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Radiological Risk Assessment and Environmental Analysis$
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John E. Till and Helen Grogan

Print publication date: 2008

Print ISBN-13: 9780195127270

Published to Oxford Scholarship Online: September 2008

DOI: 10.1093/acprof:oso/9780195127270.001.0001

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Estimating and Applying Uncertainty in Assessment models

Estimating and Applying Uncertainty in Assessment models

Chapter:
(p.465) 11 Estimating and Applying Uncertainty in Assessment models
Source:
Radiological Risk Assessment and Environmental Analysis
Author(s):

Thomas B. Kirchner

Publisher:
Oxford University Press
DOI:10.1093/acprof:oso/9780195127270.003.0011

This chapter discusses probabilistic methods for conducting uncertainty analysis, methods that can be use to evaluate both local and global sensitivity of models to parameters, and issues related to the validation of models that express uncertainty in their results. Analytical and Monte Carlo methods for propagating uncertainty through models are described, along with potential limitations of these methods and the problems that can be encountered. The chapter introduces methods for assigning distributions to model parameters. Statistical methods that can be used to help interpret and express the results of probabilistic uncertainty analyses, such as confidence and tolerance intervals, are introduced and their pertinent assumptions are described. Various statistical analyses that can be used for sensitivity analysis and their associated sampling designs are reviewed.

Keywords:   uncertainty analysis, sensitivity analysis, validation, Monte Carlo, distribution, statistics, tolerance interval

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