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OLS Field Name OLS Field Data
Main Title Guiding Principles for Monte Carlo Analysis.
Author Firestone, M. ; Fenner-Crisp, P. ; Barry, T. ; Bennett, D. ; Chang, S. ;
CORP Author Environmental Protection Agency, Washington, DC. Risk Assessment Forum.
Publisher Mar 97
Year Published 1997
Report Number EPA/630/R-07/001;
Stock Number PB97-188106
Additional Subjects Monte Carlo method ; Risk assessment ; Public health ; Environmental exposure ; Ecology ; Ecosystems ; Environmental transport ; Dose-response relationships ; Probability distribution functions ; Uncertainty analysis ; Variability ; Quantitative analysis ; Statistical analysis ; US EPA ; Government policies ; Environmental fate
Holdings
Library Call Number Additional Info Location Last
Modified
Checkout
Status
NTIS  PB97-188106 Most EPA libraries have a fiche copy filed under the call number shown. Check with individual libraries about paper copy. NTIS 12/22/1997
Collation 42p
Abstract
EPA is issuing a policy and preliminary guidance on using probabilistic analysis. The policy documents the EPA's position that such probabilistic analysis techniques as Monte Carlo analysis, given adequate supporting data and credible assumptions, can be viable statistical tools for analyzing variability and uncertainty in risk assessments. The policy also establishes conditions that are to be satisfied by risk assessments that use probabilistic techniques. These conditions are in keeping with the Agency's risk characterization policy that requires clarity, consistency, transparency, and reproducibility in risk assessments. The report presents a general framework and broad set of principles important for ensuring good scientific practices. Many of the principles apply generally to the various techniques for conducting quantitative analyses of variability and uncertainty; however, the focus of the principles is on Monte Carlo analysis. The guiding principles are intended to serve as a minimum set of principles and are not intended to constrain or prevent the use of new or innovative improvements where scientifically defensible.