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Fast sensitivity analysis methods for computationally expensive models with multi-dimensional output
16 references·2 citing·27 second hop
Fast sensitivity analysis methods for computationally expensive models with multi-dimensional output (2018)Fast sensitivity analysis methods for com…A Review on Global Sensitivity Analysis Methods (2015)A Review on Global Sensitivit…DiceKriging , DiceOptim : Two R Packages for the Analysis of Computer Experiments by Kriging-Based Metamodeling and Optimization (2012)DiceKriging , DiceOptim : Two…How to avoid a perfunctory sensitivity analysis (2010)How to avoid a perfunctory se…Choosing the Sample Size of a Computer Experiment: A Practical Guide (2009)Choosing the Sample Size of a…Calculations of Sobol indices for the Gaussian process metamodel (2008)Calculations of Sobol indices…Global Sensitivity Analysis. The Primer (2007)Global Sensitivity Analysis. …Bayesian analysis of computer code outputs: A tutorial (2006)Bayesian analysis of computer…Probabilistic Sensitivity Analysis of Complex Models: A Bayesian Approach (2004)Probabilistic Sensitivity Ana…Making best use of model evaluations to compute sensitivity indices (2002)Making best use of model eval…A Quantitative Model-Independent Method for Global Sensitivity Analysis of Model Output (1999)A Quantitative Model-Independ…Importance measures in global sensitivity analysis of nonlinear models (1996)Importance measures in global…9 Computer experiments (1996)9 Computer experimentsScreening, Predicting, and Computer Experiments (1992)Screening, Predicting, and Co…The origins of kriging (1990)The origins of krigingSpatial statistics (1981)Spatial statisticsStudy of the sensitivity of coupled reaction systems to uncertainties in rate coefficients. I Theory (1973)Study of the sensitivity of c…Variance‐Based Global Sensitivity Analysis: A Methodological Framework and Case Study for Microkinetic Modeling (2022)Variance‐Based Global Sensiti…Multi-method global sensitivity analysis of mathematical models (2022)Multi-method global sensitivi…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)Statistics for Experimenters (1979)Handbook on Constructing Composite Indicators (2005)An effective screening design for sensitivity analysis of large models (2007)Factorial Sampling Plans for Preliminary Computational Experiments (1991)Global sensitivity analysis using polynomial chaos expansions (2007)STIGLER'S LAW OF EPONYMY* (1980)STATISTICS FOR SPATIAL DATA (1992)Covariance Tapering for Interpolation of Large Spatial Datasets (2006)Fixed Rank Kriging for Very Large Spatial Data Sets (2008)Recent Advances in Bayesian Optimization (2023)Variance based sensitivity analysis of model output. Design and estimator for the total sensitivity index (2009)Sensitivity analysis of environmental models: A systematic review with practical workflow (2016)SALib: An open-source Python library for Sensitivity Analysis (2017)From screening to quantitative sensitivity analysis. A unified approach (2011)Why so many published sensitivity analyses are false: A systematic review of sensitivity analysis practices (2019)A new uncertainty importance measure (2006)Identification and Review of Sensitivity Analysis Methods (2002)Model-based design of experiments for parameter precision: State of the art (2007)Spatial pattern and ecological analysis (1989)Geostatistical Tools for Modeling and Interpreting Ecological Spatial Dependence (1992)Model-Based Geostatistics (1998)Latin hypercube sampling and the propagation of uncertainty in analyses of complex systems (2003)
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References

  • 2007Global Sensitivity Analysis. The Primer6,425 cited
  • 1981Spatial statistics2,866 cited
  • 1999A Quantitative Model-Independent Method for Global Sensitivity Analysis of Model Output2,274 cited
  • 2002Making best use of model evaluations to compute sensitivity indices2,225 cited
  • 1996Importance measures in global sensitivity analysis of nonlinear models2,014 cited
  • 1990The origins of kriging1,763 cited
  • 2015A Review on Global Sensitivity Analysis Methods1,113 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
  • 2010How to avoid a perfunctory sensitivity analysis1,000 cited
  • 2009Choosing the Sample Size of a Computer Experiment: A Practical Guide766 cited
  • 2006Bayesian analysis of computer code outputs: A tutorial756 cited
  • 1992Screening, Predicting, and Computer Experiments633 cited
  • 2012DiceKriging , DiceOptim : Two R Packages for the Analysis of Computer Experiments by Kriging-Based Metamodeling and Optimization594 cited
  • 19969 Computer experiments378 cited

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  • 2008Calculations of Sobol indices for the Gaussian process metamodel331 cited
  • Cited by

    • 2022Multi-method global sensitivity analysis of mathematical models45 cited
    • 2022Variance‐Based Global Sensitivity Analysis: A Methodological Framework and Case Study for Microkinetic Modeling9 cited