Abstract
Sensitivity and uncertainty analysis are important ingredients of the modelling process, and contribute substantially to a reliable and efficient development, assessment and application of mathematical models. Quantifying how much the concerned model components contribute to the sensitivity and uncertainty in the model outputs is an essential issue in these analyses. An overview is given of various measures which are commonly used for assessing these contributions; their main features are discussed and critically evaluated.
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