sensobol: an R package to compute variance-based sensitivity indices
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 third-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).
Keywords
Cite
@article{arxiv.2101.10103,
title = {sensobol: an R package to compute variance-based sensitivity indices},
author = {Arnald Puy and Samuele Lo Piano and Andrea Saltelli and Simon A. Levin},
journal= {arXiv preprint arXiv:2101.10103},
year = {2021}
}
Comments
The paper has been accepted for publication in the Journal of Statistical Software (expected for 2022)