dgpsi: Interface to 'dgpsi' for Deep and Linked Gaussian Process Emulations

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 (2022) <arXiv:2107.01590>. To get started with the package, see <https://mingdeyu.github.io/dgpsi-R/>.

Version: 2.1.5
Depends: R (≥ 4.0)
Imports: reticulate (≥ 1.26), benchmarkme (≥ 1.0.8), utils, ggplot2, reshape2, patchwork
Suggests: knitr, rmarkdown, MASS, R.utils, spelling
Published: 2022-09-29
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


Package source: dgpsi_2.1.5.tar.gz
Windows binaries: r-devel: dgpsi_2.1.5.zip, r-release: dgpsi_2.1.5.zip, r-oldrel: dgpsi_2.1.5.zip
macOS binaries: r-release (arm64): dgpsi_2.1.5.tgz, r-oldrel (arm64): dgpsi_2.1.5.tgz, r-release (x86_64): dgpsi_2.1.5.tgz, r-oldrel (x86_64): dgpsi_2.1.5.tgz


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