2015
DOI: 10.18637/jss.v065.i11
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DiceDesignandDiceEval: TwoRPackages for Design and Analysis of Computer Experiments

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 exam… Show more

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Cited by 100 publications
(73 citation statements)
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“…The methodology employed is described in the DiceEval Rpackage (Dupuy et al, 2015) reference-manual. We considered K = 10 and compute the MSE between meta-model approximation and the k-fold observations for each fold (k times).…”
Section: The Validation Of the Chosen Type Of Meta-model: Training Setmentioning
confidence: 99%
“…The methodology employed is described in the DiceEval Rpackage (Dupuy et al, 2015) reference-manual. We considered K = 10 and compute the MSE between meta-model approximation and the k-fold observations for each fold (k times).…”
Section: The Validation Of the Chosen Type Of Meta-model: Training Setmentioning
confidence: 99%
“…However, for a high-dimensional space, the distribution of points provided by LHS may deviate considerably from a uniform distribution (leading to high-discrepancy). Thus, an additional step of LHS optimization is performed, using the Enhanced Stochastic Evolutionary (ESE) algorithm provided in the DiceDesign package of R [21]. The kriging model trend is specified as a first order polynomial with a second order interactions.…”
Section: A Kriging Meta-model For Nominal(without-variation) Casementioning
confidence: 99%
“…Four different variants are implemented in vdg -see ?LHS and the examples for more details. It is also possible to interface to other space-filling design implementations, such as those available in, for example, lhs (Carnell 2016) and DiceDesign (Dupuy, Helbert, and Franco 2015). An example is given in ?sampler.…”
Section: Sampling In Hypercubesmentioning
confidence: 99%