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Multivariate sensitivity analysis to measure global contribution of input factors in dynamic models
8 references·16 citing·26 second hop
Multivariate sensitivity analysis to measure global contribution of input factors in dynamic models (2010)Multivariate sensitivity analysis to meas…Variance based sensitivity analysis of model output. Design and estimator for the total sensitivity index (2009)Variance based sensitivity an…Global Sensitivity Analysis. The Primer (2007)Global Sensitivity Analysis. …Latin hypercube sampling and the propagation of uncertainty in analyses of complex systems (2003)Latin hypercube sampling and …Making best use of model evaluations to compute sensitivity indices (2002)Making best use of model eval…A Quantitative Model-Independent Method for Global Sensitivity Analysis of Model Output (1999)A Quantitative Model-Independ…Empirical Model Building and Response Surfaces (1988)Empirical Model Building and …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…Study of the sensitivity of coupled reaction systems to uncertainties in rate coefficients. I Theory (1973)Study of the sensitivity of c…A variable and mode sensitivity analysis method for structural system using a novel active learning Kriging model (2020)A variable and mode sensitivi…A global surrogate model technique based on principal component analysis and Kriging for uncertainty propagation of dynamic systems (2020)A global surrogate model tech…Variance-based sensitivity analysis for time-dependent processes (2019)Variance-based sensitivity an…Principal component analysis and sparse polynomial chaos expansions for global sensitivity analysis and model calibration: Application to urban drainage simulation (2019)Principal component analysis …Efficient dimension reduction and surrogate-based sensitivity analysis for expensive models with high-dimensional outputs (2019)Efficient dimension reduction…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…Generalized sensitivity indices based on vector projection for multivariate output (2018)Generalized sensitivity indic…Fast sensitivity analysis methods for computationally expensive models with multi-dimensional output (2018)Fast sensitivity analysis met…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…Human-oriented design of collaborative robots (2017)Human-oriented design of coll…Sensitivity analysis for multidimensional and functional outputs (2014)Sensitivity analysis for mult…Global Sensitivity Analysis for multivariate output using Polynomial Chaos Expansion (2014)Global Sensitivity Analysis f…Development of a surrogate model and sensitivity analysis for spatio-temporal numerical simulators (2014)Development of a surrogate mo…Sensitivity indices for multivariate outputs (2013)Sensitivity indices for multi…Revue sur l'analyse de sensibilité globale de modèles numériques (2011)Revue sur l'analyse de sensib…Statistics for Experimenters (1979)Response Surfaces: Designs and Analyses (1997)Explaining Fixed Effects: Random Effects Modeling of Time-Series Cross-Sectional and Panel Data (2014)A new uncertainty importance measure (2006)Asymptotic normality and efficiency of two Sobol index estimators (2013)Sensitivity Analysis Based on Cramér--von Mises Distance (2018)Factorial Sampling Plans for Preliminary Computational Experiments (1991)Handbook on Constructing Composite Indicators (2005)Global sensitivity analysis using polynomial chaos expansions (2007)Design and Analysis of Computer Experiments (1989)Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates (2001)How to avoid a perfunctory sensitivity analysis (2010)RULA: a survey method for the investigation of work-related upper limb disorders (1993)Rapid Entire Body Assessment (REBA) (2000)Comparison of ergonomic risk assessment outputs from OWAS and REBA in forestry timber harvesting (2019)Evaluation of User Experience in Human–Robot Interaction: A Systematic Literature Review (2023)A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code (2000)Survey of sampling-based methods for uncertainty and sensitivity analysis (2006)A Review on Global Sensitivity Analysis Methods (2015)Sensitivity analysis of environmental models: A systematic review with practical workflow (2016)SALib: An open-source Python library for Sensitivity Analysis (2017)Identification and Review of Sensitivity Analysis Methods (2002)Probabilistic Sensitivity Analysis of Complex Models: A Bayesian Approach (2004)Model-based design of experiments for parameter precision: State of the art (2007)Importance measures in global sensitivity analysis of nonlinear models (1996)Adaptive sparse polynomial chaos expansion based on least angle regression (2010)
this work references cited by second hop

References

  • 2007Global Sensitivity Analysis. The Primer6,425 cited
  • 1988Empirical Model Building and Response Surfaces5,235 cited
  • 1979A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code3,766 cited
  • 2009Variance based sensitivity analysis of model output. Design and estimator for the total sensitivity index3,567 cited
  • 2003Latin hypercube sampling and the propagation of uncertainty in analyses of complex systems2,707 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
  • 1973Study of the sensitivity of coupled reaction systems to uncertainties in rate coefficients. I Theory1,041 cited

Cited by

  • 2014Sensitivity analysis for multidimensional and functional outputs131 cited
  • 2017Human-oriented design of collaborative robots125 cited
  • 2014Global Sensitivity Analysis for multivariate output using Polynomial Chaos Expansion117 cited
  • 2013Sensitivity indices for multivariate outputs99 cited
  • 2019Principal component analysis and sparse polynomial chaos expansions for global sensitivity analysis and model calibration: Application to urban drainage simulation91 cited
  • 2018

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Global sensitivity analysis for high-dimensional problems: How to objectively group factors and measure robustness and convergence while reducing computational cost
87 cited
  • 2019Variance-based sensitivity analysis for time-dependent processes67 cited
  • 2017Multivariate global sensitivity analysis for dynamic models based on wavelet analysis66 cited
  • 2020A global surrogate model technique based on principal component analysis and Kriging for uncertainty propagation of dynamic systems62 cited
  • 2018Fast sensitivity analysis methods for computationally expensive models with multi-dimensional output52 cited
  • 2019Efficient dimension reduction and surrogate-based sensitivity analysis for expensive models with high-dimensional outputs52 cited
  • 2020A variable and mode sensitivity analysis method for structural system using a novel active learning Kriging model49 cited
  • 2011Revue sur l'analyse de sensibilité globale de modèles numériques48 cited
  • 2017Multivariate sensitivity analysis based on the direction of eigen space through principal component analysis48 cited
  • 2018Generalized sensitivity indices based on vector projection for multivariate output45 cited
  • 2014Development of a surrogate model and sensitivity analysis for spatio-temporal numerical simulators45 cited