Sensitivity Analysis as an Ingredient of Modeling

By Andrea Saltelli, Stefano Tarantola, Francesca Campolongo. 2000

787 citations recorded by the source corpus.

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Citations in the corpus

Making best use of model evaluations to compute sensitivity indices (2002, background): “A recent review of applications of this discipline can be found in [14,17].”
Variance-based sensitivity analysis of a forest growth model (2012, methodology): “A model-independent global SA technique is preferable for these models (Helton et al., 2006; Nossent et al., 2011; Saltelli, 2000; Saltelli and Annoni, 2010).”
A new uncertainty importance measure (2007, background): “It turns out that the rst order terms, Vi, are the expected amount of variance reduction that would be achieved for Y , if we were able to specify Xi exactly (Bedford (1998) [4], Saltelli et al (2000) [40])and, therefore, coincide with the IHi indicator [eq.”
Global sensitivity measures from given data (2013, background): “By a global SA, we gain several insights concerning the input-output mapping, and the key drivers of uncertainty (Saltelli et al., 2000).”
On the Relative Importance of Input Factors in Mathematical Models (2002, methodology): “A review of applications of the same methods was given by Saltelli, Tarantola, and Campolongo (2000).”
Review of surrogate modeling in water resources (2012, methodology): “, 2003], global sensitivity analysis methods [e.g., Hornberger and Spear, 1981; Saltelli et al., 2000], and any traditional Monte Carlo–based reliability or uncertainty analysis [e.”
Survey of sampling-based methods for uncertainty and sensitivity analysis (2006, unknown): “[56–60,195–210].”