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Editors-in-chief: Bettina GrĂ¼n, Edzer Pebesma & Achim Zeileis    ISSN 1548-7660; CODEN JSSOBK
DiceKriging, DiceOptim: Two R Packages for the Analysis of Computer Experiments by Kriging-Based Metamodeling and Optimization | Roustant | Journal of Statistical Software
Authors: Olivier Roustant, David Ginsbourger, Yves Deville
Title: DiceKriging, DiceOptim: Two R Packages for the Analysis of Computer Experiments by Kriging-Based Metamodeling and Optimization
Abstract: We present two recently released R packages, DiceKriging and DiceOptim, for the approximation and the optimization of expensive-to-evaluate deterministic functions. Following a self-contained mini tutorial on Kriging-based approximation and optimization, the functionalities of both packages are detailed and demonstrated in two distinct sections. In particular, the versatility of DiceKriging with respect to trend and noise specifications, covariance parameter estimation, as well as conditional and unconditional simulations are illustrated on the basis of several reproducible numerical experiments. We then put to the fore the implementation of sequential and parallel optimization strategies relying on the expected improvement criterion on the occasion of DiceOptims presentation. An appendix is dedicated to complementary mathematical and computational details.

Page views:: 6164. Submitted: 2010-07-09. Published: 2012-10-22.
Paper: DiceKriging, DiceOptim: Two R Packages for the Analysis of Computer Experiments by Kriging-Based Metamodeling and Optimization     Download PDF (Downloads: 6494)
Supplements:
DiceKriging_1.4.1.tar.gz: R source package Download (Downloads: 513; 55KB)
DiceOptim_1.3.3.tar.gz: R source package Download (Downloads: 472; 40KB)
v51i01.R: R example code from the paper Download (Downloads: 541; 25KB)

DOI: 10.18637/jss.v051.i01

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Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license.