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The dangers of sparse sampling for the quantification of margin and uncertainty
16 references·1 citing·27 second hop
The dangers of sparse sampling for the quantification of margin and uncertainty (2011)The dangers of sparse sampling for the qu…Choosing the Sample Size of a Computer Experiment: A Practical Guide (2009)Choosing the Sample Size of a…An effective screening design for sensitivity analysis of large models (2007)An effective screening design…Statistics for Experimenters: Design, Innovation, and Discovery (2006)Statistics for Experimenters:…Statistics for experimenters: design, innovation, and discovery (2006)Statistics for experimenters:…Combining experimental data and computer simulations, with an application to flyer plate experiments (2006)Combining experimental data a…Sensitivity Analysis in Practice: A Guide to Assessing Scientific Models (2004)Sensitivity Analysis in Pract…Probabilistic Sensitivity Analysis of Complex Models: A Bayesian Approach (2004)Probabilistic Sensitivity Ana…The Design and Analysis of Computer Experiments (2003)The Design and Analysis of Co…A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code (2000)A Comparison of Three Methods…Response Surface Methodology: Process and Product Optimization Using Designed Experiments (1996)Response Surface Methodology:…Orthogonal Array-Based Latin Hypercubes (1993)Orthogonal Array-Based Latin …Factorial Sampling Plans for Preliminary Computational Experiments (1991)Factorial Sampling Plans for …Design and Analysis of Computer Experiments (1989)Design and Analysis of Comput…A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code (1979)A Comparison of Three Methods…Analysis of Variance in Complex Experimental Designs. (1976)Analysis of Variance in Compl…Analysis of Variance in Complex Experimental Designs (1976)Analysis of Variance in Compl…Uncertainty Quantification in Fault Tree Analysis: Estimating Business Interruption due to Seismic Hazard (2020)Uncertainty Quantification in…Statistics for Experimenters (1979)Design and Analysis of Experiments (1998)Modeling and optimization I: Usability of response surface methodology (2006)Response surface methodology (2010)Importance measures in global sensitivity analysis of nonlinear models (1996)A Quantitative Model-Independent Method for Global Sensitivity Analysis of Model Output (1999)A new uncertainty importance measure (2006)Bayesian analysis of computer code outputs: A tutorial (2006)How to avoid a perfunctory sensitivity analysis (2010)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)Experimental design in chromatography: A tutorial review (2012)Experimental design of supercritical fluid extraction – A review (2013)Why so many published sensitivity analyses are false: A systematic review of sensitivity analysis practices (2019)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)Taking the Human Out of the Loop: A Review of Bayesian Optimization (2015)A review of techniques for parameter sensitivity analysis of environmental models (1994)Sensitivity analysis of environmental models: A systematic review with practical workflow (2016)SALib: An open-source Python library for Sensitivity Analysis (2017)Handbook on Constructing Composite Indicators (2005)Tools for Composite Indicators Building (2005)Adaptive sparse polynomial chaos expansion based on least angle regression (2010)An Explicit Link between Gaussian Fields and Gaussian Markov Random Fields: The Stochastic Partial Differential Equation Approach (2011)A Review on Global Sensitivity Analysis Methods (2015)Sensitivity analysis: A review of recent advances (2015)
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References

  • 1996Response Surface Methodology: Process and Product Optimization Using Designed Experiments9,540 cited
  • 2000A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code8,233 cited
  • 1989Design and Analysis of Computer Experiments6,958 cited
  • 1991Factorial Sampling Plans for Preliminary Computational Experiments4,936 cited
  • 1979A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code3,766 cited
  • 2003The Design and Analysis of Computer Experiments2,204 cited
  • 2007An effective screening design for sensitivity analysis of large models2,024 cited
  • 2004Sensitivity Analysis in Practice: A Guide to Assessing Scientific Models1,797 cited
  • 2006Statistics for experimenters: design, innovation, and discovery1,644 cited
  • 2004Probabilistic Sensitivity Analysis of Complex Models: A Bayesian Approach1,085 cited
  • 1993Orthogonal Array-Based Latin Hypercubes859 cited
  • 2006Statistics for Experimenters: Design, Innovation, and Discovery787 cited
  • 2009Choosing the Sample Size of a Computer Experiment: A Practical Guide766 cited
  • 1976Analysis of Variance in Complex Experimental Designs.552 cited
  • 1976

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Analysis of Variance in Complex Experimental Designs
235 cited
  • 2006Combining experimental data and computer simulations, with an application to flyer plate experiments88 cited
  • Cited by

    • 2020Uncertainty Quantification in Fault Tree Analysis: Estimating Business Interruption due to Seismic Hazard9 cited