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
Download:
IMEKO-WC-2012-TC21-O4.pdf
DOI:
-
Event details
Event name:
XX IMEKO World Congress
Title:

Metrology for Green Growth

Place:
Busan, REPUBLIC of KOREA
Time:
09 September 2012 - 12 September 2012