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Convergence of sensitivity analysis methods for evaluating combined influences of model inputs
16 references·3 citing·26 second hop
Convergence of sensitivity analysis methods for evaluating combined influences of model inputs (2019)Convergence of sensitivity analysis metho…Sensitivity analysis of environmental models: A systematic review with practical workflow (2016)Sensitivity analysis of envir…Global Sensitivity Analysis of environmental models: Convergence and validation (2016)Global Sensitivity Analysis o…Uncertainty Management in Simulation-Optimization of Complex Systems (2015)Uncertainty Management in Sim…A Review on Global Sensitivity Analysis Methods (2015)A Review on Global Sensitivit…Convergence and uncertainty analyses in Monte-Carlo based sensitivity analysis (2010)Convergence and uncertainty a…Monte Carlo evaluation of derivative-based global sensitivity measures (2008)Monte Carlo evaluation of der…A new computational method of a moment-independent uncertainty importance measure (2008)A new computational method of…Global Sensitivity Analysis. The Primer (2007)Global Sensitivity Analysis. …Global sensitivity analysis using polynomial chaos expansions (2007)Global sensitivity analysis u…An effective screening design for sensitivity analysis of large models (2007)An effective screening design…Survey of sampling-based methods for uncertainty and sensitivity analysis (2006)Survey of sampling-based meth…Making best use of model evaluations to compute sensitivity indices (2002)Making best use of model eval…The use of graph theory in the sensitivity analysis of the model output: a second order screening method (1999)The use of graph theory in th…Sensitivity analysis of an environmental model: an application of different analysis methods (1997)Sensitivity analysis of an en…Importance measures in global sensitivity analysis of nonlinear models (1996)Importance measures in global…Factorial Sampling Plans for Preliminary Computational Experiments (1991)Factorial Sampling Plans for …An efficient elementary effect-based method for sensitivity analysis in identifying main and two-factor interaction effects (2023)An efficient elementary effec…Variance‐Based Global Sensitivity Analysis: A Methodological Framework and Case Study for Microkinetic Modeling (2022)Variance‐Based Global Sensiti…Benchmarking Active Subspace methods of global sensitivity analysis against variance-based Sobol' and Morris methods with established test functions (2022)Benchmarking Active Subspace …Design and Analysis of Computer Experiments (1989)A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code (2000)Random forests for global sensitivity analysis: A selective review (2020)The Future of Sensitivity Analysis: An essential discipline for systems modeling and policy support (2020)A Survey on High-dimensional Gaussian Process Modeling with Application to Bayesian Optimization (2022)Response Surface Methodology (1996)How to avoid a perfunctory sensitivity analysis (2010)The generalization of Latin hypercube sampling (2015)Statistics for Experimenters (1979)Handbook on Constructing Composite Indicators (2005)A Quantitative Model-Independent Method for Global Sensitivity Analysis of Model Output (1999)Stochastic Finite Elements: A Spectral Approach (1991)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)Variance based sensitivity analysis of model output. Design and estimator for the total sensitivity index (2009)Why so many published sensitivity analyses are false: A systematic review of sensitivity analysis practices (2019)The Proof and Measurement of Association between Two Things (1904)Progressive Latin Hypercube Sampling: An efficient approach for robust sampling-based analysis of environmental models (2017)Distribution-based sensitivity analysis from a generic input-output sample (2018)What has Global Sensitivity Analysis ever done for us? A systematic review to support scientific advancement and to inform policy-making in earth system modelling (2019)THE DESIGN OF OPTIMUM MULTIFACTORIAL EXPERIMENTS (1946)On the Experimental Attainment of Optimum Conditions (1951)Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code (1979)Latin hypercube sampling and the propagation of uncertainty in analyses of complex systems (2003)SALib: An open-source Python library for Sensitivity Analysis (2017)
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References

  • 2007Global Sensitivity Analysis. The Primer6,425 cited
  • 1991Factorial Sampling Plans for Preliminary Computational Experiments4,936 cited
  • 2007Global sensitivity analysis using polynomial chaos expansions2,547 cited
  • 2002Making best use of model evaluations to compute sensitivity indices2,225 cited
  • 2007An effective screening design for sensitivity analysis of large models2,024 cited
  • 1996Importance measures in global sensitivity analysis of nonlinear models2,014 cited
  • 2016Sensitivity analysis of environmental models: A systematic review with practical workflow1,722 cited
  • 2006Survey of sampling-based methods for uncertainty and sensitivity analysis1,240 cited
  • 2015A Review on Global Sensitivity Analysis Methods1,113 cited
  • 2016Global Sensitivity Analysis of environmental models: Convergence and validation394 cited
  • 2010Convergence and uncertainty analyses in Monte-Carlo based sensitivity analysis326 cited
  • 2008Monte Carlo evaluation of derivative-based global sensitivity measures294 cited
  • 1997Sensitivity analysis of an environmental model: an application of different analysis methods292 cited
  • 2015Uncertainty Management in Simulation-Optimization of Complex Systems192 cited
  • 2008

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A new computational method of a moment-independent uncertainty importance measure
137 cited
  • 1999The use of graph theory in the sensitivity analysis of the model output: a second order screening method130 cited
  • Cited by

    • 2022Benchmarking Active Subspace methods of global sensitivity analysis against variance-based Sobol' and Morris methods with established test functions18 cited
    • 2022Variance‐Based Global Sensitivity Analysis: A Methodological Framework and Case Study for Microkinetic Modeling9 cited
    • 2023An efficient elementary effect-based method for sensitivity analysis in identifying main and two-factor interaction effects9 cited