Uncertainty and Sensitivity Analysis
Marvin Rausand, Stein Haugen
Abstract
Marvin Rausand, Stein Haugen
Abstract
Results from risk analyses are always uncertain, and to make good decisions about risk, it is important that this uncertainty is understood by the decision-maker. A discussion is provided of uncertainty and specifically what the main contributors and sources of uncertainty are. Epistemic and aleatory uncertainty is introduced, and model uncertainty, parameter uncertainty, and completeness uncertainty are described and discussed. Methods for uncertainty analysis are briefly introduced and also sensitivity analysis as a tool for investigating the effect of uncertainty on the results from risk analysis.
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Results from risk analyses are always uncertain, and to make good decisions about risk, it is important that this uncertainty is understood by the decision-maker. A discussion is provided of uncertainty and specifically what the main contributors and sources of uncertainty are. Epistemic and aleatory uncertainty is introduced, and model uncertainty, parameter uncertainty, and completeness uncertainty are described and discussed. Methods for uncertainty analysis are briefly introduced and also sensitivity analysis as a tool for investigating the effect of uncertainty on the results from risk analysis.
Key concepts: Uncertainty analysis, Uncertainty quantification, Sensitivity analysis, Completeness (order theory), Decision maker, Sensitivity (control systems), Uncertainty, Propagation of uncertainty