Extending a global sensitivity analysis technique to models with correlated parameters


The identification and representation of uncertainty is recognized as an essential component in model applications. One important approach in the identification of uncertainty is sensitivity analysis. Sensitivity analysis evaluates how the variations in the model output can be apportioned to variations in model parameters. One of the most popular… (More)
DOI: 10.1016/j.csda.2007.04.003

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