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dgpsi  

Interface to 'dgpsi' for Deep and Linked Gaussian Process Emulations
View on CRAN: Click here


Download and install dgpsi package within the R console
Install from CRAN:
install.packages("dgpsi")

Install from Github:
library("remotes")
install_github("cran/dgpsi")

Install by package version:
library("remotes")
install_version("dgpsi", "2.5.0")



Attach the package and use:
library("dgpsi")
Maintained by
Deyu Ming
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2022-09-29
Latest Update: 2023-09-03
Description:
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) and Ming, Williamson, & Guillas (2023) and Ming & Williamson (2023) . To get started with the package, see .
How to cite:
Deyu Ming (2022). dgpsi: Interface to 'dgpsi' for Deep and Linked Gaussian Process Emulations. R package version 2.5.0, https://cran.r-project.org/web/packages/dgpsi. Accessed 22 Dec. 2024.
Previous versions and publish date:
2.1.5 (2022-09-29 14:50), 2.1.6 (2023-02-08 15:50), 2.2.0 (2023-06-05 14:00), 2.3.0 (2023-09-03 18:40), 2.4.0 (2024-01-14 13:20)
Other packages that cited dgpsi R package
View dgpsi citation profile
Other R packages that dgpsi depends, imports, suggests or enhances
Complete documentation for dgpsi
Functions, R codes and Examples using the dgpsi R package
Some associated functions: Hetero . NegBin . Poisson . alm . combine . continue . design . dgp . draw . gp . init_py . kernel . lgp . mice . nllik . pack . pei . plot . predict . prune . read . set_imp . set_linked_idx . set_seed . summary . trace_plot . unpack . update . validate . vigf . window . write . 
Some associated R codes: alm.R . design.R . dgp.R . draw.R . gp.R . initi_py.R . kernel.R . lgp.R . likelihood.R . mice.R . packing.R . pei.R . plot.R . prediction.R . update.R . utils.R . validation.R . vigf.R . zzz.R .  Full dgpsi package functions and examples
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