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Extending the use of ecological models without sacrificing details: a generic and parsimonious meta‐modelling approach
7 references·0 citing·26 second hop
Extending the use of ecological models without sacrificing details: a generic and parsimonious meta‐modelling approach (2014)Extending the use of ecological models wi…Simulation optimization using metamodels (2009)Simulation optimization using…Hierarchical adaptive experimental design for Gaussian process emulators (2008)Hierarchical adaptive experim…Metamodeling: a state of the art review (2005)Metamodeling: a state of the …Latin hypercube sampling and the propagation of uncertainty in analyses of complex systems (2003)Latin hypercube sampling and …A methodology for fitting and validating metamodels in simulation1Two anonymous referees' comments on the first draft lead to an improved organization of our paper.1 (2000)A methodology for fitting and…Metamodeling: a state of the art review (1994)Metamodeling: a state of the …A Comment on Blanning's “Metamodel for Sensitivity Analysis: The Regression Metamodel in Simulation” (1975)A Comment on Blanning's “Meta…Design and Analysis of Computer Experiments (1989)Comparing Predictive Accuracy (1994)Comparing Predictive Accuracy (1995)Model calibration as a testing strategy for system dynamics models (2003)An overview of the design and analysis of simulation experiments for sensitivity analysis (2004)Application-driven sequential designs for simulation experiments: Kriging metamodelling (2004)Empirical Model Building and Response Surfaces (1988)A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code (2000)An Adaptive Exploration-Exploitation Algorithm for Constructing Metamodels in Random Simulation Using a Novel Sequential Experimental Design (2013)A Critical Appraisal of Design of Experiments for Uncertainty Quantification (2017)A New Kriging-Based Learning Function for Reliability Analysis and Its Application to Fatigue Crack Reliability (2019)Statistics for Experimenters (1979)A taxonomy of model abstraction techniques (1995)Game-Theoretic Validation and Analysis of Air Combat Simulation Models (2010)Simulation optimization based on Taylor Kriging and evolutionary algorithm (2011)On the Experimental Attainment of Optimum Conditions (1951)Statistics for Spatial Data (1993)Tutorial: Simulation metamodeling (2015)Bayesian Optimization via Simulation with Pairwise Sampling and Correlated Prior Beliefs (2016)The Metamodel in Simulation Analysis: Can It Be Trusted? (1988)Metamodels in manufacturing: a review (1994)A new uncertainty importance measure (2006)Survey of sampling-based methods for uncertainty and sensitivity analysis (2006)A Review on Global Sensitivity Analysis Methods (2015)A sequential-design metamodeling strategy for simulation optimization (2003)Efficient Greek Calculation of Variable Annuity Portfolios for Dynamic Hedging: A Two-Level Metamodeling Approach (2017)
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References

  • 2003Latin hypercube sampling and the propagation of uncertainty in analyses of complex systems2,707 cited
  • 2000A methodology for fitting and validating metamodels in simulation1Two anonymous referees' comments on the first draft lead to an improved organization of our paper.1491 cited
  • 1975A Comment on Blanning's “Metamodel for Sensitivity Analysis: The Regression Metamodel in Simulation”115 cited
  • 2009Simulation optimization using metamodels93 cited
  • 1994Metamodeling: a state of the art review91 cited
  • 2008Hierarchical adaptive experimental design for Gaussian process emulators83 cited
  • 2005Metamodeling: a state of the art review60 cited

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