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

Downloads:

Reference manual: CGGP.pdf
Vignettes: CGGP
Package source: CGGP_1.0.3.tar.gz
Windows binaries: r-devel: CGGP_1.0.3.zip, r-devel-UCRT: CGGP_1.0.3.zip, r-release: CGGP_1.0.3.zip, r-oldrel: CGGP_1.0.3.zip
macOS binaries: r-release (arm64): CGGP_1.0.3.tgz, r-release (x86_64): CGGP_1.0.3.tgz, r-oldrel: CGGP_1.0.3.tgz
Old sources: CGGP archive

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