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Performing (variance-based) global sensitivity analysis (GSA) with dependent inputs has recently benefited from cooperative game theory concepts.By using this theory, despite the potential correlation between the inputs, meaningful sensitivity indices can be defined via allocation shares of the model output's variance to each input.
Notes on the n-Person Game – II: The Value of an n-Person Game
L. S. Shapley · 1951
Earlier work this paper cites.
A value for n-person games
L. S. Shapley · 1953
Earlier work this paper cites.
A Simplified Bargaining Model for the n-Person Cooperative Game
J. C. Harsanyi · 1963
Earlier work this paper cites.
Introduction to bivariate and multivariate analysis
R. H. Lindeman, P. F. Merenda, and R. Z. Gold · 1980
Earlier work this paper cites.
The jacknife estimate of variance
B. Efron and C. Stein · 1981
Earlier work this paper cites.
On weighted Shapley values
E. Kalai and D. Samet · 1987
Earlier work this paper cites.
Probabilistic values for games
R. J. Weber · 1988
Earlier work this paper cites.
On sensitivity estimation for nonlinear mathematical models
I. M. Sobol · 1990
Earlier work this paper cites.
Dominance analysis: A new approach to the problem of relative importance of predictors in multiple regression
D.V. Budescu · 1993
Earlier work this paper cites.
Dual axiomatizations of solutions of cooperative games, January 1996
Y. Funaki · 1996
Earlier work this paper cites.
The proportional value of a cooperative game
B. E. Feldman et al · 1999
Earlier work this paper cites.
The proportional value for positive cooperative games
K. M. Ortmann · 2000
Earlier work this paper cites.
Quasi-regression
J. An and A.B. Owen · 2001
Earlier work this paper cites.
A dual model of cooperative value
B. E Feldman · 2002
Earlier work this paper cites.
History and use of relative importance indices in organizational research
J.W. Johnson and J.M. LeBreton · 2004
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Relative Importance and Value
B. E. Feldman · 2005
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Uncertainty analysis with high dimensional dependence modelling
D. Kurowicka and R. Cooke · 2006
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A Theory of Attribution
B. E. Feldman · 2007
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Estimators of relative importance in linear regression based on variance decomposition
U. Grömping · 2007
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Global sensitivity analysis - The primer
A. Saltelli, M. Ratto, T. Andres, F. Campolongo, J. Cariboni, D. Gatelli, M. Salsana, and S. Tarantola · 2008
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An approximation theoretic perspective of Sobol’ indices with dependent variables
J. Hart and P. A. Gremaud · 2018
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Shapley effects for sensitivity analysis with dependent inputs: comparisons with Sobol’ indices, numerical estimation and applications
B. Iooss and C. Prieur · 2019
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Sensitivity analysis with dependent random variables : Estimation of the Shapley effects for unknown input distribution and linear Gaussian models
B. Broto · 2020
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Variance reduction for estimation of Shapley effects and adaptation to unknown input distribution
B. Broto, F. Bachoc, and M. Depecker · 2020
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Kernel-based ANOVA decomposition and Shapley effects–Application to global sensitivity analysis
S. Da Veiga · 2021
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Variable importance in regression models
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Shapley effects for global sensitivity analysis: Theory and computation
E. Song, B.L. Nelson, and J. Staum · 2016
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Springer Handbook on Uncertainty Quantification
R. Ghanem, D. Higdon, and H. Owhadi, editors · 2017
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Introduction: Sensitivity analysis
B. Iooss and A. Saltelli · 2017
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Sobol’ indices for problems defined in non-rectangular domains
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Computing Shapley effects for sensitivity analysis
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