Estimating the approximation error when fixing unessential factors in global sensitivity analysis

By Ilya M. Sobol, Stefano Tarantola, Debora Gatelli, Sergei S. Kucherenko, Wolfgang Mauntz. Reliability Engineering & System Safety, 2007

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Variance-based global sensitivity analysis for multiple scenarios and models with implementation using sparse grid collocation (2015, methodology): “…paper is to use computationally efficient methods for global sensitivity analysis, which is well known to be computationally expensive because it requires Monte Carlo (MC) simulation with a large number of model executions (Sobol’, 1993; Jansen, 1999; Sobol’ et al., 2007; Saltelli et al., 2010).”
The Future of Sensitivity Analysis: An essential discipline for systems modeling and policy support (2020, positive): “…(b) dimensionality reduction to identify uninfluential factors in a system that may be redundant and fixed or removed in subsequent analyses (e.g., Sobol ’ et al., 2007); (c) data worth assessment to identify processes, parameters and scales that dominantly control a system, for which new data…”