DiceOptim: Kriging-Based Optimization for Computer Experiments

Efficient Global Optimization (EGO) algorithm as described in "Roustant et al. (2012)" <doi:10.18637/jss.v051.i01> and adaptations for problems with noise ("Picheny and Ginsbourger, 2012") <doi:10.1016/j.csda.2013.03.018>, parallel infill, and problems with constraints.

Version: 2.0.1
Depends: DiceKriging (≥ 1.2), methods
Imports: randtoolbox, pbivnorm, rgenoud, mnormt, DiceDesign
Suggests: KrigInv, GPareto, lhs
Published: 2020-06-29
Author: Victor Picheny [aut, cre], David Ginsbourger Green [aut], Olivier Roustant [aut], Mickael Binois [ctb], Sebastien Marmin [ctb], Tobias Wagner [ctb]
Maintainer: Victor Picheny <victor.picheny at toulouse.inra.fr>
License: GPL-2 | GPL-3
URL: http://dice.emse.fr/
NeedsCompilation: yes
CRAN checks: DiceOptim results


Reference manual: DiceOptim.pdf
Package source: DiceOptim_2.0.1.tar.gz
Windows binaries: r-devel: DiceOptim_2.0.1.zip, r-release: DiceOptim_2.0.1.zip, r-oldrel: DiceOptim_2.0.1.zip
macOS binaries: r-release: DiceOptim_2.0.1.tgz, r-oldrel: DiceOptim_2.0.1.tgz
Old sources: DiceOptim archive

Reverse dependencies:

Reverse suggests: GPGame, laGP, mlrMBO


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