Comparison of Gaussian process modeling software

DOI10.1016/J.EJOR.2017.10.002zbMath1403.62006arXiv1710.03157OpenAlexW2761682901MaRDI QIDQ65764

Susan M. Sanchez, Bruce E. Ankenman, Collin B. Erickson, Collin B. Erickson, Susan M. Sanchez, Bruce E. Ankenman

Publication date: April 2018

Published in: European Journal of Operational Research (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1710.03157

zbMATH Keywords

simulationGaussian processescomputer experimentsmetamodelsstochastic kriging

Mathematics Subject Classification ID

Software, source code, etc. for problems pertaining to statistics (62-04) Gaussian processes (60G15) Applications of statistics (62Pxx) Design of statistical experiments (62Kxx)

Related Items (8)

Statistical Tests for Cross-Validation of Kriging Models ⋮ Modeling and Active Learning for Experiments with Quantitative-Sequence Factors ⋮ Faster Kriging: Facing High-Dimensional Simulators ⋮ An extended two-stage sequential optimization approach: properties and performance ⋮ Practical Heteroscedastic Gaussian Process Modeling for Large Simulation Experiments ⋮ 10 Kriging: methods and applications ⋮ GauPro ⋮ On surrogate learning for linear stability assessment of Navier-Stokes equations with stochastic viscosity.

Uses Software

• JMP
• R
• L-BFGS
• DACE
• LBFGS-B
• SciPy
• EGO
• DiceKriging
• DiceOptim
• tgp
• Scikit
• mlegp
• rgenoud
• laGP
• GPfit
• GPy
• Python
• MaxPro
• Virtual library

Cites Work

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• Cases for the nugget in modeling computer experiments
• On the limited memory BFGS method for large scale optimization
• Efficient global optimization of expensive black-box functions
• The design and analysis of computer experiments.
• Design and analysis of computer experiments. With comments and a rejoinder by the authors
• Analysis methods for computer experiments: how to assess and what counts?
• Bayesian Treed Gaussian Process Models With an Application to Computer Modeling
• Stochastic Kriging for Simulation Metamodeling
• Bayesian Design and Analysis of Computer Experiments: Use of Derivatives in Surface Prediction
• A Limited Memory Algorithm for Bound Constrained Optimization
• Design and analysis of simulation experiments

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