CRAN/E | dgpsi

dgpsi

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

Installation

About

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) . To get started with the package, see .

Citation dgpsi citation info
github.com/mingdeyu/dgpsi-R
mingdeyu.github.io/dgpsi-R/
Bug report File report

Key Metrics

Version 2.4.0
R ≥ 4.0
Published 2024-01-14 103 days ago
Needs compilation? no
License MIT
License File
CRAN checks dgpsi results
Language en-US

Downloads

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Last 30 days 231 -3%
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Last 365 days 3.043 +98%

Maintainer

Maintainer

Deyu Ming

deyu.ming.16@ucl.ac.uk

Authors

Deyu Ming

aut / cre / cph

Daniel Williamson

aut

Material

README
NEWS
Reference manual
Package source

Vignettes

A Quick Guide to dgpsi
Linked (D)GP Emulation
DGP Emulation with the Heteroskedastic Gaussian Likelihood
Sequential Design I
Sequential Design II

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

dgpsi archive

Depends

R ≥ 4.0

Imports

reticulate ≥ 1.26
benchmarkme ≥ 1.0.8
utils
ggplot2
ggforce
reshape2
patchwork
lhs
methods
stats
bitops
clhs
dplyr
uuid

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