Variance-based global sensitivity analysis of numerical models using R Article Swipe
Hossein Mohammadi
,
Peter Challenor
,
Clémentine Prieur
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2206.11348
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2206.11348
Sensitivity analysis plays an important role in the development of computer models/simulators through identifying the contribution of each (uncertain) input factor to the model output variability. This report investigates different aspects of the variance-based global sensitivity analysis in the context of complex black-box computer codes. The analysis is mainly conducted using two R packages, namely sensobol (Puy et al., 2021) and sensitivity (Iooss et al., 2021). While the package sensitivity is equipped with a rich set of methods to conduct sensitivity analysis, especially in the case of models with dependent inputs, the package sensobol offers a bunch of user-friendly tools for the visualisation purposes. Several illustrative examples are supplied that allow the user to learn both packages easily and benefit from their features.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2206.11348
- https://arxiv.org/pdf/2206.11348
- OA Status
- green
- Cited By
- 1
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4283461838
All OpenAlex metadata
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https://openalex.org/W4283461838Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.2206.11348Digital Object Identifier
- Title
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Variance-based global sensitivity analysis of numerical models using RWork title
- Type
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preprintOpenAlex work type
- Language
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enPrimary language
- Publication year
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2022Year of publication
- Publication date
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2022-06-22Full publication date if available
- Authors
-
Hossein Mohammadi, Peter Challenor, Clémentine PrieurList of authors in order
- Landing page
-
https://arxiv.org/abs/2206.11348Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/2206.11348Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
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https://arxiv.org/pdf/2206.11348Direct OA link when available
- Concepts
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Sensitivity (control systems), Computer science, Set (abstract data type), Context (archaeology), Visualization, Variance (accounting), Data mining, R package, Computational science, Programming language, Engineering, Electronic engineering, Biology, Business, Accounting, PaleontologyTop concepts (fields/topics) attached by OpenAlex
- Cited by
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1Total citation count in OpenAlex
- Citations by year (recent)
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2025: 1Per-year citation counts (last 5 years)
- Related works (count)
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10Other works algorithmically related by OpenAlex
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