sensobol: An R Package to Compute Variance-Based Sensitivity Indices
Dublin Core
Title
sensobol: An R Package to Compute Variance-Based Sensitivity Indices
Subject
: R, uncertainty, sensitivity analysis, modeling
Description
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).
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).
Creator
Arnald Puy
Source
https://www.jstatsoft.org/article/view/v102i05
Publisher
Princeton University
Date
April 2022
Contributor
Fajar bagus W
Format
PDF
Language
English
Type
Text
Files
Collection
Citation
Arnald Puy, “sensobol: An R Package to Compute Variance-Based Sensitivity Indices,” Repository Horizon University Indonesia, accessed April 4, 2025, https://repository.horizon.ac.id/items/show/8251.