Run computer experiments using the adaptive composite grid algorithm with a Gaussian process model. The algorithm works best when running an experiment that can evaluate thousands of points from a deterministic computer simulation. This package is an implementation of a forthcoming paper by Plumlee, Erickson, Ankenman, et al. For a preprint of the paper, contact the maintainer of this package.
| Version: | 1.0.2 |
| Imports: | Rcpp (≥ 0.12.18) |
| LinkingTo: | Rcpp, RcppArmadillo |
| Suggests: | testthat, covr, ggplot2, reshape2, plyr, MASS, knitr |
| Published: | 2020-03-29 |
| Author: | Collin Erickson [aut, cre], Matthew Plumlee [aut] |
| Maintainer: | Collin Erickson <collinberickson at gmail.com> |
| BugReports: | https://github.com/CollinErickson/CGGP/issues |
| License: | GPL-3 |
| URL: | https://github.com/CollinErickson/CGGP |
| NeedsCompilation: | yes |
| Materials: | README NEWS |
| CRAN checks: | CGGP results |
| Reference manual: | CGGP.pdf |
| Vignettes: |
CGGP |
| Package source: | CGGP_1.0.2.tar.gz |
| Windows binaries: | r-devel: CGGP_1.0.2.zip, r-release: CGGP_1.0.2.zip, r-oldrel: CGGP_1.0.2.zip |
| macOS binaries: | r-release: CGGP_1.0.2.tgz, r-oldrel: CGGP_1.0.2.tgz |
| Old sources: | CGGP archive |
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