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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:

Reference manual:CGGP.html ,CGGP.pdf
Vignettes:CGGP (source,R code)

Downloads:

Package source: CGGP_1.0.4.tar.gz
Windows binaries: r-devel:CGGP_1.0.4.zip, r-release:CGGP_1.0.4.zip, r-oldrel:CGGP_1.0.4.zip
macOS binaries: r-release (arm64):CGGP_1.0.4.tgz, r-oldrel (arm64):CGGP_1.0.4.tgz, r-release (x86_64):CGGP_1.0.4.tgz, r-oldrel (x86_64):CGGP_1.0.4.tgz
Old sources: CGGP archive

Linking:

Please use the canonical formhttps://CRAN.R-project.org/package=CGGPto link to this page.


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