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• W2906011738 abstract "The Shapley effects are global sensitivity indices: they quantify the impact of each input variable on the output variable in a model. In this work, we suggest new estimators of these sensitivity indices. When the input distribution is known, we investigate the already existing estimator and suggest a new one with a lower variance. Then, when the distribution of the inputs is unknown, we extend these estimators. Finally, we provide asymptotic properties of the estimators studied in this article." @default.
• W2906011738 created "2019-01-01" @default.
• W2906011738 creator A5030279456 @default.
• W2906011738 creator A5032830767 @default.
• W2906011738 creator A5064241978 @default.
• W2906011738 date "2020-02-05" @default.
• W2906011738 modified "2023-09-23" @default.
• W2906011738 title "Variance reduction for estimation of Shapley effects and adaptation to unknown input distribution" @default.
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• W2906011738 hasPublicationYear "2020" @default.
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