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A function dataset for benchmarking in sensitivity analysis

In this paper a dataset of functions has been described which includes analytical values of Sobol’ first-order and total-order indices. This unique collection represents a valid benchmark to evaluate sensitivity analysis methodologies and allows the comparison of different technique outcomes. The be...

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Detalles Bibliográficos
Autores principales: Azzini, Ivano, Rosati, Rossana
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8989694/
https://www.ncbi.nlm.nih.gov/pubmed/35402667
http://dx.doi.org/10.1016/j.dib.2022.108071
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author Azzini, Ivano
Rosati, Rossana
author_facet Azzini, Ivano
Rosati, Rossana
author_sort Azzini, Ivano
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description In this paper a dataset of functions has been described which includes analytical values of Sobol’ first-order and total-order indices. This unique collection represents a valid benchmark to evaluate sensitivity analysis methodologies and allows the comparison of different technique outcomes. The benchmarking dataset was introduced in Azzini and Rosati following a practice already consolidated in many fields of research such as machine learning or Statistics. The dataset should be considered as an initial proposal open to being easily updated, extended, or modified by new mathematical functions or models in the future.
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spelling pubmed-89896942022-04-09 A function dataset for benchmarking in sensitivity analysis Azzini, Ivano Rosati, Rossana Data Brief Data Article In this paper a dataset of functions has been described which includes analytical values of Sobol’ first-order and total-order indices. This unique collection represents a valid benchmark to evaluate sensitivity analysis methodologies and allows the comparison of different technique outcomes. The benchmarking dataset was introduced in Azzini and Rosati following a practice already consolidated in many fields of research such as machine learning or Statistics. The dataset should be considered as an initial proposal open to being easily updated, extended, or modified by new mathematical functions or models in the future. Elsevier 2022-03-20 /pmc/articles/PMC8989694/ /pubmed/35402667 http://dx.doi.org/10.1016/j.dib.2022.108071 Text en © 2022 The Authors. Published by Elsevier Inc. https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Data Article
Azzini, Ivano
Rosati, Rossana
A function dataset for benchmarking in sensitivity analysis
title A function dataset for benchmarking in sensitivity analysis
title_full A function dataset for benchmarking in sensitivity analysis
title_fullStr A function dataset for benchmarking in sensitivity analysis
title_full_unstemmed A function dataset for benchmarking in sensitivity analysis
title_short A function dataset for benchmarking in sensitivity analysis
title_sort function dataset for benchmarking in sensitivity analysis
topic Data Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8989694/
https://www.ncbi.nlm.nih.gov/pubmed/35402667
http://dx.doi.org/10.1016/j.dib.2022.108071
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