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What do we mean by sensitivity analysis? The need for comprehensive characterization of “global” sensitivity in E arth and E nvironmental systems models
16 references·16 citing·19 second hopsampled
What do we mean by sensitivity analysis? The need for comprehensive characterization of “global” sensitivity in E arth and E nvironmental systems models (2015)What do we mean by sensitivity analysis? …How to avoid a perfunctory sensitivity analysis (2010)How to avoid a perfunctory se…Global Sensitivity Analysis. The Primer (2007)Global Sensitivity Analysis. …Design and Analysis of Experiments (2007)Design and Analysis of Experi…An effective screening design for sensitivity analysis of large models (2007)An effective screening design…Sensitivity Analysis in Practice: A Guide to Assessing Scientific Models (2005)Sensitivity Analysis in Pract…Sensitivity Analysis in Practice: A Guide to Assessing Scientific Models (2004)Sensitivity Analysis in Pract…Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates (2001)Global sensitivity indices fo…A Quantitative Model-Independent Method for Global Sensitivity Analysis of Model Output (1999)A Quantitative Model-Independ…Response Surface Methodology: Process and Product Optimization Using Designed Experiments (1996)Response Surface Methodology:…Response Surface Methodology: Process and Product Optimization Using Designed Experiments (1996)Response Surface Methodology:…Importance measures in global sensitivity analysis of nonlinear models (1996)Importance measures in global…A review of techniques for parameter sensitivity analysis of environmental models (1994)A review of techniques for pa…Factorial Sampling Plans for Preliminary Computational Experiments (1991)Factorial Sampling Plans for …Design and Analysis of Computer Experiments (1989)Design and Analysis of Comput…Study of the sensitivity of coupled reaction systems to uncertainties in rate coefficients. I Theory (1973)Study of the sensitivity of c…Design of Experiments (1936)Design of ExperimentsBayesian Optimization in Bioprocess Engineering—Where Do We Stand Today? (2025)Bayesian Optimization in Biop…Toward SALib 2.0: Advancing the accessibility and interpretability of global sensitivity analyses (2022)Toward SALib 2.0: Advancing t…Multi-method global sensitivity analysis of mathematical models (2022)Multi-method global sensitivi…Socio-technical scales in socio-environmental modeling: Managing a system-of-systems modeling approach (2020)Socio-technical scales in soc…Certain trends in uncertainty and sensitivity analysis: An overview of software tools and techniques (2019)Certain trends in uncertainty…VARS-TOOL: A toolbox for comprehensive, efficient, and robust sensitivity and uncertainty analysis (2018)VARS-TOOL: A toolbox for comp…Global sensitivity analysis for high-dimensional problems: How to objectively group factors and measure robustness and convergence while reducing computational cost (2018)Global sensitivity analysis f…Distribution-based sensitivity analysis from a generic input-output sample (2018)Distribution-based sensitivit…Review of literature on decision support systems for natural hazard risk reduction: Current status and future research directions (2017)Review of literature on decis…Progressive Latin Hypercube Sampling: An efficient approach for robust sampling-based analysis of environmental models (2017)Progressive Latin Hypercube S…Multivariate sensitivity analysis based on the direction of eigen space through principal component analysis (2017)Multivariate sensitivity anal…Multivariate global sensitivity analysis for dynamic models based on wavelet analysis (2017)Multivariate global sensitivi…Moment-based metrics for global sensitivity analysis of hydrological systems (2017)Moment-based metrics for glob…Insights into sensitivity analysis of Earth and environmental systems models: On the impact of parameter perturbation scale (2017)Insights into sensitivity ana…Global Sensitivity Analysis for Uncertain Parameters, Models, and Scenarios (2016)Global Sensitivity Analysis f…A new framework for comprehensive, robust, and efficient global sensitivity analysis: 1. Theory (2015)A new framework for comprehen…Statistics for Experimenters (1979)A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code (2000)Handbook on Constructing Composite Indicators (2005)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)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)Observational Study of Behavior: Sampling Methods (1974)Effect size, confidence interval and statistical significance: a practical guide for biologists (2007)Latin hypercube sampling and the propagation of uncertainty in analyses of complex systems (2003)Taking the Human Out of the Loop: A Review of Bayesian Optimization (2015)Design and Analysis of Experiments (1998)Modeling and optimization I: Usability of response surface methodology (2006)Response surface methodology (2010)A new uncertainty importance measure (2006)Research Issues and Ideas in Statistical Process Control (1999)Global sensitivity analysis using polynomial chaos expansions (2007)
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References

  • 1996Response Surface Methodology: Process and Product Optimization Using Designed Experiments9,540 cited
  • 1989Design and Analysis of Computer Experiments6,958 cited
  • 2007Global Sensitivity Analysis. The Primer6,425 cited
  • 2001Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates6,377 cited
  • 1936Design of Experiments4,949 cited
  • 1991Factorial Sampling Plans for Preliminary Computational Experiments4,936 cited
  • 1996Response Surface Methodology: Process and Product Optimization Using Designed Experiments3,255 cited
  • 1999A Quantitative Model-Independent Method for Global Sensitivity Analysis of Model Output2,274 cited
  • 2007An effective screening design for sensitivity analysis of large models2,024 cited
  • 1996Importance measures in global sensitivity analysis of nonlinear models2,014 cited
  • 1994A review of techniques for parameter sensitivity analysis of environmental models1,964 cited
  • 2005Sensitivity Analysis in Practice: A Guide to Assessing Scientific Models1,843 cited
  • 2004Sensitivity Analysis in Practice: A Guide to Assessing Scientific Models1,797 cited
  • 1973Study of the sensitivity of coupled reaction systems to uncertainties in rate coefficients. I Theory1,041 cited

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2007
Design and Analysis of Experiments
1,039 cited
  • 2010How to avoid a perfunctory sensitivity analysis1,000 cited
  • Cited by

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    • 2018VARS-TOOL: A toolbox for comprehensive, efficient, and robust sensitivity and uncertainty analysis103 cited
    • 2020Socio-technical scales in socio-environmental modeling: Managing a system-of-systems modeling approach88 cited
    • 2018Global sensitivity analysis for high-dimensional problems: How to objectively group factors and measure robustness and convergence while reducing computational cost87 cited
    • 2017Moment-based metrics for global sensitivity analysis of hydrological systems82 cited
    • 2017Multivariate global sensitivity analysis for dynamic models based on wavelet analysis66 cited
    • 2017Insights into sensitivity analysis of Earth and environmental systems models: On the impact of parameter perturbation scale55 cited
    • 2025Bayesian Optimization in Bioprocess Engineering—Where Do We Stand Today?51 cited
    • 2017Multivariate sensitivity analysis based on the direction of eigen space through principal component analysis48 cited
    • 2022Multi-method global sensitivity analysis of mathematical models45 cited
    • 2016Global Sensitivity Analysis for Uncertain Parameters, Models, and Scenarios33 cited