Interface to the 'python' package 'dgpsi' for Gaussian process, deep Gaussian process, and linked Gaussian process emulations of computer models and systems of computer models. The implementations follow Ming & Guillas (2021) <doi:10.1137/20M1323771> and Ming, Williamson, & Guillas (2023) <doi:10.1080/00401706.2022.2124311> and Ming & Williamson (2023) <arXiv:2306.01212>. To get started with the package, see <https://mingdeyu.github.io/dgpsi-R/>.
Version: | 2.2.0 |
Depends: | R (≥ 4.0) |
Imports: | reticulate (≥ 1.26), benchmarkme (≥ 1.0.8), utils, ggplot2, ggforce, reshape2, patchwork, lhs, methods, stats, bitops |
Suggests: | knitr, rmarkdown, MASS, R.utils, spelling |
Published: | 2023-06-05 |
Author: | Deyu Ming [aut, cre, cph], Daniel Williamson [aut] |
Maintainer: | Deyu Ming <deyu.ming.16 at ucl.ac.uk> |
BugReports: | https://github.com/mingdeyu/dgpsi-R/issues |
License: | MIT + file LICENSE |
URL: | https://github.com/mingdeyu/dgpsi-R, https://mingdeyu.github.io/dgpsi-R/ |
NeedsCompilation: | no |
Language: | en-US |
Citation: | dgpsi citation info |
Materials: | README NEWS |
CRAN checks: | dgpsi results |
Reference manual: | dgpsi.pdf |
Vignettes: |
A Quick Guide to dgpsi Linked (D)GP Emulation DGP Emulation with the Heteroskedastic Gaussian Likelihood Sequential Design I Sequential Design II |
Package source: | dgpsi_2.2.0.tar.gz |
Windows binaries: | r-devel: dgpsi_2.1.6.zip, r-release: dgpsi_2.2.0.zip, r-oldrel: dgpsi_2.1.6.zip |
macOS binaries: | r-release (arm64): dgpsi_2.2.0.tgz, r-oldrel (arm64): dgpsi_2.2.0.tgz, r-release (x86_64): dgpsi_2.2.0.tgz, r-oldrel (x86_64): dgpsi_2.1.6.tgz |
Old sources: | dgpsi archive |
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