Journal of Statistical Software (Apr 2022)

sensobol: An R Package to Compute Variance-Based Sensitivity Indices

  • Arnald Puy,
  • Samuele Lo Piano,
  • Andrea Saltelli,
  • Simon A. Levin

DOI
https://doi.org/10.18637/jss.v102.i05
Journal volume & issue
Vol. 102
pp. 1 – 37

Abstract

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The R package sensobol provides several functions to conduct variance-based uncertainty and sensitivity analysis, from the estimation of sensitivity indices to the visual representation of the results. It implements several state-of-the-art first and total-order estimators and allows the computation of up to fourth-order effects, as well as of the approximation error, in a swift and user-friendly way. Its flexibility makes it also appropriate for models with either a scalar or a multivariate output. We illustrate its functionality by conducting a variance-based sensitivity analysis of three classic models: the Sobol' (1998) G function, the logistic population growth model of Verhulst (1845), and the spruce budworm and forest model of Ludwig, Jones, and Holling (1976).

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