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deepgp  

Bayesian Deep Gaussian Processes using MCMC
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("deepgp", "1.2.0")



Attach the package and use:
library("deepgp")
Maintained by
Annie S. Booth
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2020-10-29
Latest Update: 2024-08-19
Description:
Performs Bayesian posterior inference for deep Gaussian processes following Sauer, Gramacy, and Higdon (2023, ). See Sauer (2023, ) for comprehensive methodological details and for a variety of coding examples. Models are trained through MCMC including elliptical slice sampling of latent Gaussian layers and Metropolis-Hastings sampling of kernel hyperparameters. Vecchia-approximation for faster computation is implemented following Sauer, Cooper, and Gramacy (2022, ). Downstream tasks include sequential design through active learning Cohn/integrated mean squared error (ALC/IMSE; Sauer, Gramacy, and Higdon, 2023), optimization through expected improvement (EI; Gramacy, Sauer, and Wycoff, 2021 ), and contour location through entropy (Sauer, 2023). Models extend up to three layers deep; a one layer model is equivalent to typical Gaussian process regression. Incorporates OpenMP and SNOW parallelization and utilizes C/C++ under the hood.
How to cite:
Annie S. Booth (2020). deepgp: Bayesian Deep Gaussian Processes using MCMC. R package version 1.2.0, https://cran.r-project.org/web/packages/deepgp. Accessed 16 Jul. 2026.
Previous versions and publish date:
(2026-07-09 07:31), 0.1.0 (2020-10-29 11:20), 0.2.0 (2020-12-16 17:50), 0.2.1 (2021-07-15 17:40), 0.3.0 (2021-11-24 00:20), 0.3.1 (2021-12-07 09:00), 1.0.0 (2022-04-08 16:12), 1.0.1 (2022-06-20 21:40), 1.1.0 (2022-12-15 09:40), 1.1.1 (2023-08-07 22:50), 1.1.2 (2024-04-28 23:10), 1.1.3 (2024-08-19 17:00), 1.2.0 (2026-01-09 00:50)
Other packages that cited deepgp R package
View deepgp citation profile
Other R packages that deepgp depends, imports, suggests or enhances
Complete documentation for deepgp
Functions, R codes and Examples using the deepgp R package
Some associated functions: ALC . IMSE . continue . crps . deepgp-package . fit_one_layer . fit_three_layer . fit_two_layer . plot . predict . rmse . score . sq_dist . trim . 
Some associated R codes: ALC.R . IMSE.R . RcppExports.R . checks.R . continue.R . deepgp-package.R . fit.R . general.R . gibbs.R . gibbs_vecchia.R . mcmc.R . mcmc_vecchia.R . plot.R . predict.R . predict_vecchia.R . trim.R . vecchia.R .  Full deepgp package functions and examples
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