LUISA
Sensitivity analysis (SA) is a fundamental tool in the building, use and understanding of mathematical models of all forms. SA provides information regarding the behaviour of the underlying simulated system. This information ranges from the identification of relevant model factors (parameters or inputs) to model reduction or simplification, better understanding of the model structure for given components of a system, model quality assurance, and model building in general. Among the methods most used, it is possible to individuate three classes: screening methods, regression-based methods, variance-based methods. The most used screening method is the one proposed by Morris, particularly effective in identifying the few important factors in models with many factors or with high computational requirements. The second class includes the regression methods, which are based on the computation of standard or partial regression coefficients quantifying the effects due to a change in a factor value while the other are kept constant. Within this class, different methods can be used to generate the sample of factors combinations necessary to obtain the model evaluations and therefore to calculate the regression coefficients; here, Latin Hypercube Sampling (LHS), Random, and Quasi-Random LpTau will be used. The last class, variance-based methods, includes the Fourier Amplitude Sensitivity Test (FAST) , its evolution Extended FAST (E-FAST), and the method of Sobol'. All the methods belonging to this class computes total sensitivity indices for first and higher orders effects and are quite demanding in terms of computational time because of the high number of model evaluations needed for each model factor. The JRC.IPSC.MARS.SensitivityAnalysis is a component developed with the goal of making available the sensitivity analysis models implemented in the Simlab library via a user friendly application programming interface, in the memory managed environment of the Microsoft .NET platform (the Simlab library is targeted at C, C++, Matlab and Fortran). The component allows running sensitivity analysis on a model of choice using the methods mentioned above. It is implemented using C# under the Microsoft .NET v 3.0 platform. Sample applications inclusive of source code are provided to allow an easy start on SensitivityAnalysis use by different clients.