Cited by 48Probabilistic and Robust Engineering DesignGaussian Processes and Bayesian InferenceSimulation Techniques and Applications

GlobalSensitivity.jl: Performant and Parallel Global Sensitivity Analysis with Julia

Open access
Dixit, Vaibhav Kumar, Rackauckas, Christopher·2022·Journal of Open Source Software

Abstract

Global Sensitivity Analysis (GSA) methods are used to quantify the uncertainty in the output of a model with respect to the parameters.These methods allow practitioners to measure both parameters' individual contributions and the contribution of their interactions to the output uncertainty.GlobalSensitivity.jl is a Julia (Bezanson et al., 2017) package containing implementations of some of the most popular GSA methods.Currently it supports Delta Moment-Independent (Borgonovo, 2007;

Integrity signals

Registry

Crossref · 10.21105/joss.04561

Cites

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

We couldn’t retrieve this paper’s full text, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • System steady states can be computed using NLSolve.jl or HomotopyContinuation.jl; bifurcation structures can be calculated with BifurcationKit.jl; sensitivity and uncertainty can be investigated with SciMLSensitivity.jl and GlobalSensitivity.jl.

    “More broadly, system steady states can be computed using the NLSolve.jl or HomotopyContinuation.jl Julia packages [57]; bifurcation structures can be calculated, and bifurcation diagrams generated, with the BifurcationKit.jl library [61]; and SciMLSensitivity.jl and GlobalSensitivity.jl can be used to investigate the sensitivity and uncertainty of model solutions with regard to parameters [62].”

    From Catalyst: Fast and flexible modeling of reaction networks (2023) · cites this paper as [62]

The citation lists haven’t been fetched yet

References 24 · Cited by 48

Authors
Dixit, V. K., & Rackauckas, C.
Affiliations
Massachusetts Institute of Technology (US)
Venue
Journal of Open Source Software
Published
2022-08-17
Volume
7
Issue
76
Pages
4561
ISSN
2475-9066 (ISSN-L)
OpenAlex
W4292133640
Cited by
48
References
24
Citations by year
2026: 13 · 2025: 11 · 2024: 13 · 2023: 9 · 2021: 1 · 2019: 1
FWCI
4.98
Type
journal article
Language
en
Open access
Locations
The Journal of Open Source Software (publishedVersion, cc-by)
Funders
  • National Science Foundation (2029670, 2103804, S002283-USAID, 1835443)
  • U.S. Department of Energy (DEAR0001211, DEAR0001222)
  • United States Agency for International Development (S002283‐USAID)
  • University of Pennsylvania
  • Pennsylvania State University
  • Equinor (308817)
  • Norges Forskningsråd (308817)
  • Advanced Research Projects Agency - Energy (DE-AR0001222, DE-AR0001211)
  • U.S. Air Force (FA8750‐19‐2‐1000)
  • Advanced Research Projects Agency (DE-AR0001211, DE-AR0001222)
  • Division of Electrical, Communications and Cyber Systems
Topics
  • Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Probabilistic and Robust Engineering Design
  • Physical Sciences › Computer Science › Artificial Intelligence › Gaussian Processes and Bayesian Inference
  • Social Sciences › Decision Sciences › Management Science and Operations Research › Simulation Techniques and Applications
Keywords
global sensitivity analysis, Julia, parallel computing, uncertainty quantification, parameter interactions, software package

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review