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A Global Sensitivity Analysis Framework for Hybrid Simulation with Stochastic Substructures
15 references·0 citing·26 second hop
A Global Sensitivity Analysis Framework for Hybrid Simulation with Stochastic Substructures (2021)A Global Sensitivity Analysis Framework f…Global sensitivity analysis for stochastic simulators based on generalized lambda surrogate models (2021)Global sensitivity analysis f…Emulation of Stochastic Simulators Using Generalized Lambda Models (2021)Emulation of Stochastic Simul…REPLICATION-BASED EMULATION OF THE RESPONSE DISTRIBUTION OF STOCHASTIC SIMULATORS USING GENERALIZED LAMBDA DISTRIBUTIONS (2020)REPLICATION-BASED EMULATION O…A global sensitivity analysis framework for hybrid simulation (2020)A global sensitivity analysis…UQLab: A Framework for Uncertainty Quantification in Matlab (2014)UQLab: A Framework for Uncert…Generalized Sobol sensitivity indices for dependent variables: numerical methods (2014)Generalized Sobol sensitivity…On the convergence of generalized polynomial chaos expansions (2011)On the convergence of general…Adaptive sparse polynomial chaos expansion based on least angle regression (2010)Adaptive sparse polynomial ch…Global sensitivity analysis of computer models with functional inputs (2008)Global sensitivity analysis o…Global Sensitivity Analysis. The Primer (2007)Global Sensitivity Analysis. …Global sensitivity analysis using polynomial chaos expansions (2007)Global sensitivity analysis u…Stochastic finite element: a non intrusive approach by regression (2006)Stochastic finite element: a …The Wiener--Askey Polynomial Chaos for Stochastic Differential Equations (2002)The Wiener--Askey Polynomial …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…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…Stochastic Finite Elements: A Spectral Approach (1991)Structural Reliability Methods (1996)Efficient computation of global sensitivity indices using sparse polynomial chaos expansions (2010)Stochastic analysis of the fracture toughness of polymeric nanoparticle composites using polynomial chaos expansions (2017)Sparse Polynomial Chaos Expansions: Literature Survey and Benchmark (2021)A Quantitative Model-Independent Method for Global Sensitivity Analysis of Model Output (1999)High-Order Collocation Methods for Differential Equations with Random Inputs (2005)Sparse tensor discretizations of high-dimensional parametric and stochastic PDEs (2011)Adaptive Smolyak Pseudospectral Approximations (2013)Design and Analysis of Computer Experiments (1989)Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates (2001)Simplex-based screening designs for estimating metamodels (2008)Revue sur l'analyse de sensibilité globale de modèles numériques (2011)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)A review of techniques for parameter sensitivity analysis of environmental models (1994)Importance measures in global sensitivity analysis of nonlinear models (1996)Latin hypercube sampling and the propagation of uncertainty in analyses of complex systems (2003)POLYNOMIAL-CHAOS-BASED KRIGING (2015)An active-learning algorithm that combines sparse polynomial chaos expansions and bootstrap for structural reliability analysis (2018)The Future of Sensitivity Analysis: An essential discipline for systems modeling and policy support (2020)Toward SALib 2.0: Advancing the accessibility and interpretability of global sensitivity analyses (2022)Hybrid simulation–optimization methods: A taxonomy and discussion (2014)Time-dependent reliability of aging structures in the presence of non-stationary loads and degradation (2014)Design of computer experiments: A review (2017)
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References

  • 2000A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code8,233 cited
  • 2007Global Sensitivity Analysis. The Primer6,425 cited
  • 2002The Wiener--Askey Polynomial Chaos for Stochastic Differential Equations4,821 cited
  • 2000A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output From a Computer Code2,856 cited
  • 2007Global sensitivity analysis using polynomial chaos expansions2,547 cited
  • 2010Adaptive sparse polynomial chaos expansion based on least angle regression1,507 cited
  • 2014UQLab: A Framework for Uncertainty Quantification in Matlab1,018 cited
  • 2006Stochastic finite element: a non intrusive approach by regression427 cited
  • 2011On the convergence of generalized polynomial chaos expansions414 cited
  • 2008Global sensitivity analysis of computer models with functional inputs86 cited
  • 2014Generalized Sobol sensitivity indices for dependent variables: numerical methods76 cited
  • 2020A global sensitivity analysis framework for hybrid simulation65 cited
  • 2021Global sensitivity analysis for stochastic simulators based on generalized lambda surrogate models50 cited
  • 2020REPLICATION-BASED EMULATION OF THE RESPONSE DISTRIBUTION OF STOCHASTIC SIMULATORS USING GENERALIZED LAMBDA DISTRIBUTIONS

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44 cited
  • 2021Emulation of Stochastic Simulators Using Generalized Lambda Models40 cited
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