Open Access
Issue
Int. J. Metrol. Qual. Eng.
Volume 3, Number 2, 2012
Page(s) 71 - 77
DOI https://doi.org/10.1051/ijmqe/2012017
Published online 14 November 2012
  1. JCGM 200, International vocabulary of metrology – basic and general concepts and associated terms (VIM), 2008
  2. JCGM 100, Guide to the expression of uncertainty in measurement (GUM), 2008
  3. JCGM 101, Guide to the expression of uncertainty in measurement – Supplement 1 : Propagation of distribution using the Monte Carlo method (GUMS1), 2008
  4. H.S. Migon, D. Gamerman, Statistical Inference : an Integrated Approach (Arnold, London, 1999)
  5. A. Gelman, J.B. Carlin, H.S. Stern, D.B. Rubin, Bayesian Data Analysis, 2nd edn. (Chapman & Hall/CRC, Boca Raton, 2004)
  6. D. Gamerman, Markov Chain Monte Carlo (Chapman & Hall/CRC, Boca Raton, 1999)
  7. G. Grimmett, D. Stirzaker, Probability and Random Processes, 3rd edn. (Oxford University Press, Oxford, 2001)
  8. C. Elster, W. Wöger, M.G. Cox. Draft GUM Supplement 1 and Bayesian analysis, Metrologia 44, L31–L32 (2007) [CrossRef]
  9. C. Elster, B. Toman, Bayesian uncertainty analysis under prior ignorance of the measurand versus analysis using Supplement 1 to the Guide : a comparison. Metrologia 46, 261–266 (2009) [CrossRef]
  10. A.B. Forbes, J.A. Sousa, The GUM, Bayesian inference and forward and inverse uncertainty evaluation. Measurement 44, 1422–1435 (2011) [CrossRef]
  11. A.B. Forbes, An MCMC algorithm based on GUM Supplement 1 for uncertainty evaluation. Measurement. (in press, DOI : 10.1016/j.measurement.2012.01.018)
  12. A.B. Forbes, A two stage MCM/MCMC algorithm for uncertainty evaluation, in Advanced Mathematical and Computational Tools in Metrology and Testing IX, Göteborg, Sweeden, 2011, edited by F. Pavese et al. (World Scientific, 2012), pp. 159–170
  13. M.G. Cox, P.M. Harris, Uncertainty Evaluation, Report No. MS 6 (Software Support for Metrology Best Practice Guide 6) (National Physical Laboratory, Teddington, 2011)
  14. J.A. Sousa, A.S. Ribeiro, A.B. Forbes, P.M. Harris, F. Carvalho, L. Bacelar, The relevance of using a Monte Carlo method to evaluate uncertainty in mass calibration, IMEKO TC3, TC16 and TC22 International Conference Merida, Mexico, 2007
  15. A. Possolo, B. Toman, Assessment of measurement uncertainty via observation equations. Metrologia 44, 464–475, 2007 [CrossRef]
  16. A.B. Forbes, Nonlinear least squares and Bayesian inference, in Advanced Mathematical and Computational Tools for Metrology VIII, edited by F. Pavese et al. (World Scientific, Singapore, 2009), pp. 103–111

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