BAYESIAN ANALYSIS OF REPEATED MEASUREMENTS AFFECTED BY A SYSTEMATIC ERROR AND ITS APPLICATION TO CONFORMITY ASSESSMENT

Carlo Carobbi, Francesca Pennecchi

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 <i>p</i>₁ of the series production shows to have a characteristic value below a prescribed limit, with a probability not less than <i>p</i>₂.

Keywords

Bayesian inference, repeated measurements, systematic effect, conformity assessment

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IMEKO-WC-2015-TC21-410.pdf

DOI

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IMEKO TC

TC21 - Mathematical Tools for Measurements

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