Probabilistic modelling: theory and practice
作者:
Barbara J. Petersen,
期刊:
Food Additives & Contaminants
(Taylor Available online 2000)
卷期:
Volume 17,
issue 7
页码: 591-599
ISSN:0265-203X
年代: 2000
DOI:10.1080/026520300412500
出版商: Taylor & Francis Group
关键词: Probabilistic Modelling Monte Carlo Analysis Exposure Precision
数据来源: Taylor
摘要:
Probabilistic modelling techniques allow much more realistic estimates of exposure and risk by computing the use of the full range of potential exposures rather than single ‘worst case’ exposures. However, these techniques require additional considerations regarding the appropriate data and models. This article reviews the theoretical aspects of probabilistic modelling and also considers some of the practical applications. The most common method, called Monte Carlo analysis, is discussed in some detail. The practical application of Monte Carlo to risk assessments is presented along with an evaluation of the input parameters. Topics also discussed include considerations of the requirements for precision and procedures for validation of assessments.
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