The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
DiceKriging,DiceOptim: Two R Packages for the Analysis of Computer Experiments by Kriging-Based Metamodeling and Optimization
Open accessAbstract
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 DiceOptim’s presentation. An appendix is dedicated to complementary mathematical and computational details.
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Cites
Gaussian Processes for Machine Learning
Rasmussen, C. E., & Williams, C. K. I. (2005) · doi:10.7551/mitpress/3206.001.0001 · Cited by 11,705
Efficient Global Optimization of Expensive Black-Box Functions
Jones, D. R., Schonlau, M., & Welch, W. J. (1998) · Journal of Global Optimization · doi:10.1023/a:1008306431147 · Cited by 8,070
Global Sensitivity Analysis. The Primer
Saltelli, A., Ratto, M., Andres, T., Campolongo, F., Cariboni, J., Gatelli, D., Saisana, M., & Tarantola, S. (2007) · doi:10.1002/9780470725184 · Cited by 6,430
Bayesian calibration of computer models
Kennedy, M. C., & O'Hagan, A. (2001) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/1467-9868.00294 · Cited by 4,222
Cited by
Fast Computation of the Multi-Points Expected Improvement with Applications in Batch Selection
Chevalier, C., & Ginsbourger, D. (2013) · Lecture Notes in Computer Science · doi:10.1007/978-3-642-44973-4_7 · Cited by 147
Self-citationFletcher, C. G., Kravitz, B., & Badawy, B. (2018) · Atmospheric Chemistry and Physics · doi:10.5194/acp-18-17529-2018 · Cited by 20
RKappa: Software for Analyzing Rule-Based Models
Sorokin, A., Sorokina, O., & Douglas Armstrong, J. (2019) · Methods in Molecular Biology · doi:10.1007/978-1-4939-9102-0_17 · Cited by 4
Metadata
- Authors
- Roustant, O., Ginsbourger, D., & Deville, Y.
- Venue
- Journal of Statistical Software
- Publisher
- Foundation for Open Access Statistic
- Published
- 2012
- Volume
- 51
- Issue
- 1
- ISSN
- 1548-7660 (ISSN-L)
- OpenAlex
- W1840389249
- Cited by
- 594
- References
- 4
- FWCI
- 41.38
- Type
- journal article
- Language
- en
- Open access
- diamond
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- Roustant, O., Ginsbourger, D., & Deville, Y. (2012). DiceKriging,DiceOptim: Two R Packages for the Analysis of Computer Experiments by Kriging-Based Metamodeling and Optimization. Journal of Statistical Software. https://doi.org/10.18637/jss.v051.i01
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