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Sensitivity analysis based dimension reduction of multiscale models
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Sensitivity analysis based dimension reduction of multiscale models (2019)Sensitivity analysis based dimension redu…Why so many published sensitivity analyses are false: A systematic review of sensitivity analysis practices (2019)Why so many published sensiti…Quantile based global sensitivity measures (2018)Quantile based global sensiti…Uncertainty Quantification (2017)Uncertainty QuantificationSensitivity analysis: A review of recent advances (2015)Sensitivity analysis: A revie…An overview of methods to evaluate uncertainty of deterministic models in decision support (2014)An overview of methods to eva…Quantification of margins and uncertainties of complex systems in the presence of aleatoric and epistemic uncertainty (2011)Quantification of margins and…A comprehensive framework for verification, validation, and uncertainty quantification in scientific computing (2011)A comprehensive framework for…How to avoid a perfunctory sensitivity analysis (2010)How to avoid a perfunctory se…Variance based sensitivity analysis of model output. Design and estimator for the total sensitivity index (2009)Variance based sensitivity an…Derivative based global sensitivity measures and their link with global sensitivity indices (2009)Derivative based global sensi…Monte Carlo evaluation of derivative-based global sensitivity measures (2008)Monte Carlo evaluation of der…Estimating the approximation error when fixing unessential factors in global sensitivity analysis (2006)Estimating the approximation …Error and uncertainty in modeling and simulation (2002)Error and uncertainty in mode…Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates (2001)Global sensitivity indices fo…Importance measures in global sensitivity analysis of nonlinear models (1996)Importance measures in global…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)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. The Primer (2007)From screening to quantitative sensitivity analysis. A unified approach (2011)Sensitivity analysis for volcanic source modeling quality assessment and model selection (2012)What do we mean by sensitivity analysis? The need for comprehensive characterization of “global” sensitivity in E arth and E nvironmental systems models (2015)Dilemmas in a general theory of planning (1973)Modelling with stakeholders – Next generation (2015)Developing successful environmental decision support systems: Challenges and best practices (2020)Model uncertainty, political contestation, and public trust in science: Evidence from the COVID-19 pandemic (2020)A mathematical theory of evidence (1977)Stochastic Finite Elements: A Spectral Approach (1991)Verification and Validation in Computational Science and Engineering (1998)Integration of model verification, validation, and calibration for uncertainty quantification in engineering systems (2015)Adaptive kriging-based efficient reliability method for structural systems with multiple failure modes and mixed variables (2019)Modeling, analysis, and optimization under uncertainties: a review (2021)Simulation Modeling and Analysis. (1983)Empirical Model Building and Response Surfaces (1988)Verification, validation, and predictive capability in computational engineering and physics (2004)Calibration, validation, and sensitivity analysis: What's what (2006)Monte-Carlo based uncertainty analysis: Sampling efficiency and sampling convergence (2012)Why Most Published Research Findings Are False (2005)Sensitivity analysis methods in the biomedical sciences (2020)Toward SALib 2.0: Advancing the accessibility and interpretability of global sensitivity analyses (2022)Risk, Ambiguity, and the Savage Axioms (1961)The Price of Robustness (2004)Risk assessment and risk management: Review of recent advances on their foundation (2015)The Future of Sensitivity Analysis: An essential discipline for systems modeling and policy support (2020)SALib: An open-source Python library for Sensitivity Analysis (2017)A new uncertainty importance measure (2006)
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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
  • 1996Importance measures in global sensitivity analysis of nonlinear models2,014 cited
  • 2015Sensitivity analysis: A review of recent advances1,172 cited
  • 2010How to avoid a perfunctory sensitivity analysis1,000 cited
  • 2019Why so many published sensitivity analyses are false: A systematic review of sensitivity analysis practices827 cited
  • 2011A comprehensive framework for verification, validation, and uncertainty quantification in scientific computing810 cited
  • 2002Error and uncertainty in modeling and simulation629 cited
  • 2014An overview of methods to evaluate uncertainty of deterministic models in decision support539 cited
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  • 2008Monte Carlo evaluation of derivative-based global sensitivity measures294 cited
  • 2017Uncertainty Quantification184 cited
  • 2011Quantification of margins and uncertainties of complex systems in the presence of aleatoric and epistemic uncertainty

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  • 2018Quantile based global sensitivity measures30 cited
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