MEASUREMENT UNCERTAINTY AND SUMMARISING MONTE CARLO SAMPLES

A. B. Forbes

Abstract

Many uncertainty evaluation applications require summary information about the distribution associated with the measurand. This paper looks at summarizing distributions on the basis of Monte Carlo samples and describes how relative entropy can be used as a measure of the effectiveness of the summary.

Keywords

kernel density estimation, measurement uncertainty, mixture distribution, relative entropy

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IMEKO-WC-2012-TC21-O4.pdf

DOI

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IMEKO TC

TC21 - Mathematical Tools for Measurements

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