The Bayesian analysis of a series of correlated indications of an unknown quantity is here presented when they are modelled by a joint Gaussian distribution and their covariance is assumed to be the (known) squared uncertainty associated with a systematic effect common to all the indications. An interesting application of the obtained results to the conformity assessment of a series production is also presented. A criterion is derived so that at least a portion p1 of the series production shows to have a characteristic value below a prescribed limit, with a probability not less than p2.
Bayesian analysis of repeated measurements affected by a systematic error and its application to conformity assessment / Carobbi, C.; Pennecchi, F.. - (2015), p. 1947. (Intervento presentato al convegno 21st IMEKO World Congress on Measurement in Research and Industry tenutosi a Prague Congress Centre, Prague, Czech Republic nel 30 August 2015 through 4 September 2015).
Bayesian analysis of repeated measurements affected by a systematic error and its application to conformity assessment
Pennecchi F.
2015
Abstract
The Bayesian analysis of a series of correlated indications of an unknown quantity is here presented when they are modelled by a joint Gaussian distribution and their covariance is assumed to be the (known) squared uncertainty associated with a systematic effect common to all the indications. An interesting application of the obtained results to the conformity assessment of a series production is also presented. A criterion is derived so that at least a portion p1 of the series production shows to have a characteristic value below a prescribed limit, with a probability not less than p2.File | Dimensione | Formato | |
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