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Insights into sensitivity analysis of Earth and environmental systems models: On the impact of parameter perturbation scale
13 references·2 citing·29 second hop
Insights into sensitivity analysis of Earth and environmental systems models: On the impact of parameter perturbation scale (2017)Insights into sensitivity analysis of Ear…Progressive Latin Hypercube Sampling: An efficient approach for robust sampling-based analysis of environmental models (2017)Progressive Latin Hypercube S…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 sensitivit…A new framework for comprehensive, robust, and efficient global sensitivity analysis: 1. Theory (2015)A new framework for comprehen…Optimal Sliced Latin Hypercube Designs (2014)Optimal Sliced Latin Hypercub…Sliced Latin Hypercube Designs (2012)Sliced Latin Hypercube DesignsA fully multiple‐criteria implementation of the Sobol′ method for parameter sensitivity analysis (2012)A fully multiple‐criteria imp…How to avoid a perfunctory sensitivity analysis (2010)How to avoid a perfunctory se…Derivative based global sensitivity measures and their link with global sensitivity indices (2009)Derivative based global sensi…Global Sensitivity Analysis. The Primer (2007)Global Sensitivity Analysis. …An effective screening design for sensitivity analysis of large models (2007)An effective screening design…Importance measures in global sensitivity analysis of nonlinear models (1996)Importance measures in global…Statistics for Spatial Data, Revised Edition. (1994)Statistics for Spatial Data, …Factorial Sampling Plans for Preliminary Computational Experiments (1991)Factorial Sampling Plans for …Sensitivity Analysis: An Operational Picture (2023)Sensitivity Analysis: An Oper…An effective strategy for combining variance- and distribution-based global sensitivity analysis (2020)An effective strategy for com…Statistics for Experimenters (1979)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)Handbook on Constructing Composite Indicators (2005)Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates (2001)From screening to quantitative sensitivity analysis. A unified approach (2011)Sensitivity analysis for volcanic source modeling quality assessment and model selection (2012)Response Surface Methodology: Process and Product Optimization Using Designed Experiments (1996)Toward SALib 2.0: Advancing the accessibility and interpretability of global sensitivity analyses (2022)A Quantitative Model-Independent Method for Global Sensitivity Analysis of Model Output (1999)Statistics for Spatial Data (1993)Certain trends in uncertainty and sensitivity analysis: An overview of software tools and techniques (2019)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)sensobol : An R Package to Compute Variance-Based Sensitivity Indices (2022)Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code (1979)Multi-criteria group decision making under uncertainty: Application in reservoir flood control operation (2017)Global sensitivity analysis for high-dimensional problems: How to objectively group factors and measure robustness and convergence while reducing computational cost (2018)VARS-TOOL: A toolbox for comprehensive, efficient, and robust sensitivity and uncertainty analysis (2018)THE DESIGN OF OPTIMUM MULTIFACTORIAL EXPERIMENTS (1946)On the Experimental Attainment of Optimum Conditions (1951)Latin hypercube sampling and the propagation of uncertainty in analyses of complex systems (2003)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)Why so many published sensitivity analyses are false: A systematic review of sensitivity analysis practices (2019)The Future of Sensitivity Analysis: An essential discipline for systems modeling and policy support (2020)SPATIAL AUTOCORRELATION AND AUTOREGRESSIVE MODELS IN ECOLOGY (2002)Spatial analysis a guide for ecologists (2005)Fixed Rank Kriging for Very Large Spatial Data Sets (2008)
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References

  • 2007Global Sensitivity Analysis. The Primer6,425 cited
  • 1991Factorial Sampling Plans for Preliminary Computational Experiments4,936 cited
  • 2007An effective screening design for sensitivity analysis of large models2,024 cited
  • 1996Importance measures in global sensitivity analysis of nonlinear models2,014 cited
  • 1994Statistics for Spatial Data, Revised Edition.1,875 cited
  • 2010How to avoid a perfunctory sensitivity analysis1,000 cited
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  • 2015What do we mean by sensitivity analysis? The need for comprehensive characterization of “global” sensitivity in E arth and E nvironmental systems models373 cited
  • 2017Progressive Latin Hypercube Sampling: An efficient approach for robust sampling-based analysis of environmental models258 cited
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  • 2012Sliced Latin Hypercube Designs193 cited
  • 2014Optimal Sliced Latin Hypercube Designs157 cited
  • 2012A fully multiple‐criteria implementation of the Sobol′ method for parameter sensitivity analysis139 cited

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  • 2020An effective strategy for combining variance- and distribution-based global sensitivity analysis

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26 cited
  • 2023Sensitivity Analysis: An Operational Picture14 cited