Probabilistic modelling: theory and practice.

B J Petersen

doi:10.1080/026520300412500

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PubMed · 10983583

Probabilistic modelling: theory and practice.

B J Petersen

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Abstract

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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Food Contamination Humans Models, Statistical Monte Carlo Method Pesticide Residues Risk Assessment Journal Article

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B J Petersen. 2000. Probabilistic modelling: theory and practice.. https://doi.org/10.1080/026520300412500

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