Interface to the 'python' package 'dgpsi' for Gaussian process, deep Gaussian process,
and linked deep Gaussian process emulations of computer models and networks using stochastic imputation (SI).
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) <doi:10.48550/arXiv.2306.01212>. To get started with the package,
see <https://mingdeyu.github.io/dgpsi-R/>.
| Version: |
2.6.0 |
| Depends: |
R (≥ 4.0) |
| Imports: |
reticulate (≥ 1.26), benchmarkme (≥ 1.0.8), utils, ggplot2, ggforce, reshape2, patchwork, lhs, methods, stats, clhs, dplyr, uuid, tidyr, rlang, lifecycle, magrittr, visNetwork, parallel, kableExtra |
| Suggests: |
knitr, rmarkdown, MASS, R.utils, spelling |
| Published: |
2025-10-15 |
| DOI: |
10.32614/CRAN.package.dgpsi |
| 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 |