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: |
1.0.3 |
Imports: |
Rcpp (≥ 0.12.18) |
LinkingTo: |
Rcpp, RcppArmadillo |
Suggests: |
testthat, covr, ggplot2, reshape2, plyr, MASS, rmarkdown, knitr |
Published: |
2021-05-08 |
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:
Linking:
Please use the canonical form
https://CRAN.R-project.org/package=CGGP
to link to this page.