certified reference gas mixtures

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Abstract

The weighted least squares method to build an analysis function described in ISO 6143, Gas analysis—Comparison methods for determining and checking the composition of calibration gas mixtures, is modified to take into account the typically small number of instrumental readings that are obtained for each primary standard gas mixture used in calibration. The theoretical basis for this modification is explained, and its superior performance is illustrated in a simulation study built around a concrete example, using real data. The corresponding uncertainty assessment is obtained by application of a Monte Carlo method consistent with the guidance in the Supplement 1 to the Guide to the expression of uncertainty in measurement, which avoids the need for two successive applications of the linearizing approximation of the conventional method for uncertainty propagation. The three main steps that NIST currently uses to certify a reference gas mixture (homogeneity study, calibration, and assignment of value and uncertainty assessment), are described and illustrated using data pertaining to an actual standard reference material.

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References

  1. BIPM (2010) The BIPM key comparison database. http://kcdb.bipm.org/

  2. Carroll RJ, Ruppert D, Stefanski LA, Crainiceanu CM (2006) Measurement error in nonlinear models—a modern perspective, 2nd edn. Chapman & Hall/CRC, Boca Raton

    Book  Google Scholar 

  3. Casella G, Berger RL (2002) Statistical inference, 2nd edn. Duxbury, Pacific Grove

    Google Scholar 

  4. Chambers J, Cleveland W, Kleiner B, Tukey P (1983) Graphical methods for data analysis. Wadsworth, Belmont

    Google Scholar 

  5. Comité International des Poids et Mesures (CIPM) (1999) Mutual recognition of national measurement standards and of calibration and measurement certificates issued by national metrology institutes. Bureau International des Poids et Mesures (BIPM), Pavillon de Breteuil, Sèvres, France, Technical supplement revised in October 2003

  6. Draper NR, Smith H (1981) Applied regression analysis, 2nd edn. Wiley, New York

    Google Scholar 

  7. Efron B, Tibshirani RJ (1993) An introduction to the bootstrap. Chapman & Hall, London

    Google Scholar 

  8. Fuller WA (1987) Measurement error models. Wiley, New York

    Book  Google Scholar 

  9. Hastie T, Tibshirani R, Friedman J (2001) The elements of statistical learning: data mining, inference, and prediction. Springer, New York

    Google Scholar 

  10. ISO (2001) Gas analysis—comparison methods for determining and checking the composition of calibration gas mixtures. International Organization for Standardization (ISO), Geneva, Switzerland, International Standard ISO 6143:2001(E)

  11. Joint Committee for Guides in Metrology (2008) Evaluation of measurement data—guide to the expression of uncertainty in measurement. International Bureau of Weights and Measures (BIPM), Sèvres, France. http://www.bipm.org/en/publications/guides/gum.html. BIPM, IEC, IFCC, ILAC, ISO, IUPAC, IUPAP and OIML, JCGM 100:2008, GUM 1995 with minor corrections

  12. Joint Committee for Guides in Metrology (2008) Evaluation of measurement data—supplement 1 to the “Guide to the expression of uncertainty in measurement”—propagation of distributions using a Monte Carlo method. International Bureau of Weights and Measures (BIPM), Sèvres, France. http://www.bipm.org/en/publications/guides/gum.html. BIPM, IEC, IFCC, ILAC, ISO, IUPAC, IUPAP and OIML, JCGM 101:2008

  13. Joint Committee for Guides in Metrology (2008) International vocabulary of metrology—basic and general concepts and associated terms (VIM). International Bureau of Weights and Measures (BIPM), Sèvres, France. http://www.bipm.org/en/publications/guides/vim.html. BIPM, IEC, IFCC, ILAC, ISO, IUPAC, IUPAP and OIML, JCGM 200:2008

  14. Lehmann EL (1999) Elements of large-sample theory. Springer, New York

    Book  Google Scholar 

  15. Loader C (1999) Local regression and likelihood. Springer, New York

    Google Scholar 

  16. Miller RG (1986) Beyond ANOVA, basics of applied statistics. Wiley, New York

    Google Scholar 

  17. Milton MJT, Guenther F, Miller WR, Brown AS (2006) Validation of the gravimetric values and uncertainties of independently prepared primary standard gas mixtures. Metrologia 43:L7–L10

    Article  Google Scholar 

  18. Nelder JA, Mead R (1965) A simplex algorithm for function minimization. Comput J 7:308–313

    Google Scholar 

  19. NIST (2008) Standard reference material 1685b: nitric oxide in nitrogen. National Institute of Standards and Technology, Gaithersburg, MD. http://www.nist.gov/ts/msd/srm/. Certificate of analysis

  20. NIST/SEMATECH (2006) NIST/SEMATECH e-handbook of statistical methods. National Institute of Standards and Technology, U.S. Department of Commerce, Gaithersburg, MD. http://www.itl.nist.gov/div898/handbook/

  21. Pinheiro J, Bates D, DebRoy S, Sarkar D, R Core Team (2009) nlme: linear and nonlinear mixed effects models. http:/www.r-project.org/. R package version 3.1-96

  22. Pinheiro JC, Bates DM (2000) Mixed-effects models in S and S-Plus. Springer, New York

    Book  Google Scholar 

  23. R Development Core Team (2009) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna. http://www.R-project.org. ISBN 3-900051-07-0

  24. R Development Core Team (2010) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna. http://www.R-project.org. ISBN 3-900051-07-0

  25. Silverman BW (1986) Density estimation. Chapman & Hall, London

    Google Scholar 

  26. Smith IM (2005) XGENLINE version 8.1 stand-alone executable—software documentation. Tech. rep., National Physical Laboratory, Teddington, Middlesex, UK. Version 1.0

  27. Stefanski LA (2000) Measurement error models. J Am Stat Assoc 95(452):1353–1358

    Article  Google Scholar 

  28. Tukey JW (1977) Exploratory data analysis. Addison-Wesley, Reading

    Google Scholar 

  29. Venables WN, Ripley BD (2002) Modern applied statistics with S, 4th edn. Springer, New York. http://www.stats.ox.ac.uk/pub/MASS4. ISBN 0-387-95457-0

  30. Young DS (2009) Tolerance: functions for calculating tolerance intervals. http://CRAN.R-project.org/package=tolerance. R package version 0.1.0

  31. Zwolak JW, Boggs PT, Watson LT (2007) Algorithm 869: ODRPACK95: a weighted orthogonal distance regression code with bound constraints. ACM Trans Math Softw 33(4):27

    Article  Google Scholar 

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Acknowledgements

The authors are particularly grateful to their NIST colleagues Andrew Rukhin, Blaza Toman, and David Duewer, who kindly provided detailed reviews of a draft, and offered useful comments and suggestions. However, we may not have incorporated all of their suggestions, or heeded all of their advice, hence there is no implication that they subscribe to the current version of the contribution. The same applies to other colleagues including Hung-kung Liu and Stefan Leigh, who have given us suggestions, comments, and references, on several occasions.

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Correspondence to Antonio Possolo.

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Guenther, F.R., Possolo, A. Calibration and uncertainty assessment for certified reference gas mixtures. Anal Bioanal Chem 399, 489–500 (2011). https://doi.org/10.1007/s00216-010-4379-z

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