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Global Sensitivity Analysis: a new generation of mighty estimators based on rank statistics
16 references·3 citing·29 second hop
Global Sensitivity Analysis: a new generation of mighty estimators based on rank statistics (2020)Global Sensitivity Analysis: a new genera…A New Coefficient of Correlation (2020)A New Coefficient of Correlat…Shapley effects for sensitivity analysis with correlated inputs: comparisons with Sobol' indices, numerical estimation and applications (2017)Shapley effects for sensitivi…On Shapley Value for Measuring Importance of Dependent Inputs (2017)On Shapley Value for Measurin…Shapley Effects for Global Sensitivity Analysis: Theory and Computation (2016)Shapley Effects for Global Se…Sobol' Indices and Shapley Value (2014)Sobol' Indices and Shapley Va…Sensitivity analysis for multidimensional and functional outputs (2014)Sensitivity analysis for mult…Global sensitivity analysis with dependence measures (2014)Global sensitivity analysis w…Asymptotic normality and efficiency of two Sobol index estimators (2013)Asymptotic normality and effi…Multivariate sensitivity analysis to measure global contribution of input factors in dynamic models (2010)Multivariate sensitivity anal…Moment Independent Importance Measures: New Results and Analytical Test Cases (2010)Moment Independent Importance…Uncertainty in Industrial Practice (2008)Uncertainty in Industrial Pra…Global sensitivity analysis using polynomial chaos expansions (2007)Global sensitivity analysis u…A new uncertainty importance measure (2006)A new uncertainty importance …Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates (2001)Global sensitivity indices fo…Design and Analysis of Computer Experiments (1989)Design and Analysis of Comput…A value for n -person games (1988)A value for n -person gamesMultifidelity uncertainty quantification and model validation of large-scale multidisciplinary systems (2022)Multifidelity uncertainty qua…Kernel-based ANOVA decomposition and Shapley effects -- Application to global sensitivity analysis (2021)Kernel-based ANOVA decomposit…Estimation of high-order moment-independent importance measures for Shapley value analysis (2020)Estimation of high-order mome…Factorial Sampling Plans for Preliminary Computational Experiments (1991)A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code (2000)A simple and efficient method for global sensitivity analysis based on cumulative distribution functions (2015)Variable importance analysis: A comprehensive review (2015)The Future of Sensitivity Analysis: An essential discipline for systems modeling and policy support (2020)A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code (1979)Empirical Model Building and Response Surfaces (1988)Global Sensitivity Analysis. The Primer (2007)Global Sensitivity Analysis for multivariate output using Polynomial Chaos Expansion (2014)Human-oriented design of collaborative robots (2017)Stochastic Finite Elements: A Spectral Approach (1991)A Quantitative Model-Independent Method for Global Sensitivity Analysis of Model Output (1999)The Wiener--Askey Polynomial Chaos for Stochastic Differential Equations (2002)Adaptive sparse polynomial chaos expansion based on least angle regression (2010)UQLab: A Framework for Uncertainty Quantification in Matlab (2014)Sensitivity analysis of environmental models: A systematic review with practical workflow (2016)Making best use of model evaluations to compute sensitivity indices (2002)Variance Reduction for Estimation of Shapley Effects and Adaptation to Unknown Input Distribution (2020)Cores of convex games (1971)Graphs and Cooperation in Games (1977)Property Rights and the Nature of the Firm (1990)Latin hypercube sampling and the propagation of uncertainty in analyses of complex systems (2003)Variance based sensitivity analysis of model output. Design and estimator for the total sensitivity index (2009)Taking the Human Out of the Loop: A Review of Bayesian Optimization (2015)Better estimation of small sobol' sensitivity indices (2013)SALib: An open-source Python library for Sensitivity Analysis (2017)On weak conditional convergence of bivariate Archimedean and Extreme Value copulas, and consequences to nonparametric estimation (2021)On a multivariate copula-based dependence measure and its estimation (2022)Effectiveness of AI ‐Driven Vocal Art Tools in Enhancing Student Performance and Creativity (2025)
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References

  • 1989Design and Analysis of Computer Experiments6,958 cited
  • 2001Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates6,377 cited
  • 1988A value for n -person games4,956 cited
  • 2007Global sensitivity analysis using polynomial chaos expansions2,547 cited
  • 2006A new uncertainty importance measure1,030 cited
  • 2020A New Coefficient of Correlation373 cited
  • 2014Sobol' Indices and Shapley Value268 cited
  • 2013Asymptotic normality and efficiency of two Sobol index estimators246 cited
  • 2016Shapley Effects for Global Sensitivity Analysis: Theory and Computation244 cited
  • 2010Multivariate sensitivity analysis to measure global contribution of input factors in dynamic models243 cited
  • 2008Uncertainty in Industrial Practice243 cited
  • 2014Global sensitivity analysis with dependence measures195 cited
  • 2010Moment Independent Importance Measures: New Results and Analytical Test Cases176 cited
  • 2017On Shapley Value for Measuring Importance of Dependent Inputs169 cited
  • 2014Sensitivity analysis for multidimensional and functional outputs131 cited

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2017
Shapley effects for sensitivity analysis with correlated inputs: comparisons with Sobol' indices, numerical estimation and applications
128 cited

Cited by

  • 2021Kernel-based ANOVA decomposition and Shapley effects -- Application to global sensitivity analysis11 cited
  • 2022Multifidelity uncertainty quantification and model validation of large-scale multidisciplinary systems9 cited
  • 2020Estimation of high-order moment-independent importance measures for Shapley value analysis8 cited