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According to the [http://simlab.jrc.it/docs/html/sastd.html SimLab software web site] (where further discussion of the nature and purpose of sensitivity analysis can be found): ---- "The purpose of uncertainty analysis is to determine the uncertainty in estimates for dependent variables of interest. The purpose of sensitivity analysis is to determine the relationships between the uncertainty in the independent variables used in an analysis and the uncertainty in the resultant dependent variables." ---- Thus uncertainty analysis focuses on data, and how uncertainty in data propagates through computations. Sensitivity analysis sets out to establish the properties of computations (e.g. models) independently of particular data. The information generated by sensitivity analysis can be used to target [[uncertainty reduction]] activities, including for example data collection or model improvement, where it will have maximum impact. Many uncertainty analysis tools deal with parameter identifiability, ambiguity or uniqueness (see e.g. Spear and Hornberger, 1980; Wagener et al., 2003), and thus include some elements of [sensitivity analysis]. Plots showing model parameters vs. model results, such as the [[dotty plots]] of the [[GLUE]] methodology, provide a graphical indication of parameter sensitivity (Saltelli et al., 2004). Types of sensitivity analysis include: * [Local sensitivity analysis methods] * [Global sensitivity analysis methods] such as [variance-based sensitivity analysis] == Software == * [http://simlab.jrc.it/docs/html/main.html SimLab] == References and Further Reading == Hall, J.W., Tarantola, S., Bates, P.D. and Horritt, M.S., 2005. Distributed sensitivity analysis of flood inundation model calibration. Journal Of Hydraulic Engineering-Asce, 131(2): 117-126. Oakley, J.E. and O'Hagan, A., 2004. Probabilistic sensitivity analysis of complex models: a Bayesian approach. Journal Of The Royal Statistical Society Series B-Statistical Methodology, 66: 751-769. Pappenberger, F., Iorgulescu, I. and Beven, K.J., in press. [Sensitivity] Analysis based on Regional Splits (SARS - RT). Ratto, M., Tarantola, S. and Saltelli, A., 2001. [Sensitivity] analysis in model calibration: GSA-GLUE approach. Computer Physics Communications, 136(3): 212-224. Saltelli, A., Tarantola, A., Campolongo, F. and Ratto, M., 2004. [Sensitivity] Analysis in Practice - A Guide to Assessing Scientific Models. John Wiley & Sons, Chichester. Spear, R.C. and Hornberger, G.M., 1980. Eutrophication in Peel Inlet, II, Identification of critical uncertainties via Generalised [Sensitivity] Analysis. Water Resource Research, 14: 43-49. Wagener, T., McIntyre, N., Lees, M.J., Wheater, H.S. and Gupta, H.V., 2003. Towards reduced uncertainty in conceptual rainfall-runoff modelling: Dynamic identifiability analysis. Hydrological Processes, 17(2): 455-476. see also: http://en.wikipedia.org/wiki/Sensitivity_analysis
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