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Modification of the Maximin and ϕ p (Phi) Criteria to Achieve Statistically Uniform Distribution of Sampling Points
16 references·0 citing·29 second hop
Modification of the Maximin and ϕ p (Phi) Criteria to Achieve Statistically Uniform Distribution of Sampling Points (2019)Modification of the Maximin and ϕ p (Phi)…The generalization of Latin hypercube sampling (2015)The generalization of Latin h…Maximum projection designs for computer experiments (2015)Maximum projection designs fo…Handbook of Design and Analysis of Experiments (2015)Handbook of Design and Analys…Monte-Carlo based uncertainty analysis: Sampling efficiency and sampling convergence (2012)Monte-Carlo based uncertainty…An algorithm for fast optimal Latin hypercube design of experiments (2009)An algorithm for fast optimal…ORTHOGONAL-MAXIMIN LATIN HYPERCUBE DESIGNS (2008)ORTHOGONAL-MAXIMIN LATIN HYPE…An efficient algorithm for constructing optimal design of computer experiments (2004)An efficient algorithm for co…The Design and Analysis of Computer Experiments (2003)The Design and Analysis of Co…Uniform Design: Theory and Application (2000)Uniform Design: Theory and Ap…Algorithmic construction of optimal symmetric Latin hypercube designs (2000)Algorithmic construction of o…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…Exploratory designs for computational experiments (1995)Exploratory designs for compu…Orthogonal Array-Based Latin Hypercubes (1993)Orthogonal Array-Based Latin …Minimax and maximin distance designs (1990)Minimax and maximin distance …Large Sample Properties of Simulations Using Latin Hypercube Sampling (1987)Large Sample Properties of Si…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…A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code (1979)Global Sensitivity Analysis. The Primer (2007)Modern Monte Carlo methods for efficient uncertainty quantification and propagation: A survey (2020)Sparse Polynomial Chaos Expansions: Literature Survey and Benchmark (2021)Monte Carlo and variance reduction methods for structural reliability analysis: A comprehensive review (2023)THE DESIGN OF OPTIMUM MULTIFACTORIAL EXPERIMENTS (1946)Orthogonal Column Latin Hypercubes and Their Application in Computer Experiments (1998)Design and Analysis of Computer Experiments (1989)Sampling Strategies for Computer Experiments (2001)Response Surface Methodology: A Retrospective and Literature Survey (2004)Random Balance Experimentation (1959)The Application of Random Balance Designs (1959)The art of simulation (1964)Factorial Sampling Plans for Preliminary Computational Experiments (1991)Latin hypercube sampling and the propagation of uncertainty in analyses of complex systems (2003)Optimum Designs in Regression Problems (1959)Designs for Computer Experiments (1989)Small sample sensitivity analysis techniques for computer models.with an application to risk assessment (1980)A distribution-free approach to inducing rank correlation among input variables (1982)A review of techniques for parameter sensitivity analysis of environmental models (1994)High-Order Collocation Methods for Differential Equations with Random Inputs (2005)Space-Filling Designs for Computer Experiments (2003)Kriging Metamodeling in Simulation: A Review (2007)An Explicit Link between Gaussian Fields and Gaussian Markov Random Fields: The Stochastic Partial Differential Equation Approach (2011)Taking the Human Out of the Loop: A Review of Bayesian Optimization (2015)Space-Filling Designs for Computer Experiments (2018)Design of computer experiments: space filling and beyond (2011)Design of computer experiments: A review (2017)Choosing the Sample Size of a Computer Experiment: A Practical Guide (2009)
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References

  • 2000A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code8,270 cited
  • 1979A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code7,071 cited
  • 1987Large Sample Properties of Simulations Using Latin Hypercube Sampling2,483 cited
  • 2003The Design and Analysis of Computer Experiments2,219 cited
  • 1990Minimax and maximin distance designs1,452 cited
  • 1995Exploratory designs for computational experiments1,202 cited
  • 2000Uniform Design: Theory and Application954 cited
  • 1993Orthogonal Array-Based Latin Hypercubes859 cited
  • 2004An efficient algorithm for constructing optimal design of computer experiments671 cited
  • 2015The generalization of Latin hypercube sampling656 cited
  • 2000Algorithmic construction of optimal symmetric Latin hypercube designs436 cited
  • 2012Monte-Carlo based uncertainty analysis: Sampling efficiency and sampling convergence388 cited
  • 2015Maximum projection designs for computer experiments339 cited
  • 2009An algorithm for fast optimal Latin hypercube design of experiments317 cited
  • 2015Handbook of Design and Analysis of Experiments

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309 cited
  • 2008ORTHOGONAL-MAXIMIN LATIN HYPERCUBE DESIGNS266 cited
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