CGGP: Composite Grid Gaussian Processes
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: |
1.0.4 |
| Imports: |
Rcpp (≥ 0.12.18) |
| LinkingTo: |
Rcpp, RcppArmadillo |
| Suggests: |
testthat, covr, ggplot2, reshape2, plyr, MASS, rmarkdown, knitr |
| Published: |
2024-01-23 |
| DOI: |
10.32614/CRAN.package.CGGP |
| 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 |
Documentation:
Downloads:
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