Numerical Aspects in the Evaluation of Measurement Uncertainty

Abstract : Numerical quantification of the results from a measurement uncertainty computation is considered in terms of the inputs to that computation. The primary output is often an approximation to the PDF (probability density function) for the univariate or multivariate measurand (the quantity intended to be measured). All results of interest can be derived from this PDF. We consider uncertainty elicitation, propagation of distributions through a computational model, Bayes’ rule and its implementation and other numerical considerations, representation of the PDF for the measurand, and sensitivities of the numerical results with respect to the inputs to the computation. Speculations are made regarding future requirements in the area and relationships to problems in uncertainty quantification for scientific computing.
Type de document :
Communication dans un congrès
Andrew M. Dienstfrey; Ronald F. Boisvert. 10th Working Conference on Uncertainty Quantification in Scientific Computing (WoCoUQ), Aug 2011, Boulder, CO, United States. Springer, IFIP Advances in Information and Communication Technology, AICT-377, pp.180-194, 2012, Uncertainty Quantification in Scientific Computing. 〈10.1007/978-3-642-32677-6_12〉
Liste complète des métadonnées

Littérature citée [30 références]  Voir  Masquer  Télécharger

https://hal.inria.fr/hal-01518677
Contributeur : Hal Ifip <>
Soumis le : vendredi 5 mai 2017 - 10:55:59
Dernière modification le : vendredi 5 mai 2017 - 10:57:09
Document(s) archivé(s) le : dimanche 6 août 2017 - 12:33:48

Fichier

978-3-642-32677-6_12_Chapter.p...
Fichiers produits par l'(les) auteur(s)

Licence


Distributed under a Creative Commons Paternité 4.0 International License

Identifiants

Citation

Maurice Cox, Alistair Forbes, Peter Harris, Clare Matthews. Numerical Aspects in the Evaluation of Measurement Uncertainty. Andrew M. Dienstfrey; Ronald F. Boisvert. 10th Working Conference on Uncertainty Quantification in Scientific Computing (WoCoUQ), Aug 2011, Boulder, CO, United States. Springer, IFIP Advances in Information and Communication Technology, AICT-377, pp.180-194, 2012, Uncertainty Quantification in Scientific Computing. 〈10.1007/978-3-642-32677-6_12〉. 〈hal-01518677〉

Partager

Métriques

Consultations de la notice

88

Téléchargements de fichiers

33