Properties of the metafunction over 1000 realisations: distribution of the fraction of active inputs (left); distribution of Si (right).

Properties of the metafunction over 1000 realisations: distribution of the fraction of active inputs (left); distribution of Si (right).

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Comparison studies of global sensitivity analysis (GSA) approaches are limited in that they are performed on a single model or a small set of test functions, with a limited set of sample sizes and dimensionalities. This work introduces a flexible ‘metafunction’ framework to benchmarking which randomly generates test problems of varying dimensionali...

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... One of the main SA methods is Sobol' analysis, which studies how the dispersion of individual components of the input data (and their combinations) affects the dispersion of output data [16][17][18][19]. Improvements to this method can be found in recent works [20,21]. ...
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... If the model runs fast, then perhaps up to a dozen inputs can be considered. Otherwise, owing to the sparsity-ofeffects principle-aka Pareto principle (Becker, 2020)-it is reasonable to expect that a sufficiently large number of total indices will be close to zero. Thus, we may still apply the inference method proposed, but to a well-chosen selection of inputs. ...
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