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

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

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

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 bud-worm and forest model of Ludwig, Jones, and Holling (1976).

Original languageEnglish (US)
JournalJournal of Statistical Software
Volume102
Issue number5
DOIs
StatePublished - 2022

All Science Journal Classification (ASJC) codes

  • Software
  • Statistics and Probability
  • Statistics, Probability and Uncertainty

Keywords

  • modeling
  • R
  • sensitivity analysis
  • uncertainty

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