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:	2.1.1
Depends:	DiceKriging (≥ 1.2), methods
Imports:	randtoolbox, pbivnorm, rgenoud, mnormt, DiceDesign, parallel
Suggests:	KrigInv, GPareto
Published:	2021-02-02
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

Documentation:

Reference manual:

DiceOptim.pdf

Downloads:

Package source:	DiceOptim_2.1.1.tar.gz
Windows binaries:	r-devel: DiceOptim_2.1.1.zip, r-release: DiceOptim_2.1.1.zip, r-oldrel: DiceOptim_2.1.1.zip
macOS binaries:	r-release (arm64): DiceOptim_2.1.1.tgz, r-oldrel (arm64): DiceOptim_2.1.1.tgz, r-release (x86_64): DiceOptim_2.1.1.tgz, r-oldrel (x86_64): DiceOptim_2.1.1.tgz
Old sources:	DiceOptim archive

Reverse dependencies:

Reverse suggests:

comparer, GPareto, GPGame, laGP

Linking:

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