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DiceDesign and DiceEval: Two R Packages for Design and Analysis of Computer Experiments

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  • Dupuy, Delphine
  • Helbert, Céline
  • Franco, Jessica

Abstract

This paper introduces two R packages available on the Comprehensive R Archive network. The main application concerns the study of computer code output. Package DiceDesign is dedicated to numerical design of experiments, from the construction to the study of the design properties. Package DiceEval deals with the fit, the validation and the comparison of metamodels. After a brief presentation of the context, we focus on the architecture of these two packages. A two-dimensional test function will be a running example to illustrate the main functionalities of these packages and an industrial case study in five dimensions will also be detailed.

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  • Dupuy, Delphine & Helbert, Céline & Franco, Jessica, 2015. "DiceDesign and DiceEval: Two R Packages for Design and Analysis of Computer Experiments," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 65(i11).
    • Handle: RePEc:jss:jstsof:v:065:i11
    DOI: http://hdl.handle.net/10.18637/jss.v065.i11
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    References listed on IDEAS

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    1. Roustant, Olivier & Ginsbourger, David & Deville, Yves, 2012. "DiceKriging, DiceOptim: Two R Packages for the Analysis of Computer Experiments by Kriging-Based Metamodeling and Optimization," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 51(i01).
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    3. Sridharan, Vamsi Krishna & Jackson, Doug & Hein, Andrew M. & Perry, Russell W. & Pope, Adam C. & Hendrix, Noble & Danner, Eric M. & Lindley, Steven T., 2023. "Simulating the migration dynamics of juvenile salmonids through rivers and estuaries using a hydrodynamically driven enhanced particle tracking model," Ecological Modelling, Elsevier, vol. 482(C).
    4. Perrin, T.V.E. & Roustant, O. & Rohmer, J. & Alata, O. & Naulin, J.P. & Idier, D. & Pedreros, R. & Moncoulon, D. & Tinard, P., 2021. "Functional principal component analysis for global sensitivity analysis of model with spatial output," Reliability Engineering and System Safety, Elsevier, vol. 211(C).
    5. Christophette Blanchet-Scalliet & Céline Helbert & Mélina Ribaud & Céline Vial, 2019. "Four algorithms to construct a sparse kriging kernel for dimensionality reduction," Computational Statistics, Springer, vol. 34(4), pages 1889-1909, December.
    6. Łukasz Klimkowski, 2024. "An Artificial Neural Network Model for a Comprehensive Assessment of the Production Performance of Multiple Fractured Unconventional Tight Gas Wells," Energies, MDPI, vol. 17(13), pages 1-26, June.
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    8. Schoonees, Pieter & le Roux, Niël & Coetzer, Roelof, 2016. "Flexible Graphical Assessment of Experimental Designs in R: The vdg Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 74(i03).
    9. Neves Costa, João & Ambrósio, Jorge & Andrade, António R. & Frey, Daniel, 2023. "Safety assessment using computer experiments and surrogate modeling: Railway vehicle safety and track quality indices," Reliability Engineering and System Safety, Elsevier, vol. 229(C).
    10. Johannes Ziesmer & Ding Jin & Sneha D Thube & Christian Henning, 2023. "A Dynamic Baseline Calibration Procedure for CGE models," Computational Economics, Springer;Society for Computational Economics, vol. 61(4), pages 1331-1368, April.

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