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Estimating Sobol sensitivity indices using correlations
16 references·16 citing·24 second hopsampled
Estimating Sobol sensitivity indices using correlations (2012)Estimating Sobol sensitivity indices usin…How to avoid a perfunctory sensitivity analysis (2010)How to avoid a perfunctory se…Convergence and uncertainty analyses in Monte-Carlo based sensitivity analysis (2010)Convergence and uncertainty a…Variance based sensitivity analysis of model output. Design and estimator for the total sensitivity index (2009)Variance based sensitivity an…Estimating the approximation error when fixing unessential factors in global sensitivity analysis (2006)Estimating the approximation …Random balance designs for the estimation of first order global sensitivity indices (2005)Random balance designs for th…Making best use of model evaluations to compute sensitivity indices (2002)Making best use of model eval…Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates (2001)Global sensitivity indices fo…General foundations of high‐dimensional model representations (1999)General foundations of high‐d…Analysis of variance designs for model output (1999)Analysis of variance designs …A Quantitative Model-Independent Method for Global Sensitivity Analysis of Model Output (1999)A Quantitative Model-Independ…Sensitivity measures,anova-like Techniques and the use of bootstrap (1997)Sensitivity measures,anova-li…Sensitivity analysis of model output (1997)Sensitivity analysis of model…Importance measures in global sensitivity analysis of nonlinear models (1996)Importance measures in global…About the use of rank transformation in sensitivity analysis of model output (1995)About the use of rank transfo…Nonlinear sensitivity analysis of multiparameter model systems (1978)Nonlinear sensitivity analysi…Study of the sensitivity of coupled reaction systems to uncertainties in rate coefficients. I Theory (1973)Study of the sensitivity of c…sensobol : An R Package to Compute Variance-Based Sensitivity Indices (2022)sensobol : An R Package to Co…Benchmarking Active Subspace methods of global sensitivity analysis against variance-based Sobol' and Morris methods with established test functions (2022)Benchmarking Active Subspace …Sobol’ main effect index: an Innovative Algorithm (IA) using Dynamic Adaptive Variances (2021)Sobol’ main effect index: an …Local and global spatio-temporal sensitivity analysis of thermal consolidation around a point heat source (2021)Local and global spatio-tempo…Adaptive use of replicated Latin Hypercube Designs for computing Sobol’ sensitivity indices (2021)Adaptive use of replicated La…A COMPREHENSIVE COMPARISON OF TOTAL-ORDER ESTIMATORS FOR GLOBAL SENSITIVITY ANALYSIS (2021)A COMPREHENSIVE COMPARISON OF…Variance-based sensitivity analysis: The quest for better estimators and designs between explorativity and economy (2020)Variance-based sensitivity an…Efficient analysis of parametric sensitivity and uncertainty of fuel cell models with application to SOFC (2020)Efficient analysis of paramet…An effective strategy for combining variance- and distribution-based global sensitivity analysis (2020)An effective strategy for com…Shapley effect application for variance-based sensitivity analysis of the few-group cross-sections (2019)Shapley effect application fo…Demonstration of the relationship between sensitivity and identifiability for inverse uncertainty quantification (2019)Demonstration of the relation…Uncertainpy: A Python Toolbox for Uncertainty Quantification and Sensitivity Analysis in Computational Neuroscience (2018)Uncertainpy: A Python Toolbox…Probability models for data-Driven global sensitivity analysis (2018)Probability models for data-D…Different numerical estimators for main effect global sensitivity indices (2017)Different numerical estimator…Comparison of global sensitivity analysis methods – Application to fuel behavior modeling (2015)Comparison of global sensitiv…Uncertainty quantification of dry woven fabrics: A sensitivity analysis on material properties (2014)Uncertainty quantification of…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)A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code (2000)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)Statistics for Experimenters (1979)Design and Analysis of Computer Experiments (1989)Handbook on Constructing Composite Indicators (2005)An effective screening design for sensitivity analysis of large models (2007)Sensitivity analysis of environmental models: A systematic review with practical workflow (2016)Factorial Sampling Plans for Preliminary Computational Experiments (1991)Global sensitivity analysis using polynomial chaos expansions (2007)Global Sensitivity Analysis. The Primer (2007)Why so many published sensitivity analyses are false: A systematic review of sensitivity analysis practices (2019)Uncertainty and sensitivity analysis techniques for use in performance assessment for radioactive waste disposal (1993)Model-based design of experiments for parameter precision: State of the art (2007)SALib: An open-source Python library for Sensitivity Analysis (2017)A new uncertainty importance measure (2006)Identification and Review of Sensitivity Analysis Methods (2002)Probabilistic Sensitivity Analysis of Complex Models: A Bayesian Approach (2004)Latin hypercube sampling and the propagation of uncertainty in analyses of complex systems (2003)Efficient input—output model representations (1999)Sensitivity Analysis for Chemical Models (2005)
this work references cited by second hop· second hop is a sample of the most-cited connections

References

  • 2001Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates6,377 cited
  • 2009Variance based sensitivity analysis of model output. Design and estimator for the total sensitivity index3,567 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
  • 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
  • 1999General foundations of high‐dimensional model representations905 cited
  • 1978Nonlinear sensitivity analysis of multiparameter model systems696 cited
  • 1999Analysis of variance designs for model output648 cited
  • 1997Sensitivity measures,anova-like Techniques and the use of bootstrap546 cited
  • 2006Estimating the approximation error when fixing unessential factors in global sensitivity analysis395 cited
  • 1995About the use of rank transformation in sensitivity analysis of model output340 cited
  • 2010Convergence and uncertainty analyses in Monte-Carlo based sensitivity analysis326 cited

Only edges whose both ends are imported exist here. Widen the year window, or show the whole map. Back to the work

  • 2005Random balance designs for the estimation of first order global sensitivity indices319 cited
  • 1997Sensitivity analysis of model output313 cited
  • Cited by

    • 2018Uncertainpy: A Python Toolbox for Uncertainty Quantification and Sensitivity Analysis in Computational Neuroscience111 cited
    • 2022sensobol : An R Package to Compute Variance-Based Sensitivity Indices110 cited
    • 2017Different numerical estimators for main effect global sensitivity indices64 cited
    • 2021A COMPREHENSIVE COMPARISON OF TOTAL-ORDER ESTIMATORS FOR GLOBAL SENSITIVITY ANALYSIS58 cited
    • 2020Variance-based sensitivity analysis: The quest for better estimators and designs between explorativity and economy56 cited
    • 2015Comparison of global sensitivity analysis methods – Application to fuel behavior modeling53 cited
    • 2014Uncertainty quantification of dry woven fabrics: A sensitivity analysis on material properties47 cited
    • 2018Probability models for data-Driven global sensitivity analysis45 cited
    • 2019Demonstration of the relationship between sensitivity and identifiability for inverse uncertainty quantification44 cited
    • 2020Efficient analysis of parametric sensitivity and uncertainty of fuel cell models with application to SOFC36 cited
    • 2021Local and global spatio-temporal sensitivity analysis of thermal consolidation around a point heat source29 cited
    • 2020An effective strategy for combining variance- and distribution-based global sensitivity analysis26 cited
    • 2021Sobol’ main effect index: an Innovative Algorithm (IA) using Dynamic Adaptive Variances26 cited
    • 2019Shapley effect application for variance-based sensitivity analysis of the few-group cross-sections23 cited
    • 2021Adaptive use of replicated Latin Hypercube Designs for computing Sobol’ sensitivity indices20 cited
    • 2022Benchmarking Active Subspace methods of global sensitivity analysis against variance-based Sobol' and Morris methods with established test functions18 cited