Int. J. Metrol. Qual. Eng.
Volume 3, Number 2, 2012
|Page(s)||71 - 77|
|Published online||14 November 2012|
- JCGM 200, International vocabulary of metrology – basic and general concepts and associated terms (VIM), 2008
- JCGM 100, Guide to the expression of uncertainty in measurement (GUM), 2008
- JCGM 101, Guide to the expression of uncertainty in measurement – Supplement 1 : Propagation of distribution using the Monte Carlo method (GUMS1), 2008
- H.S. Migon, D. Gamerman, Statistical Inference : an Integrated Approach (Arnold, London, 1999)
- A. Gelman, J.B. Carlin, H.S. Stern, D.B. Rubin, Bayesian Data Analysis, 2nd edn. (Chapman & Hall/CRC, Boca Raton, 2004)
- D. Gamerman, Markov Chain Monte Carlo (Chapman & Hall/CRC, Boca Raton, 1999)
- G. Grimmett, D. Stirzaker, Probability and Random Processes, 3rd edn. (Oxford University Press, Oxford, 2001)
- C. Elster, W. Wöger, M.G. Cox. Draft GUM Supplement 1 and Bayesian analysis, Metrologia 44, L31–L32 (2007) [CrossRef]
- 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]
- A.B. Forbes, J.A. Sousa, The GUM, Bayesian inference and forward and inverse uncertainty evaluation. Measurement 44, 1422–1435 (2011) [CrossRef]
- 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)
- 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
- 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)
- 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
- A. Possolo, B. Toman, Assessment of measurement uncertainty via observation equations. Metrologia 44, 464–475, 2007 [CrossRef]
- 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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