kergp: Kernel laboratory. This package, created during the DICE consortium, has been enriched with new functionalities:
categorical variables, radial kernels, optimizer choices, etc.
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lineqGPR : Gaussian Process Regression Models with Linear Inequality Constraints.
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nestedKriging : Nested kriging models for large data sets.
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mixgp: Kriging models with both discrete and continuous input variables. Will be included in kergp.
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Gaussian Processes For Computer Experiments,
F. Bachoc, E. Contal, H. Maatouk, and D. Rullière (2017), ESAIM: Proceedings and surveys, proceedings of MAS2016 conference, 60, p. 163-179.
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(*)
One of the Chair activities is to develop opensource R packages
that are later available on the CRAN archive website.
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