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Academic users can download SobolGSA free of charge via the following link: www.imperial.ac.uk/process-systems-engineering/research/free-software/sobolgsa-software/

Commercial users can licence the latest version of SobolGSA by emailing quicktech@imperialinnovations.co.uk. Price is on application. 



High complexity models are commonly used in physics, chemistry, bioengineering, environmental studies, finance, statistics and other fields. Models with a large number of variables require significant time and computational power to produce outputs. However, in practice, some of these variables will have little impact on the model outputs. A metamodel treats these variables as constants, which reduces the amount of time and computing effort to produce outputs that are very similar to the full model. Global sensitivity analysis (GSA) is a method of analysing the effect of a variable on the outputs of a model in order to construct a metamodel.

SobolGSA is a user-friendly software application that can conduct global sensitivy analyses and construct metamodels. It can:

  • Be applied to both static and time-dependent problems
  • Handle several outputs for analysis - these can be time-dependent
  • Construct metamodels either from explicitly known models or directly from data produced by "black-box" models
  • Output metamodels as C# or MATLAB files (SobolGSA can be linked to MATLAB)
  • Deploy three different metamodeling techniques, including Quasi Random Sampling-High dimensional model representation (QRS-HDMR) and Radial Basis Function (RBF)
  • Deploy several GSA measures including Sobol indices, FAST, Morris and derivative-based measures
  • Allow users to save both settings as well as results

SobolGSA has over 300 users worldwide



SobolGSA can run a number of different analyses and models


SobolGSA can model multiple outputs


Sensitivity analysis can return the first order effect of multiple inputs



Metamodels can be easily compared to original models

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Global sensitivity analysis and metamodelling software

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