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Simple approach to emulating complex computer models for global sensitivity analysis
16 references·3 citing·39 second hop
Simple approach to emulating complex computer models for global sensitivity analysis (2015)Simple approach to emulating complex comp…Estimating Multiparameter Partial Expected Value of Perfect Information from a Probabilistic Sensitivity Analysis Sample (2013)Estimating Multiparameter Par…Global Sensitivity Analysis for Systems with Independent and/or Correlated Inputs (2010)Global Sensitivity Analysis f…DAKOTA : a multilevel parallel object-oriented framework for design optimization, parameter estimation, uncertainty quantification, and sensitivity analysis. Version 5.0, user's manual. (2010)DAKOTA : a multilevel paralle…Adaptive sparse polynomial chaos expansion based on least angle regression (2010)Adaptive sparse polynomial ch…Variance based sensitivity analysis of model output. Design and estimator for the total sensitivity index (2009)Variance based sensitivity an…Implementation and evaluation of nonparametric regression procedures for sensitivity analysis of computationally demanding models (2009)Implementation and evaluation…State Dependent Parameter metamodelling and sensitivity analysis (2007)State Dependent Parameter met…Multiple predictor smoothing methods for sensitivity analysis: Description of techniques (2007)Multiple predictor smoothing …Global sensitivity analysis using polynomial chaos expansions (2007)Global sensitivity analysis u…Sensitivity analysis when model outputs are functions (2006)Sensitivity analysis when mod…Estimating the approximation error when fixing unessential factors in global sensitivity analysis (2006)Estimating the approximation …Probabilistic Sensitivity Analysis of Complex Models: A Bayesian Approach (2004)Probabilistic Sensitivity Ana…An importance quantification technique in uncertainty analysis for computer models (2002)An importance quantification …Analysis of variance designs for model output (1999)Analysis of variance designs …Factorial Sampling Plans for Preliminary Computational Experiments (1991)Factorial Sampling Plans for …Study of the sensitivity of coupled reaction systems to uncertainties in rate coefficients. I Theory (1973)Study of the sensitivity of c…An Improved Copula‐Based Framework for Efficient Global Sensitivity Analysis (2024)An Improved Copula‐Based Fram…Model Variable Augmentation (MVA) for Diagnostic Assessment of Sensitivity Analysis Results (2019)Model Variable Augmentation (…Global sensitivity analysis with a hierarchical sparse metamodeling method (2018)Global sensitivity analysis w…Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates (2001)Making best use of model evaluations to compute sensitivity indices (2002)Sensitivity Analysis in Practice (2002)Estimation of global sensitivity indices for models with dependent variables (2011)Sobol' Indices and Shapley Value (2014)A guide to uncertainty quantification and sensitivity analysis for cardiovascular applications (2015)Stochastic Finite Elements: A Spectral Approach (1991)Response Surface Methodology: Process and Product Optimization Using Designed Experiments (1996)A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code (2000)Comparison of Non-Intrusive Polynomial Chaos and Stochastic Collocation Methods for Uncertainty Quantification (2009)Recent Advances in Non-Intrusive Polynomial Chaos and Stochastic Collocation Methods for Uncertainty Analysis and Design (2009)Chaospy: An open source tool for designing methods of uncertainty quantification (2015)A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code (1979)Large Sample Properties of Simulations Using Latin Hypercube Sampling (1987)From screening to quantitative sensitivity analysis. A unified approach (2011)Variable importance analysis: A comprehensive review (2015)The Future of Sensitivity Analysis: An essential discipline for systems modeling and policy support (2020)The Wiener--Askey Polynomial Chaos for Stochastic Differential Equations (2002)Efficient computation of global sensitivity indices using sparse polynomial chaos expansions (2010)UQLab: A Framework for Uncertainty Quantification in Matlab (2014)POLYNOMIAL-CHAOS-BASED KRIGING (2015)A Quantitative Model-Independent Method for Global Sensitivity Analysis of Model Output (1999)Sensitivity analysis of environmental models: A systematic review with practical workflow (2016)Design and Analysis of Computer Experiments (1989)STATISTICS FOR SPATIAL DATA (1992)Mixed aleatory-epistemic uncertainty quantification with stochastic expansions and optimization-based interval estimation (2011)Asymptotic normality and efficiency of two Sobol index estimators (2013)Global Sensitivity Analysis. The Primer (2007)How to avoid a perfunctory sensitivity analysis (2010)SALib: An open-source Python library for Sensitivity Analysis (2017)Importance measures in global sensitivity analysis of nonlinear models (1996)A new uncertainty importance measure (2006)Bayesian analysis of computer code outputs: A tutorial (2006)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)Identification and Review of Sensitivity Analysis Methods (2002)Model-based design of experiments for parameter precision: State of the art (2007)
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References

  • 1991Factorial Sampling Plans for Preliminary Computational Experiments4,936 cited
  • 2009Variance based sensitivity analysis of model output. Design and estimator for the total sensitivity index3,567 cited
  • 2007Global sensitivity analysis using polynomial chaos expansions2,547 cited
  • 2010Adaptive sparse polynomial chaos expansion based on least angle regression1,507 cited
  • 2004Probabilistic Sensitivity Analysis of Complex Models: A Bayesian Approach1,085 cited
  • 1973Study of the sensitivity of coupled reaction systems to uncertainties in rate coefficients. I Theory1,041 cited
  • 2010DAKOTA : a multilevel parallel object-oriented framework for design optimization, parameter estimation, uncertainty quantification, and sensitivity analysis. Version 5.0, user's manual.775 cited
  • 1999Analysis of variance designs for model output648 cited
  • 2006Estimating the approximation error when fixing unessential factors in global sensitivity analysis395 cited
  • 2009Implementation and evaluation of nonparametric regression procedures for sensitivity analysis of computationally demanding models327 cited
  • 2002An importance quantification technique in uncertainty analysis for computer models251 cited
  • 2013Estimating Multiparameter Partial Expected Value of Perfect Information from a Probabilistic Sensitivity Analysis Sample248 cited
  • 2010Global Sensitivity Analysis for Systems with Independent and/or Correlated Inputs

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242 cited
  • 2007State Dependent Parameter metamodelling and sensitivity analysis217 cited
  • 2007Multiple predictor smoothing methods for sensitivity analysis: Description of techniques173 cited
  • 2006Sensitivity analysis when model outputs are functions162 cited
  • Cited by

    • 2019Model Variable Augmentation (MVA) for Diagnostic Assessment of Sensitivity Analysis Results15 cited
    • 2018Global sensitivity analysis with a hierarchical sparse metamodeling method14 cited
    • 2024An Improved Copula‐Based Framework for Efficient Global Sensitivity Analysis10 cited